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          <h2 data-itemtype="http://schema.stenci.la/Heading">Abstract</h2>
          <meta itemprop="description"
            content="As part of the Reproducibility Project: Cancer Biology, we published a Registered Report (Blum et al., 2015), that described how we intended to replicate selected experiments from the paper &quot;Transcriptional amplification in tumor cells with elevated c-Myc&quot; (Lin et al., 2012). Here we report the results. We found overexpression of c-Myc increased total levels of RNA in P493-6 Burkitt’s lymphoma cells; however, while the effect was in the same direction as the original study (Figure 3E; Lin et al., 2012), statistical significance and the size of the effect varied between the original study and the two different lots of serum tested in this replication. Digital gene expression analysis for a set of genes was also performed on P493-6 cells before and after c-Myc overexpression. Transcripts from genes that were active before c-Myc induction increased in expression following c-Myc overexpression, similar to the original study (Figure 3F; Lin et al., 2012). Transcripts from genes that were silent before c-Myc induction also increased in expression following c-Myc overexpression, while the original study concluded elevated c-Myc had no effect on silent genes (Figure 3F; Lin et al., 2012). Treating the data as paired, we found a statistically significant increase in gene expression for both active and silent genes upon c-Myc induction, with the change in gene expression greater for active genes compared to silent genes. Finally, we report meta-analyses for each result.">
          <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">As part of the <a
              href="https://osf.io/e81xl/wiki/home/" itemscope=""
              itemtype="http://schema.stenci.la/Link">Reproducibility Project: Cancer Biology</a>,
            we published a Registered Report (Blum et al., 2015), that described how we intended to
            replicate selected experiments from the paper &quot;Transcriptional amplification in
            tumor cells with elevated c-Myc&quot; (Lin et al., 2012). Here we report the results. We
            found overexpression of c-Myc increased total levels of RNA in P493-6 Burkitt’s lymphoma
            cells; however, while the effect was in the same direction as the original study (Figure
            3E; Lin et al., 2012), statistical significance and the size of the effect varied
            between the original study and the two different lots of serum tested in this
            replication. Digital gene expression analysis for a set of genes was also performed on
            P493-6 cells before and after c-Myc overexpression. Transcripts from genes that were
            active before c-Myc induction increased in expression following c-Myc overexpression,
            similar to the original study (Figure 3F; Lin et al., 2012). Transcripts from genes that
            were silent before c-Myc induction also increased in expression following c-Myc
            overexpression, while the original study concluded elevated c-Myc had no effect on
            silent genes (Figure 3F; Lin et al., 2012). Treating the data as paired, we found a
            statistically significant increase in gene expression for both active and silent genes
            upon c-Myc induction, with the change in gene expression greater for active genes
            compared to silent genes. Finally, we report meta-analyses for each result.</p>
        </section>
        <stencila-code-chunk itemscope="" itemtype="http://schema.stenci.la/CodeChunk"
          data-include="FALSE" data-programminglanguage="r">
          <pre class="language-r" itemscope="" itemtype="http://schema.stenci.la/CodeBlock"
            slot="text"><code>chooseCRANmirror(graphics=FALSE, ind=1) #selects a CRAN mirror

#Writes a manifest to local folder which includes all packages necessary to run each script called in the r markdown
cat(&#39;
library(httr)
library(tidyr)
library(reshape2)
library(pander)
library(car)
library(lsmeans)
library(coin)
library(MBESS)
library(metafor)
library(rjson)
library(psychometric)
&#39;,
file = &quot;manifest.R&quot;)

#Creates a .checkpoint folder (in tempdir for this example)
dir.create(file.path(tempdir(), &quot;.checkpoint&quot;), recursive = TRUE, showWarnings = FALSE)
options(install.packages.compile.from.source = &quot;no&quot;)

#Creates a checkpoint which allows for installation of packages as they existed on CRAN at the snapshot date of 2017-10-19
if ((&quot;checkpoint&quot; %in% installed.packages()[, 1]) == F) {
        install.packages(&quot;checkpoint&quot;)
}

#loads checkpoint
library(checkpoint)
checkpoint(&quot;2017-10-19&quot;, checkpointLocation = tempdir())
#Checkpoint in markdown code found at: https://github.com/RevolutionAnalytics/checkpoint/blob/master/vignettes/archive/using-checkpoint-with-knitr.Rmd 
</code></pre>
        </stencila-code-chunk>
        <figure itemscope="" itemtype="http://schema.stenci.la/Figure" title="R Scripts"><label
            data-itemprop="label">R Scripts</label>
          <stencila-code-chunk itemscope="" itemtype="http://schema.stenci.la/CodeChunk"
            data-include="FALSE" data-programminglanguage="r">
            <pre class="language-r" itemscope="" itemtype="http://schema.stenci.la/CodeBlock"
              slot="text"><code>RPCB_private_access &lt;- &quot;https://osf.io/mokeb/?view_only=756a4e87b872460d8d4ed25eae4d5150&quot;
#RPCB_private_access is an object that contains the private viewing link above or a private access token which is necessary to view and create scripts while this project is private. Upon publication, when the project is made public, a private access token or private link will no longer be necessary to render the rmd or view/access any of the scripts used in this Replication project.

#attaches only the packages neccessary to knit the r markdown document
library(httr) #version 1.2.1
library(rjson) #version 0.2.15
library(pander) #version 0.6.0
library(reshape2) #version 1.4.2

#Downloads R script &quot;download.OSF.file.R&quot;
GET(&quot;https://osf.io/hkpjb/?action=download&quot;, write_disk(&quot;download.OSF.file.R&quot;, overwrite = TRUE))
source(&quot;download.OSF.file.R&quot;)
#calls the download.OSF.file

#Downloads data file &#39;Study_48_Protocol_2_Analysis.R&#39; from https://osf.io/u7a5h/
download.OSF.file(GUID=&quot;u7a5h&quot;,Access_Token=RPCB_private_access,
file_name=&quot;Study_48_Protocol_2_Analysis.R&quot;)
source(&quot;Study_48_Protocol_2_Analysis.R&quot;)
#Calls &#39;data2&#39;
#Calls  &#39;contrast1&#39;
#Calls  &#39;contrast2&#39;

#Downloads data file &#39;Study_48_Accession#_Comparisons.R&#39; from https://osf.io/nvjkd/
download.OSF.file(GUID=&quot;nvjkd&quot;,Access_Token=RPCB_private_access,
file_name=&quot;Study_48_Accession#_Comparisons.R&quot;)
source(&quot;Study_48_Accession#_Comparisons.R&quot;)
#Calls &#39;common&#39; which is all 1212 genes common between the replication study and the original study

#Downloads data file &#39;Study_48_Protocols3&amp;4_Analysis.R &#39; from https://osf.io/2yj6v/
download.OSF.file(GUID=&quot;2yj6v&quot;,Access_Token=RPCB_private_access,
file_name=&quot;Study_48_Protocols3&amp;4_Analysis.R&quot;)
source(&quot;Study_48_Protocols3&amp;4_Analysis.R&quot;)
#calls &#39;a.lot1.0v1_P, a.lot2.0v1_P, a.lot1.0v24_P, a.lot2.0v24_P, a.lot1.1v24_P, a.lot2.1v24_P&#39; 
### which are the pvalues for the wilcoxon signed rank tests for lot1/lot2 for active genes
#calls &#39;s.lot1.0v1_P, s.lot2.0v1_P, s.lot1.0v24_P, s.lot2.0v24_P, s.lot1.1v24_P, s.lot2.1v24_P&#39; 
### which are the pvalues for the wilcoxon signed rank tests for lot1/lot2 for silent genes
#calls &#39;a.lot1.0v1_Z, a.lot2.0v1_Z, a.lot1.0v24_Z, a.lot2.0v24_Z, a.lot1.1v24_Z, a.lot2.1v24_Z&#39; 
### which are the Z statistics for the wilcoxon signed rank test for lot1/lot2 for active genes
#calls &#39;s.lot1.0v1_Z, s.lot2.0v1_Z, s.lot1.0v24_Z, s.lot2.0v24_Z, s.lot1.1v24_Z, s.lot2.1v24_Z&#39; 
### which are the Z statistics for the wilcoxon signed rank test for lot1/lot2 for silent genes
#calls &#39;a.lot1.0v1_n, a.lot2.0v1_n, a.lot1.0v24_n, a.lot2.0v24_n, a.lot1.1v24_n, a.lot2.1v24_n&#39; 
### which is n for the wilcoxon signed rank test for lot1/lot2 for active genes
#calls &#39;s.lot1.0v1_n, s.lot2.0v1_n, s.lot1.0v24_n, s.lot2.0v24_n, s.lot1.1v24_n, s.lot2.1v24_n&#39; 
###which is n for the wilcoxon signed rank test for lot1/lot2 for silent genes

#Downloads data file &#39;Study_48_Protocols3&amp;4_Analysis_Exploratory.R&#39; from https://osf.io/3k9sb/
download.OSF.file(GUID=&quot;3k9sb&quot;,Access_Token=RPCB_private_access,
file_name=&quot;Study_48_Protocols3&amp;4_Analysis_Exploratory.R&quot;)
source(&quot;Study_48_Protocols3&amp;4_Analysis_Exploratory.R&quot;)
#calls &#39;e_a.lot1.0v1_P, e_a.lot2.0v1_P, e_a.lot1.0v24_P, e_a.lot2.0v24_P, e_a.lot1.1v24_P, e_a.lot2.1v24_P&#39; 
### which are the pvalues for the wilcoxon rank sum tests for lot1/lot2 for active genes
#calls &#39;e_s.lot1.0v1_P, e_s.lot2.0v1_P, e_s.lot1.0v24_P, e_s.lot2.0v24_P, e_s.lot1.1v24_P, e_s.lot2.1v24_P&#39; 
### which are the pvalues for the wilcoxon rank sum tests for lot1/lot2 for silent genes
#calls &#39;e_a.lot1.0v1_Z, e_a.lot2.0v1_Z, e_a.lot1.0v24_Z, e_a.lot2.0v24_Z, e_a.lot1.1v24_Z, e_a.lot2.1v24_Z&#39; 
### which are the Z statistics for the wilcoxon rank sum test for lot1/lot2 for active genes
#calls &#39;e_s.lot1.0v1_Z, e_s.lot2.0v1_Z, e_s.lot1.0v24_Z, e_s.lot2.0v24_Z, e_s.lot1.1v24_Z, e_s.lot2.1v24_Z&#39; 
### which are the Z statistics for the wilcoxon rank sum test for lot1/lot2 for silent genes
#calls &#39;e_a.lot1.0v1_n, e_a.lot2.0v1_n, e_a.lot1.0v24_n, e_a.lot2.0v24_n, e_a.lot1.1v24_n, e_a.lot2.1v24_n&#39; 
### which is n for the wilcoxon rank sum test for lot1/lot2 for active genes
#calls &#39;e_s.lot1.0v1_n, e_s.lot2.0v1_n, e_s.lot1.0v24_n, e_s.lot2.0v24_n, e_s.lot1.1v24_n, e_s.lot2.1v24_n&#39; 
###which is n for the wilcoxon rank sum test for lot1/lot2 for silent genes

# Downloads data file &#39;Study_48_Protocols3&amp;4_Original_Data_ReAnalysis.R&#39; from https://osf.io/s845v/
download.OSF.file(GUID=&quot;s845v&quot;,Access_Token=RPCB_private_access,
file_name=&quot;Study_48_Protocols3&amp;4_Original_Data_ReAnalysis.R&quot;)
source(&quot;Study_48_Protocols3&amp;4_Original_Data_ReAnalysis.R&quot;)
#calls &#39; a.orig.0v1$statistic[[1]], a.orig.0v24$statistic[[1]]), a.orig.1v24$statistic[[1]])&#39; 
###Calls the W statistic for the Wilcoxon Rank Sum tests on active genes
#calls &#39;s.orig.0v1$statistic[[1]]), s.orig.0v24$statistic[[1]]), s.orig.1v24$statistic[[1]])&#39; 
###Calls the W statistic for the Wilcoxon Rank Sum tests on silent genes
#e_a.orig.0v1$p.value, e_a.orig.0v24$p.value, e_a.orig.1v24$p.value
###Calls the pval for the Wilcoxon Rank Sum tests on Active genes
#e_s.orig.0v1$p.value, e_s.orig.0v24$p.value, e_s.orig.1v24$p.value
###Calls the pval for the Wilcoxon Rank Sum tests on silent genes
#a.orig.0v1_n, a.orig.0v24_n, a.orig.0v24_n&#39; 
###which is the n for each Studies&#39;s Active genes
#s.orig.0v1_n, s.orig.0v24_n, s.orig.1v24_n&#39; 
###which is the n for each Studies&#39;s Silent genes

# Downloads data file &#39;Study_48_Protocols3&amp;4_Original_Data_ReAnalysis_Exploratory.R&#39; from https://osf.io/c74s6/
download.OSF.file(GUID=&quot;c74s6&quot;,Access_Token=RPCB_private_access,
file_name=&quot;Study_48_Protocols3&amp;4_Original_Data_ReAnalysis_Exploratory.R&quot;)
source(&quot;Study_48_Protocols3&amp;4_Original_Data_ReAnalysis_Exploratory.R&quot;)
#calls &#39; e_e_a.orig.0v1$statistic[[1]], e_e_a.orig.0v24$statistic[[1]]), e_e_a.orig.1v24$statistic[[1]])&#39; 
###Calls the W statistic for the Wilcoxon Rank Sum tests on active genes
#calls &#39;e_s.orig.0v1$statistic[[1]]), e_s.orig.0v24$statistic[[1]]), e_s.orig.1v24$statistic[[1]])&#39; 
###Calls the W statistic for the Wilcoxon Rank Sum tests on silent genes
#e_a.orig.0v1$p.value, e_a.orig.0v24$p.value, e_a.orig.1v24$p.value
###Calls the pval for the Wilcoxon Rank Sum tests on Active genes
#e_e_a.orig.0v1$p.value, e_e_a.orig.0v24$p.value, e_e_a.orig.1v24$p.value
###Calls the pval for the Wilcoxon Rank Sum tests on silent genes
#e_e_a.orig.0v1_n, e_a.orig.0v24_n, e_a.orig.0v24_n&#39; 
###which is the n for each Studies&#39;s Active genes
#e_a.orig.0v1_n, e_a.orig.0v24_n, e_a.orig.1v24_n&#39; 
###which is the n for each Studies&#39;s Silent genes

# Downloads R script &#39;Protocol 2 normality homoscedasiticity.R&#39; from https://osf.io/9wmq8/
download.OSF.file(GUID=&quot;9wmq8&quot;,Access_Token=RPCB_private_access,
file_name=&quot;Protocol 2 normality homoscedasiticity.R&quot;)
source(&quot;Protocol 2 normality homoscedasiticity.R&quot;)
# Calls &#39;zero&#39;
# Calls &#39;one&#39;
# Calls &#39;twentyfour&#39;

# Downloads R script &#39;Study_48_Meta_Analysis.R&#39; from https://osf.io/89e2b/
download.OSF.file(GUID=&quot;89e2b&quot;,Access_Token=RPCB_private_access,
                  file_name=&quot;Study_48_Meta_Analysis.R&quot;)
source(&quot;Study_48_Meta_Analysis.R&quot;)
# Calls &#39;exp_orig_d&#39; which is the original effect
# Calls &#39;exp_lot1_d&#39; which is the replication study lot 1 effect
# Calls &#39;exp_lot2_d&#39; which is the replication study lot 2 effect
# Calls &#39;exp_meta&#39; which is the replication study meta analysis
# Calls &#39;a_meta_0v1&#39;, &#39;a_meta_0v24&#39;, &amp; &#39;a_meta_1v24&#39;, which are the meta analyses for each respective test for Active Genes
# Calls &#39;s_meta_0v1&#39;, &#39;s_meta_0v24&#39;, &amp; &#39;s_meta_1v24&#39;, which are the meta analyses for each respective test for Silent Genes

# Downloads R script &#39;Replication_Study_functions.R&#39; from https://osf.io/duvht/
download.OSF.file(GUID=&quot;duvht&quot;,Access_Token=RPCB_private_access,
file_name=&quot;Replication_Study_functions.R&quot;)
source(&quot;Replication_Study_functions.R&quot;)
# Calls &#39;scinot&#39; which is a function to write in scientific notation in Rmd

# Downloads R script &#39;Study_48_Figure_2_Supplemental_Tables.csv&#39; from https://osf.io/rynzs/
download.OSF.file(GUID=&quot;rynzs&quot;,Access_Token=RPCB_private_access,
file_name=&quot;Study_48_Figure_2_Supplemental_Tables.csv&quot;)
#reads csv file of Table 1 csv file
dat &lt;- read.csv(&quot;Study_48_Figure_2_Supplemental_Tables.csv&quot;, header=T, sep=&quot;,&quot;)
# Calls &#39;dat&#39; which is data from Supplemental tables
</code></pre>
          </stencila-code-chunk>
        </figure>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">##Replication Study:
          Transcriptional amplification in tumor cells with elevated c-Myc##</p>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">L. Michelle Lewis<sup
            itemscope="" itemtype="http://schema.stenci.la/Superscript"><span
              data-itemtype="http://schema.org/Number">1</span></sup>, Meredith C. Edwards<sup
            itemscope="" itemtype="http://schema.stenci.la/Superscript"><span
              data-itemtype="http://schema.org/Number">1</span></sup>, Zachary R. Meyers<sup
            itemscope="" itemtype="http://schema.stenci.la/Superscript"><span
              data-itemtype="http://schema.org/Number">1</span></sup>, C. Conover Talbot Jr.<sup
            itemscope="" itemtype="http://schema.stenci.la/Superscript"><span
              data-itemtype="http://schema.org/Number">2</span></sup>, Haiping Hao<sup itemscope=""
            itemtype="http://schema.stenci.la/Superscript"><span
              data-itemtype="http://schema.org/Number">2</span></sup>, David Blum<sup itemscope=""
            itemtype="http://schema.stenci.la/Superscript"><span
              data-itemtype="http://schema.org/Number">1</span></sup>, Reproducibility
          Project:Cancer Biology<sup itemscope=""
            itemtype="http://schema.stenci.la/Superscript"></sup><sup itemscope=""
            itemtype="http://schema.stenci.la/Superscript">*</sup></p>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph"><sup itemscope=""
            itemtype="http://schema.stenci.la/Superscript"></sup> The RP:CB core team consists of
          Elizabeth Iorns (Science Exchange, Palo Alto, California), Rachel Tsui (Science Exchange,
          Palo Alto, California), Alexandria Denis (Center for Open Science, Charlottesville,
          Virginia), Nicole Perfito (Science Exchange, Palo Alto, California), and Timothy M.
          Errington (Center for Open Science, Charlottesville, Virginia).</p>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph"><sup itemscope=""
            itemtype="http://schema.stenci.la/Superscript"><span
              data-itemtype="http://schema.org/Number">1</span></sup> University of Georgia,
          Bioexpression and Fermentation Facility, Athens, Georgia, United States</p>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph"><sup itemscope=""
            itemtype="http://schema.stenci.la/Superscript"><span
              data-itemtype="http://schema.org/Number">2</span></sup> Johns Hopkins University, Deep
          Sequencing and Microarray Core Facility, Baltimore, Maryland, United States</p>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph"><sup itemscope=""
            itemtype="http://schema.stenci.la/Superscript">*</sup> Correspondence to Nicole Perfito
          (<a href="mailto:nicole@scienceexchange.com" itemscope=""
            itemtype="http://schema.stenci.la/Link">nicole@scienceexchange.com</a>) and Timothy M.
          Errington (<a href="mailto:tim@cos.io" itemscope=""
            itemtype="http://schema.stenci.la/Link">tim@cos.io</a>)</p>
        <h2 itemscope="" itemtype="http://schema.stenci.la/Heading" id="competing-interests">
          Competing Interests</h2>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">RP:CB: EI, RT, NP: Employed by
          and hold shares in Science Exchange Inc.</p>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">LML, MCE, ZRM, DB:
          Bioexpression and Fermentation Facility, University of Georgia is a Science Exchange
          associated lab.</p>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">CCT, HH: Deep Sequencing and
          Microarray Core Facility, Johns Hopkins University is a Science Exchange associated lab.
        </p>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">The other authors declare no
          conflicts of interest exist.</p>
        <h2 itemscope="" itemtype="http://schema.stenci.la/Heading" id="funding">Funding</h2>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">The Reproducibility Project:
          Cancer Biology is funded by the Laura and John Arnold Foundation, provided to the Center
          for Open Science in collaboration with Science Exchange. The funder had no role in study
          design, data collection and interpretation, or the decision to submit the work for
          publication.</p>
        <h2 itemscope="" itemtype="http://schema.stenci.la/Heading"
          id="private-link-for-additional-content-related-to-the-experimentation-raw-files-methods-notes-scripts-etc">
          Private Link for additional content related to the experimentation (raw files, methods
          notes, scripts, etc)</h2>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph"><a
            href="https://osf.io/mokeb/?view_only=756a4e87b872460d8d4ed25eae4d5150" itemscope=""
            itemtype="http://schema.stenci.la/Link">https://osf.io/mokeb/?view_only=756a4e87b872460d8d4ed25eae4d5150</a>
        </p>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">Suggested browser to view:
          Chrome</p>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">To view any osf.io link in the
          manuscript add this extension to the end of it in your browser:
          &quot;?view_only=756a4e87b872460d8d4ed25eae4d5150&quot;</p>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">List of private links for
          experiments reported:</p>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">Conditional expression of c-Myc
          in P493-6 cells and total RNA levels (Figure 1):</p>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph"><a
            href="https://osf.io/tfd57/?view_only=756a4e87b872460d8d4ed25eae4d5150" itemscope=""
            itemtype="http://schema.stenci.la/Link">https://osf.io/tfd57/?view_only=756a4e87b872460d8d4ed25eae4d5150</a>
        </p>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">Digital gene expression
          following c-Myc overexpression (Figure 2):</p>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph"><a
            href="https://osf.io/fn2y4/?view_only=756a4e87b872460d8d4ed25eae4d5150" itemscope=""
            itemtype="http://schema.stenci.la/Link">https://osf.io/fn2y4/?view_only=756a4e87b872460d8d4ed25eae4d5150</a>
        </p>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">Meta-analyses (Figure 3):</p>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph"><a
            href="https://osf.io/5yscz/?view_only=756a4e87b872460d8d4ed25eae4d5150" itemscope=""
            itemtype="http://schema.stenci.la/Link">https://osf.io/5yscz/?view_only=756a4e87b872460d8d4ed25eae4d5150</a>
        </p>
        <h2 itemscope="" itemtype="http://schema.stenci.la/Heading" id="introduction">Introduction
        </h2>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">The <a
            href="https://osf.io/e81xl/wiki/home/" itemscope=""
            itemtype="http://schema.stenci.la/Link">Reproducibility Project: Cancer Biology</a>
          (RP:CB) is a collaboration between the <a href="https://centerforopenscience.org"
            itemscope="" itemtype="http://schema.stenci.la/Link">Center for Open Science</a> and <a
            href="https://www.scienceexchange.com" itemscope=""
            itemtype="http://schema.stenci.la/Link">Science Exchange</a> that seeks to address
          concerns about reproducibility in scientific research by conducting replications of
          selected experiments from a number of high-profile papers in the field of cancer biology
          (Errington et al., 2014). For each of these papers a Registered Report detailing the
          proposed experimental designs and protocols for the replications was peer reviewed and
          published prior to data collection. The present paper is a Replication Study that reports
          the results of the replication experiments detailed in the Registered Report (Blum et al.,
          2015) for a 2012 paper by Lin et al., and uses a number of approaches to compare the
          outcomes of the original experiments and the replications.</p>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">In 2012, Lin et al. reported
          results that the c-Myc transcription factor, a potent oncogene that is frequently
          overexpressed in a large percentage of cancers, globally amplifies the expression of
          actively transcribed genes, opposed to regulating specific target genes. Using the P493-6
          cell line, a model for <em itemscope=""
            itemtype="http://schema.stenci.la/Emphasis">MYC</em> activation in Burkitt’s lymphoma,
          total levels of RNA per cell were reported to increase when c-Myc was highly expressed
          compared to conditions where c-Myc expression was low. Additionally, active genes in cells
          with low c-Myc levels were reported to increase in expression upon c-Myc induction, in
          contrast to genes that were silent under low c-Myc conditions that did not change.</p>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">The Registered Report for the
          2012 paper by Lin et al. described the experiments to be replicated (Figures 1B and 3E-F),
          and summarized the current evidence for these findings (Blum et al., 2015). Since that
          publication there have been additional studies investigating the ability c-Myc to
          influence the global gene expression output of cells. Similar to Lin et al. other studies
          have reported c-Myc dependent amplification of cellular RNA (Hart et al., 2015; Hsu et
          al., 2015; Nie et al., 2012; Sabò et al., 2014), although this observation was not
          reported in all biological systems (Fagnocchi et al., 2016; Sabò et al., 2014; Walz et
          al., 2014). It has been suggested c-Myc regulates specific genes that indirectly lead to
          RNA amplification (Sabò et al., 2014; Sabò and Amati, 2014; Walz et al., 2014). This has
          also been suggested of MYCN (Duffy et al., 2014). The reported differences could be a
          result of the intrinsic variation between cell lines in maintaining the transcriptome
          (Trakhtenberg et al., 2016). Indeed, a recent study reported that distinct transcriptional
          regulation can be accounted for by differences in promoter affinity under different c-Myc
          expression levels (Lorenzin et al., 2016).</p>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">The outcome measures reported
          in this Replication Study will be aggregated with those from the other Replication Studies
          to create a dataset that will be examined to provide evidence about reproducibility of
          cancer biology research, and to identify factors that influence reproducibility more
          generally.</p>
        <h2 itemscope="" itemtype="http://schema.stenci.la/Heading" id="results-and-discussion">
          Results and Discussion</h2>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph"><em itemscope=""
            itemtype="http://schema.stenci.la/Emphasis">Conditional expression of c-Myc in the
            B-cell line P493-6</em></p>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">To test the effects of
          increased levels of c-Myc on gene expression we used the same human P493-6 B cell line of
          Burkitt’s lymphoma that contains a conditional tetracycline-repressive <em itemscope=""
            itemtype="http://schema.stenci.la/Emphasis">MYC</em> transgene (Pajic et al., 2000;
          Schuhmacher et al., 1999) as the original study. We performed Western blot analysis to
          confirm c-Myc expression could be reduced to very low levels and then reactivated after
          removal of tetracycline. This is comparable to what was reported in Figure 1B of Lin et
          al., 2012 and described in Protocol 1 in the Registered Report (Blum et al., 2015). Since
          proliferation of P493-6 cells depend on c-Myc expression and the presence of serum (Pajic
          et al., 2000; Schuhmacher et al., 1999), with serum reported to stimulate a majority of
          genes independent of c-Myc (Schlosser et al., 2005), we maintained these cells in separate
          lots of serum to assess whether the results differed. For cells maintained in both lots of
          serum, treatment with tetracycline resulted in a strong decrease in c-Myc protein levels
          (Figure 1A). After removal of tetracycline, c-Myc levels increased over time approaching
          the levels observed in tetracycline-free conditions.</p>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph"><em itemscope=""
            itemtype="http://schema.stenci.la/Emphasis">Total RNA levels following c-Myc
            overexpression</em></p>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">We sought to independently
          replicate whether increased levels of c-Myc resulted in increased absolute levels of RNA.
          This experiment is similar to what was reported in Figure 3E of Lin et al., 2012 and used
          the same extraction method for total RNA quantification, which was described in Protocol 2
          in the Registered Report (Blum et al., 2015). Total RNA was isolated from P493-6 cells 0,
          1, and 24 hr after tetracycline release and the amount of RNA per 1,000 cells was
          quantified (Figure 1B). We found that under conditions where c-Myc expression was low (0
          hr), there was a mean of <stencila-code-expression programming-language="r" itemscope=""
            itemtype="http://schema.stenci.la/CodeExpression"><code class="r"
              slot="text">round(mean(subset(data2, Lot==1 &amp; Time==0)$value),2)</code><output
              slot="output"></output></stencila-code-expression> ng total RNA per 1,000 cells (ng/1k
          cells) <a href="" itemscope="" itemtype="http://schema.stenci.la/Link">n=
            <stencila-code-expression programming-language="r" itemscope=""
              itemtype="http://schema.stenci.la/CodeExpression"><code class="r"
                slot="text">length(subset(data2, Lot==1 &amp; Time==0)$value)</code><output
                slot="output"></output></stencila-code-expression>, <em itemscope=""
              itemtype="http://schema.stenci.la/Emphasis">SD</em>=<stencila-code-expression
              programming-language="r" itemscope=""
              itemtype="http://schema.stenci.la/CodeExpression"><code class="r"
                slot="text">formatC(sd(subset(data2, Lot==1 &amp;
                Time==0)$value),2,format="f")</code><output slot="output"></output>
            </stencila-code-expression></a>, which increased to <stencila-code-expression
            programming-language="r" itemscope="" itemtype="http://schema.stenci.la/CodeExpression">
            <code class="r" slot="text">round(mean(subset(data2, Lot==1 &amp;
              Time==24)$value),2)</code><output slot="output"></output></stencila-code-expression>
          ng/1k cells <a href="" itemscope="" itemtype="http://schema.stenci.la/Link">n=
            <stencila-code-expression programming-language="r" itemscope=""
              itemtype="http://schema.stenci.la/CodeExpression"><code class="r"
                slot="text">length(subset(data2, Lot==1 &amp; Time==24)$value)</code><output
                slot="output"></output></stencila-code-expression>, <em itemscope=""
              itemtype="http://schema.stenci.la/Emphasis">SD</em>=<stencila-code-expression
              programming-language="r" itemscope=""
              itemtype="http://schema.stenci.la/CodeExpression"><code class="r"
                slot="text">round(sd(subset(data2, Lot==1 &amp; Time==24)$value),2)</code><output
                slot="output"></output></stencila-code-expression></a> when c-Myc expression was
          high (24 hr), a <stencila-code-expression programming-language="r" itemscope=""
            itemtype="http://schema.stenci.la/CodeExpression"><code class="r"
              slot="text">round(mean(subset(data2, Lot==1 &amp; Time==24)$value)/mean(subset(data2,
              Lot==1 &amp; Time==0)$value),2)</code><output slot="output"></output>
          </stencila-code-expression> times increase, for serum lot one, which was not statistically
          significant (<em itemscope="" itemtype="http://schema.stenci.la/Emphasis">t</em>(
          <stencila-code-expression programming-language="r" itemscope=""
            itemtype="http://schema.stenci.la/CodeExpression"><code class="r"
              slot="text">contrast1$df</code><output slot="output"></output>
          </stencila-code-expression>) = <stencila-code-expression programming-language="r"
            itemscope="" itemtype="http://schema.stenci.la/CodeExpression"><code class="r"
              slot="text">round(contrast1$t.ratio,2)</code><output slot="output"></output>
          </stencila-code-expression>, <em itemscope=""
            itemtype="http://schema.stenci.la/Emphasis">p</em> = <stencila-code-expression
            programming-language="r" itemscope="" itemtype="http://schema.stenci.la/CodeExpression">
            <code class="r"
              slot="text">sub('^(-)?0[.]','\\1.',round(contrast1$p.value,3))</code><output
              slot="output"></output></stencila-code-expression>). Serum lot two changed from a mean
          of <stencila-code-expression programming-language="r" itemscope=""
            itemtype="http://schema.stenci.la/CodeExpression"><code class="r"
              slot="text">round(mean(subset(data2, Lot==2 &amp; Time==0)$value),2)</code><output
              slot="output"></output></stencila-code-expression> ng/1k cells <a href="" itemscope=""
            itemtype="http://schema.stenci.la/Link">n=<stencila-code-expression
              programming-language="r" itemscope=""
              itemtype="http://schema.stenci.la/CodeExpression"><code class="r"
                slot="text">length(subset(data2, Lot==2 &amp; Time==0)$value)</code><output
                slot="output"></output></stencila-code-expression>, <em itemscope=""
              itemtype="http://schema.stenci.la/Emphasis">SD</em>=<stencila-code-expression
              programming-language="r" itemscope=""
              itemtype="http://schema.stenci.la/CodeExpression"><code class="r"
                slot="text">round(sd(subset(data2, Lot==2 &amp; Time==0)$value),2)</code><output
                slot="output"></output></stencila-code-expression></a> at 0 hr to
          <stencila-code-expression programming-language="r" itemscope=""
            itemtype="http://schema.stenci.la/CodeExpression"><code class="r"
              slot="text">round(mean(subset(data2, Lot==2 &amp; Time==24)$value),2)</code><output
              slot="output"></output></stencila-code-expression> ng/1k cells <a href="" itemscope=""
            itemtype="http://schema.stenci.la/Link">n=<stencila-code-expression
              programming-language="r" itemscope=""
              itemtype="http://schema.stenci.la/CodeExpression"><code class="r"
                slot="text">length(subset(data2, Lot==2 &amp; Time==24)$value)</code><output
                slot="output"></output></stencila-code-expression>, <em itemscope=""
              itemtype="http://schema.stenci.la/Emphasis">SD</em>=<stencila-code-expression
              programming-language="r" itemscope=""
              itemtype="http://schema.stenci.la/CodeExpression"><code class="r"
                slot="text">round(sd(subset(data2, Lot==2 &amp; Time==24)$value),2)</code><output
                slot="output"></output></stencila-code-expression></a> at 24 hr, a
          <stencila-code-expression programming-language="r" itemscope=""
            itemtype="http://schema.stenci.la/CodeExpression"><code class="r"
              slot="text">round(mean(subset(data2, Lot==2 &amp; Time==24)$value)/mean(subset(data2,
              Lot==2 &amp; Time==0)$value),2)</code><output slot="output"></output>
          </stencila-code-expression> times increase, which was statistically significant (<em
            itemscope="" itemtype="http://schema.stenci.la/Emphasis">t</em>(
          <stencila-code-expression programming-language="r" itemscope=""
            itemtype="http://schema.stenci.la/CodeExpression"><code class="r"
              slot="text">contrast2$df</code><output slot="output"></output>
          </stencila-code-expression> = <stencila-code-expression programming-language="r"
            itemscope="" itemtype="http://schema.stenci.la/CodeExpression"><code class="r"
              slot="text">round(contrast2$t.ratio,2)</code><output slot="output"></output>
          </stencila-code-expression>, <em itemscope=""
            itemtype="http://schema.stenci.la/Emphasis">p</em> = <stencila-code-expression
            programming-language="r" itemscope="" itemtype="http://schema.stenci.la/CodeExpression">
            <code class="r"
              slot="text">sub('^(-)?0[.]','\\1.',round(contrast2$p.value,4))</code><output
              slot="output"></output></stencila-code-expression>). This compares to the original
          study, which reported a mean of <stencila-code-expression programming-language="r"
            itemscope="" itemtype="http://schema.stenci.la/CodeExpression"><code class="r"
              slot="text">round(mean(zero),2)</code><output slot="output"></output>
          </stencila-code-expression> ng/1k cells at 0 hr, which increased to
          <stencila-code-expression programming-language="r" itemscope=""
            itemtype="http://schema.stenci.la/CodeExpression"><code class="r"
              slot="text">round(mean(twentyfour),2)</code><output slot="output"></output>
          </stencila-code-expression> ng/1k cells at 24 hr, a <stencila-code-expression
            programming-language="r" itemscope="" itemtype="http://schema.stenci.la/CodeExpression">
            <code class="r" slot="text">round(mean(twentyfour)/mean(zero),2)</code><output
              slot="output"></output></stencila-code-expression> times increase in total RNA levels.
          In both studies there was a minor decrease at 1 hr after tetracycline release when c-Myc
          levels begin to become detectable. Total RNA per 1,000 cells at 0 hr were much lower in
          this replication attempt than those reported in the original study, although changes in
          total RNA levels were in the same direction following c-Myc expression. Similarly, another
          independent study that measured total RNA from P493-6 cells reported a different level at
          0 hr (~3 ng/1k cells), while also reporting increased levels following c-Myc expression
          (Sabò et al., 2014). There are multiple possible explanations for these differences, such
          as variation in RNA expression during cell culture passage (Hiorns et al., 2004), low
          yield of the RNA isolation procedure (e.g. incomplete homogenization), or the high
          variance associated with manual cell counts using a hemacytometer (Biggs and Macmillan,
          1948; Nielson et al., 1991). To summarize, for this experiment we found results that were
          in the same direction as the original study and not statistically significant for serum
          lot one, while statistically significant for serum lot two.</p>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph"><em itemscope=""
            itemtype="http://schema.stenci.la/Emphasis">Digital gene expression following c-Myc
            overexpression</em></p>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">To test whether c-Myc
          expression amplifies the existing gene expression program, digital gene expression
          analysis using the NanoString nCounter platform was performed on a set of genes from
          multiple functional categories. This experiment is similar to what was reported in Figure
          3F and Table S1 of Lin et al., 2012 and described in Protocols 3-4 in the Registered
          Report (Blum et al., 2015). We quantified mRNA levels/cell of <stencila-code-expression
            programming-language="r" itemscope="" itemtype="http://schema.stenci.la/CodeExpression">
            <code class="r" slot="text">prettyNum(length(unique(comb.means$Accession)),
              big.mark=",")</code><output slot="output"></output></stencila-code-expression> genes,
          of which <stencila-code-expression programming-language="r" itemscope=""
            itemtype="http://schema.stenci.la/CodeExpression"><code class="r"
              slot="text">prettyNum(length(intersect(comb.means$Accession, o.comb.means$Accession)),
              big.mark=",")</code><output slot="output"></output></stencila-code-expression> were
          the same genes as the <stencila-code-expression programming-language="r" itemscope=""
            itemtype="http://schema.stenci.la/CodeExpression"><code class="r"
              slot="text">prettyNum(length(unique(o.comb.means$Accession)),
              big.mark=",")</code><output slot="output"></output></stencila-code-expression> genes
          interrogated in the original study. We used the same criteria as the original study to
          classify a gene as silent (expression was less than 0.5 transcript/cell at time 0 hr) or
          active (more than one transcript/cell at time 0 hr). In cells with low levels of c-Myc (0
          hr) there were <stencila-code-expression programming-language="r" itemscope=""
            itemtype="http://schema.stenci.la/CodeExpression"><code class="r"
              slot="text">length(active_0hr_l1)</code><output slot="output"></output>
          </stencila-code-expression> active genes with a median expression of
          <stencila-code-expression programming-language="r" itemscope=""
            itemtype="http://schema.stenci.la/CodeExpression"><code class="r"
              slot="text">formatC(median(active_0hr_l1),2,format="f")</code><output
              slot="output"></output></stencila-code-expression>, and <stencila-code-expression
            programming-language="r" itemscope="" itemtype="http://schema.stenci.la/CodeExpression">
            <code class="r" slot="text">length(silent_0hr_l1)</code><output slot="output"></output>
          </stencila-code-expression> silent genes with a median expression of
          <stencila-code-expression programming-language="r" itemscope=""
            itemtype="http://schema.stenci.la/CodeExpression"><code class="r"
              slot="text">round(median(silent_0hr_l1),3)</code><output slot="output"></output>
          </stencila-code-expression>, for serum lot one. For active genes,
          <stencila-code-expression programming-language="r" itemscope=""
            itemtype="http://schema.stenci.la/CodeExpression"><code class="r"
              slot="text">round(length(which((active_1hr_l1-active_0hr_l1)&gt;0))/length(active_0hr_l1)*100)</code><output
              slot="output"></output></stencila-code-expression>% of the genes increased from 0 hr
          to 1 hr, <stencila-code-expression programming-language="r" itemscope=""
            itemtype="http://schema.stenci.la/CodeExpression"><code class="r"
              slot="text">round(length(which((active_24hr_l1-active_0hr_l1)&gt;0))/length(active_0hr_l1)*100)</code><output
              slot="output"></output></stencila-code-expression>% increased from 0 hr to 24 hr, and
          <stencila-code-expression programming-language="r" itemscope=""
            itemtype="http://schema.stenci.la/CodeExpression"><code class="r"
              slot="text">round(length(which((active_24hr_l1-active_1hr_l1)&gt;0))/length(active_0hr_l1)*100)</code><output
              slot="output"></output></stencila-code-expression>% increased from 1 hr to 24 hr upon
          c-Myc induction. This corresponds to a <stencila-code-expression programming-language="r"
            itemscope="" itemtype="http://schema.stenci.la/CodeExpression"><code class="r"
              slot="text">round(median(active_1hr_l1)/median(active_0hr_l1),2)</code><output
              slot="output"></output></stencila-code-expression>, <stencila-code-expression
            programming-language="r" itemscope="" itemtype="http://schema.stenci.la/CodeExpression">
            <code class="r"
              slot="text">formatC(median(active_24hr_l1)/median(active_0hr_l1),2,format="f")</code><output
              slot="output"></output></stencila-code-expression>, and <stencila-code-expression
            programming-language="r" itemscope="" itemtype="http://schema.stenci.la/CodeExpression">
            <code class="r"
              slot="text">round(median(active_24hr_l1)/median(active_1hr_l1),2)</code><output
              slot="output"></output></stencila-code-expression> times increase in median
          expression, respectively (Figure 2, Figure 2 - figure supplement 1). For silent genes,
          <stencila-code-expression programming-language="r" itemscope=""
            itemtype="http://schema.stenci.la/CodeExpression"><code class="r"
              slot="text">round(length(which((silent_1hr_l1-silent_0hr_l1)&gt;0))/length(silent_0hr_l1)*100)</code><output
              slot="output"></output></stencila-code-expression>% of the genes increased from 0 hr
          to 1 hr, <stencila-code-expression programming-language="r" itemscope=""
            itemtype="http://schema.stenci.la/CodeExpression"><code class="r"
              slot="text">round(length(which((silent_24hr_l1-silent_0hr_l1)&gt;0))/length(silent_0hr_l1)*100)</code><output
              slot="output"></output></stencila-code-expression>% increased from 0 hr to 24 hr, and
          <stencila-code-expression programming-language="r" itemscope=""
            itemtype="http://schema.stenci.la/CodeExpression"><code class="r"
              slot="text">round(length(which((silent_24hr_l1-silent_1hr_l1)&gt;0))/length(silent_0hr_l1)*100)</code><output
              slot="output"></output></stencila-code-expression>% increased from 1 hr to 24 hr,
          corresponding to a <stencila-code-expression programming-language="r" itemscope=""
            itemtype="http://schema.stenci.la/CodeExpression"><code class="r"
              slot="text">round(median(silent_1hr_l1)/median(silent_0hr_l1),2)</code><output
              slot="output"></output></stencila-code-expression> and <stencila-code-expression
            programming-language="r" itemscope="" itemtype="http://schema.stenci.la/CodeExpression">
            <code class="r"
              slot="text">round(median(silent_24hr_l1)/median(silent_0hr_l1),2)</code><output
              slot="output"></output></stencila-code-expression> times increase, and a
          <stencila-code-expression programming-language="r" itemscope=""
            itemtype="http://schema.stenci.la/CodeExpression"><code class="r"
              slot="text">abs(round((median(silent_24hr_l1)-median(silent_1hr_l1))/(median(silent_24hr_l1)),2))</code><output
              slot="output"></output></stencila-code-expression> times decrease in median
          expression, respectively (Figure 2, Figure 2 - figure supplement 1). Serum lot two gave
          similar results, although there were variations in the number of genes identified as
          silent or active as well as the degree of increase among the conditions (Figure 2, Figure
          2 - figure supplement 1). This compares to the original study that identified
          <stencila-code-expression programming-language="r" itemscope=""
            itemtype="http://schema.stenci.la/CodeExpression"><code class="r"
              slot="text">length(active_0hr)</code><output slot="output"></output>
          </stencila-code-expression> active genes with a median expression of
          <stencila-code-expression programming-language="r" itemscope=""
            itemtype="http://schema.stenci.la/CodeExpression"><code class="r"
              slot="text">round(median(active_0hr),2)</code><output slot="output"></output>
          </stencila-code-expression>, and <stencila-code-expression programming-language="r"
            itemscope="" itemtype="http://schema.stenci.la/CodeExpression"><code class="r"
              slot="text">length(silent_0hr)</code><output slot="output"></output>
          </stencila-code-expression> silent genes with a median expression of
          <stencila-code-expression programming-language="r" itemscope=""
            itemtype="http://schema.stenci.la/CodeExpression"><code class="r"
              slot="text">formatC(median(silent_0hr),2,format="f")</code><output
              slot="output"></output></stencila-code-expression> (more than half the silent genes
          did not have a reported expression value). Active genes in the original study, increased
          <stencila-code-expression programming-language="r" itemscope=""
            itemtype="http://schema.stenci.la/CodeExpression"><code class="r"
              slot="text">round(length(which((active_1hr-active_0hr)&gt;0))/length(active_0hr)*100)</code><output
              slot="output"></output></stencila-code-expression>% from 0 hr to 1 hr,
          <stencila-code-expression programming-language="r" itemscope=""
            itemtype="http://schema.stenci.la/CodeExpression"><code class="r"
              slot="text">round(length(which((active_24hr-active_0hr)&gt;0))/length(active_0hr)*100)</code><output
              slot="output"></output></stencila-code-expression>% from 0 hr to 24 hr, and
          <stencila-code-expression programming-language="r" itemscope=""
            itemtype="http://schema.stenci.la/CodeExpression"><code class="r"
              slot="text">round(length(which((active_24hr-active_1hr)&gt;0))/length(active_0hr)*100)</code><output
              slot="output"></output></stencila-code-expression>% from 1 hr to 24 hr upon c-Myc
          induction, corresponding to a <stencila-code-expression programming-language="r"
            itemscope="" itemtype="http://schema.stenci.la/CodeExpression"><code class="r"
              slot="text">round(median(active_1hr)/median(active_0hr),2)</code><output
              slot="output"></output></stencila-code-expression>, <stencila-code-expression
            programming-language="r" itemscope="" itemtype="http://schema.stenci.la/CodeExpression">
            <code class="r"
              slot="text">round(median(active_24hr)/median(active_0hr),2)</code><output
              slot="output"></output></stencila-code-expression>, and <stencila-code-expression
            programming-language="r" itemscope="" itemtype="http://schema.stenci.la/CodeExpression">
            <code class="r"
              slot="text">round(median(active_24hr)/median(active_1hr),2)</code><output
              slot="output"></output></stencila-code-expression> times increase in median
          expression, respectively. Silent genes in the original study, increased
          <stencila-code-expression programming-language="r" itemscope=""
            itemtype="http://schema.stenci.la/CodeExpression"><code class="r"
              slot="text">round(length(which((silent_1hr-silent_0hr)&gt;0))/length(silent_0hr)*100)</code><output
              slot="output"></output></stencila-code-expression>% from 0 hr to 1 hr,
          <stencila-code-expression programming-language="r" itemscope=""
            itemtype="http://schema.stenci.la/CodeExpression"><code class="r"
              slot="text">round(length(which((silent_24hr-silent_0hr)&gt;0))/length(silent_0hr)*100)</code><output
              slot="output"></output></stencila-code-expression>% from 0 hr to 24 hr, and
          <stencila-code-expression programming-language="r" itemscope=""
            itemtype="http://schema.stenci.la/CodeExpression"><code class="r"
              slot="text">round(length(which((silent_24hr-silent_1hr)&gt;0))/length(silent_0hr)*100)</code><output
              slot="output"></output></stencila-code-expression>% from 1 hr to 24 hr, with the
          median expression unchanged among conditions. In addition, we further examined the extent
          of overlap of active and silent genes between the original study and this replication
          attempt. Of the <stencila-code-expression programming-language="r" itemscope=""
            itemtype="http://schema.stenci.la/CodeExpression"><code class="r"
              slot="text">prettyNum(nrow(common), big.mark=",")</code><output
              slot="output"></output></stencila-code-expression> genes that were interrogated in
          both studies, <stencila-code-expression programming-language="r" itemscope=""
            itemtype="http://schema.stenci.la/CodeExpression"><code class="r"
              slot="text">round(ovl1_active_percent, digits = 1)</code><output
              slot="output"></output></stencila-code-expression>% (<stencila-code-expression
            programming-language="r" itemscope="" itemtype="http://schema.stenci.la/CodeExpression">
            <code class="r" slot="text">ovl1_active</code><output slot="output"></output>
          </stencila-code-expression>/<stencila-code-expression programming-language="r"
            itemscope="" itemtype="http://schema.stenci.la/CodeExpression"><code class="r"
              slot="text">total_common_active</code><output slot="output"></output>
          </stencila-code-expression>) of the active genes we identified in serum lot one were also
          active in the original study (<stencila-code-expression programming-language="r"
            itemscope="" itemtype="http://schema.stenci.la/CodeExpression"><code class="r"
              slot="text">round(ovl2_active_percent, digits=1)</code><output slot="output"></output>
          </stencila-code-expression>% (<stencila-code-expression programming-language="r"
            itemscope="" itemtype="http://schema.stenci.la/CodeExpression"><code class="r"
              slot="text">ovl2_active</code><output slot="output"></output>
          </stencila-code-expression>/<stencila-code-expression programming-language="r"
            itemscope="" itemtype="http://schema.stenci.la/CodeExpression"><code class="r"
              slot="text">total_common_active</code><output slot="output"></output>
          </stencila-code-expression>) for serum lot two). For silent genes,
          <stencila-code-expression programming-language="r" itemscope=""
            itemtype="http://schema.stenci.la/CodeExpression"><code class="r"
              slot="text">round(ovl1_silent_percent, digits=1)</code><output slot="output"></output>
          </stencila-code-expression>% (<stencila-code-expression programming-language="r"
            itemscope="" itemtype="http://schema.stenci.la/CodeExpression"><code class="r"
              slot="text">ovl1_silent</code><output slot="output"></output>
          </stencila-code-expression>/<stencila-code-expression programming-language="r"
            itemscope="" itemtype="http://schema.stenci.la/CodeExpression"><code class="r"
              slot="text">total_common_silent</code><output slot="output"></output>
          </stencila-code-expression>) of the genes we identified as silent in serum lot one were
          common with the silent genes identified in the original study (<stencila-code-expression
            programming-language="r" itemscope="" itemtype="http://schema.stenci.la/CodeExpression">
            <code class="r" slot="text">round(ovl2_silent_percent, digits=1)</code><output
              slot="output"></output></stencila-code-expression>% (<stencila-code-expression
            programming-language="r" itemscope="" itemtype="http://schema.stenci.la/CodeExpression">
            <code class="r" slot="text">ovl2_silent</code><output slot="output"></output>
          </stencila-code-expression>/<stencila-code-expression programming-language="r"
            itemscope="" itemtype="http://schema.stenci.la/CodeExpression"><code class="r"
              slot="text">total_common_silent</code><output slot="output"></output>
          </stencila-code-expression>) for serum lot two).</p>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">To test whether active genes,
          as well as silent genes, increased expression during c-Myc induction we performed the
          confirmatory analysis as outlined in the Registered Report (Blum et al., 2015). This
          analysis differed from what was reported in the original study by analyzing the data as
          paired instead of unpaired. As suggested during peer review of the Registered Report, this
          is because expression of the same gene, analyzed across different conditions, is not
          independent (Blum et al., 2015). We performed a Wilcoxon signed-rank test on active genes
          comparing expression at 0 hr to 1 hr, 0 hr to 24 hr, and 1 hr to 24 hr, which were
          statistically significant for cells grown in both lots of serum (Table 1). The same
          comparisons were performed on silent genes, which were also statistically significant,
          with the exception of the silent gene comparison of 1 hr to 24 hr for serum lot one.
          Considering this was not the test reported in the original study, we conducted these
          paired analyses on the original data to provide a direct comparison. For both active and
          silent genes c-Myc induction resulted in statistically significant increases in
          expression, with the exception of the silent gene comparison from 0 hr to 1 hr (Table 1).
          This is in contrast to the results of the unpaired tests that were reported in the
          original study where active genes were reported to have a statistically significant
          increase in expression and silent genes were reported as not statistically significant for
          all comparisons. We conducted an exploratory unpaired analysis on the replication data for
          comparison, which resulted in statistically significant differences among the active gene
          comparisons as well as half of the silent gene comparisons (Table 2).</p>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">Importantly, though, the
          question of whether the change in expression among active genes is different than silent
          genes has not been tested. This would require a separate test on their difference (Gelman
          and Stern, 2006; Nieuwenhuis et al., 2011). To test whether active genes increased in
          expression during c-Myc induction more than silent genes, we performed an exploratory
          analysis on the difference in expression of active genes during c-Myc induction (e.g. from
          0 hr to 24 hr) compared to the difference in expression of silent genes over that same
          period (e.g. from 0 hr to 24 hr). For both the original and replication data, there was a
          statistically significant increase in expression of active genes compared to silent genes
          (Table 3). This suggests that active genes and silent genes do not have similar rates of
          expression upon c-Myc induction. To summarize, for this experiment we found results that
          were in the same direction as the original study and suggest that while both active and
          silent genes increased in expression upon c-Myc induction, the rate of increase was
          different.</p>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">The original study and this
          replication attempt used the same criteria to characterize a gene as silent or active, but
          there are many negative consequences of dichotomizing continuous variables, such as
          information loss, especially with a small gene set (Altman, 2006; Cohen, 1983). Papers
          published after the original study took an unbiased view by collecting comprehensive
          RNA-sequencing data to assess if the transcriptional effects of c-Myc were direct or
          indirect, concluding c-Myc activates and represses transcription of discrete gene sets,
          which in turn leads to induced RNA amplification (Sabò et al., 2014; Walz et al., 2014).
          Furthermore, Sabò and colleagues also used NanoString technology to quantify a subset of
          the differentially expressed genes identified by RNA-seq and observed similar results that
          revealed upward shifts in gene expression upon c-Myc induction (Sabò et al., 2014).
          However, instead of dichotomizing genes as active or silent, gene expression data was
          presented as continuous. Similarly, we presented the digital gene expression data
          generated during this replication attempt as continuous, which illustrates a general
          pattern of overall increased gene expression following c-Myc induction (Figure 2 - figure
          supplement 2). Importantly, though, these results are limited to the
          <stencila-code-expression programming-language="r" itemscope=""
            itemtype="http://schema.stenci.la/CodeExpression"><code class="r"
              slot="text">prettyNum(rep_n, big.mark=",")</code><output slot="output"></output>
          </stencila-code-expression> genes interrogated in this study and may or may not reflect
          how the entire transcriptome of P493-6 cells respond to c-Myc induction.</p>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph"><em itemscope=""
            itemtype="http://schema.stenci.la/Emphasis">Meta-analyses of original and replicated
            effects</em></p>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">We performed a meta-analysis
          using a random-effects model to combine each of the effects described above as
          pre-specified in the confirmatory analysis plan (Blum et al., 2015). To provide a
          standardized measure of the effect, a common effect size was calculated for each effect
          from the original and replication studies. Cohen’s <em itemscope=""
            itemtype="http://schema.stenci.la/Emphasis">d</em> is the standardized difference
          between two means using the pooled sample standard deviation. The effect size <em
            itemscope="" itemtype="http://schema.stenci.la/Emphasis">r</em> is a standardized
          measure of the strength and direction of the association between two variables, in this
          case time during c-Myc induction and gene expression. The estimate of the effect size of
          one study, as well as the associated uncertainty (i.e. confidence interval), compared to
          the effect size of the other study provides another approach to compare the original and
          replication results (Errington et al., 2014; Valentine et al., 2011). Importantly, the
          width of the confidence interval for each study is a reflection of not only the confidence
          level (e.g. 95%), but also variability of the sample (e.g. <em itemscope=""
            itemtype="http://schema.stenci.la/Emphasis">SD</em>) and sample size.</p>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">The comparison of total RNA
          levels at low levels of c-Myc (0hr) compared to high levels of c-Myc (24 hr) resulted in
          <em itemscope="" itemtype="http://schema.stenci.la/Emphasis">d</em> =
          <stencila-code-expression programming-language="r" itemscope=""
            itemtype="http://schema.stenci.la/CodeExpression"><code class="r"
              slot="text">round(exp_orig_d,2)</code><output slot="output"></output>
          </stencila-code-expression>, 95% CI [<stencila-code-expression programming-language="r"
            itemscope="" itemtype="http://schema.stenci.la/CodeExpression"><code class="r"
              slot="text">round(exp_orig_ci[[1]],2)</code><output slot="output"></output>
          </stencila-code-expression>, <stencila-code-expression programming-language="r"
            itemscope="" itemtype="http://schema.stenci.la/CodeExpression"><code class="r"
              slot="text">round(exp_orig_ci[[3]],2)</code><output slot="output"></output>
          </stencila-code-expression>] for the data reported in Figure 3E of the original study (Lin
          et al., 2012). This compares to <em itemscope=""
            itemtype="http://schema.stenci.la/Emphasis">d</em> = <stencila-code-expression
            programming-language="r" itemscope="" itemtype="http://schema.stenci.la/CodeExpression">
            <code class="r" slot="text">round(exp_lot1_d,2)</code><output slot="output"></output>
          </stencila-code-expression>, 95% CI [<stencila-code-expression programming-language="r"
            itemscope="" itemtype="http://schema.stenci.la/CodeExpression"><code class="r"
              slot="text">round(exp_lot1_ci[[1]],2)</code><output slot="output"></output>
          </stencila-code-expression>, <stencila-code-expression programming-language="r"
            itemscope="" itemtype="http://schema.stenci.la/CodeExpression"><code class="r"
              slot="text">round(exp_lot1_ci[[3]],2)</code><output slot="output"></output>
          </stencila-code-expression>] for serum lot one and <em itemscope=""
            itemtype="http://schema.stenci.la/Emphasis">d</em> = <stencila-code-expression
            programming-language="r" itemscope="" itemtype="http://schema.stenci.la/CodeExpression">
            <code class="r" slot="text">round(exp_lot2_d,2)</code><output slot="output"></output>
          </stencila-code-expression>, 95% CI [<stencila-code-expression programming-language="r"
            itemscope="" itemtype="http://schema.stenci.la/CodeExpression"><code class="r"
              slot="text">formatC(exp_lot2_ci[[1]],2,format="f")</code><output
              slot="output"></output></stencila-code-expression>, <stencila-code-expression
            programming-language="r" itemscope="" itemtype="http://schema.stenci.la/CodeExpression">
            <code class="r" slot="text">round(exp_lot2_ci[[3]],2)</code><output
              slot="output"></output></stencila-code-expression>] for serum lot two reported in this
          study. A meta-analysis (Figure 3A) of these effects resulted in <em itemscope=""
            itemtype="http://schema.stenci.la/Emphasis">d</em> = <stencila-code-expression
            programming-language="r" itemscope="" itemtype="http://schema.stenci.la/CodeExpression">
            <code class="r" slot="text">round(exp_meta$b[1],2)</code><output slot="output"></output>
          </stencila-code-expression>, 95% CI <a href="" itemscope=""
            itemtype="http://schema.stenci.la/Link">
            <stencila-code-expression programming-language="r" itemscope=""
              itemtype="http://schema.stenci.la/CodeExpression"><code class="r"
                slot="text">round(exp_meta$ci.lb,2)</code><output slot="output"></output>
            </stencila-code-expression>, <stencila-code-expression programming-language="r"
              itemscope="" itemtype="http://schema.stenci.la/CodeExpression"><code class="r"
                slot="text">round(exp_meta$ci.ub,2)</code><output slot="output"></output>
            </stencila-code-expression>
          </a>, which was statistically significant (<em itemscope=""
            itemtype="http://schema.stenci.la/Emphasis">p</em> = <stencila-code-expression
            programming-language="r" itemscope="" itemtype="http://schema.stenci.la/CodeExpression">
            <code class="r" slot="text">sub('^(-)?0[.]','\\1.',round(exp_meta$pval,4))</code><output
              slot="output"></output></stencila-code-expression>). The original and replication
          results are consistent when considering the direction of the effect, which suggests c-Myc
          induction increases total RNA levels in P493-6 Burkitt’s lymphoma cells. Noticeably, there
          was substantial within-study variation observed in this replication attempt, due the
          different serum lots tested. The point estimate of serum lot one was not within the
          confidence intervals of the original study and serum lot two, and vice versa; however the
          point estimate of the original study and serum lot two were within the confidence
          intervals of each other. </p>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">There were six comparisons of
          the gene expression data, three for active genes and three for silent genes (Figure 3B).
          These calculations were performed analyzing the data as paired, for reasons discussed
          above and as prespecified in the Registered Report (Blum et al., 2015). For active genes,
          expression at 0 hr to 1 hr, 0 hr to 24 hr, and 1 hr to 24 hr the meta-analyses were
          statistically significant (<em itemscope=""
            itemtype="http://schema.stenci.la/Emphasis">p</em> = <stencila-code-expression
            programming-language="r" itemscope="" itemtype="http://schema.stenci.la/CodeExpression">
            <code class="r" slot="text">scinot(a.meta.0v1$pval)$coeff</code><output
              slot="output"></output></stencila-code-expression>x10<sup itemscope=""
            itemtype="http://schema.stenci.la/Superscript">
            <stencila-code-expression programming-language="r" itemscope=""
              itemtype="http://schema.stenci.la/CodeExpression"><code class="r"
                slot="text">scinot(a.meta.0v1$pval)$exp</code><output slot="output"></output>
            </stencila-code-expression>
          </sup>, <em itemscope="" itemtype="http://schema.stenci.la/Emphasis">p</em> =
          <stencila-code-expression programming-language="r" itemscope=""
            itemtype="http://schema.stenci.la/CodeExpression"><code class="r"
              slot="text">scinot(a.meta.0v24$pval)$coeff</code><output slot="output"></output>
          </stencila-code-expression>x10<sup itemscope=""
            itemtype="http://schema.stenci.la/Superscript">
            <stencila-code-expression programming-language="r" itemscope=""
              itemtype="http://schema.stenci.la/CodeExpression"><code class="r"
                slot="text">scinot(a.meta.0v24$pval)$exp</code><output slot="output"></output>
            </stencila-code-expression>
          </sup>, <em itemscope="" itemtype="http://schema.stenci.la/Emphasis">p</em> =
          <stencila-code-expression programming-language="r" itemscope=""
            itemtype="http://schema.stenci.la/CodeExpression"><code class="r"
              slot="text">sub('^(-)?0[.]','\\1.',round(a.meta.1v24$pval,4))</code><output
              slot="output"></output></stencila-code-expression>, respectively). In all comparisons
          the results were consistent when considering the direction of the effect; however the
          effect size point estimate of each study (original, replication serum lot one, replication
          serum lot two) was not within the confidence interval of the other studies. Further, the
          large confidence intervals of the meta-analysis along with statistically significant
          Cochran’s <em itemscope="" itemtype="http://schema.stenci.la/Emphasis">Q</em> tests
          suggest heterogeneity between the original and replication studies. For silent genes, the
          meta-analysis was not statistically significant for gene expression at 0 hr to 1 hr and 1
          hr to 24 hr (<em itemscope="" itemtype="http://schema.stenci.la/Emphasis">p</em> =
          <stencila-code-expression programming-language="r" itemscope=""
            itemtype="http://schema.stenci.la/CodeExpression"><code class="r"
              slot="text">sub('^(-)?0[.]','\\1.',round(s.meta.0v1$pval,3))</code><output
              slot="output"></output></stencila-code-expression>, <em itemscope=""
            itemtype="http://schema.stenci.la/Emphasis">p</em> = <stencila-code-expression
            programming-language="r" itemscope="" itemtype="http://schema.stenci.la/CodeExpression">
            <code class="r"
              slot="text">sub('^(-)?0[.]','\\1.',round(s.meta.1v24$pval,4))</code><output
              slot="output"></output></stencila-code-expression>, respectively) and the effect size
          point estimate of each study was not within the confidence interval of the other studies.
          Similar to the active gene comparisons, the large confidence intervals of the
          meta-analysis along with statistically significant Cochran’s <em itemscope=""
            itemtype="http://schema.stenci.la/Emphasis">Q</em> tests suggest heterogeneity between
          the studies. Furthermore, for the 0 hr to 1 hr comparison the original study and
          replication studies were in opposite directions, while the 1 hr to 24 hr comparison was
          consistent. Finally, the comparison between 0 hr and 24 hr for silent genes was consistent
          when considering direction of the effect with a statistically significant meta-analysis
          (<em itemscope="" itemtype="http://schema.stenci.la/Emphasis">p</em> =
          <stencila-code-expression programming-language="r" itemscope=""
            itemtype="http://schema.stenci.la/CodeExpression"><code class="r"
              slot="text">scinot(s.meta.0v24$pval)$coeff</code><output slot="output"></output>
          </stencila-code-expression>x10<sup itemscope=""
            itemtype="http://schema.stenci.la/Superscript">
            <stencila-code-expression programming-language="r" itemscope=""
              itemtype="http://schema.stenci.la/CodeExpression"><code class="r"
                slot="text">scinot(s.meta.0v24$pval)$exp</code><output slot="output"></output>
            </stencila-code-expression>
          </sup>). The point estimate of the original study was not within the confidence intervals
          of the replication studies; however both replication studies with different serum lots
          were within the confidence intervals of the original study and each other. Overall, the
          gene expression analysis indicates that the effect sizes observed from the two serum lots
          tested in this replication attempt, although not identical, were more similar to each
          other than to the original study.</p>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">This direct replication
          provides an opportunity to understand the present evidence of these effects. Any known
          differences, including reagents and protocol differences, were identified prior to
          conducting the experimental work and described in the Registered Report (Blum et al.,
          2015). However, this is limited to what was obtainable from the original paper and through
          communication with the original authors, which means there might be particular features of
          the original experimental protocol that could be critical, but unidentified. So while some
          aspects, such as the cell line, induction time course, and the method used to measure gene
          expression were maintained, others were changed at the time of study design (Blum et al.,
          2015) that could affect results, such as the analytical approach (Silberzahn et al., 2017)
          and serum lot (Leek et al., 2010). Furthermore, other aspects were unknown or not easily
          controlled for. These include variables such as cell line genetic drift (Hughes et al.,
          2007; Kleensang et al., 2016) or changes in cellular volume that can impact overall
          transcript abundance (Padovan-Merhar et al., 2015). Whether these or other factors
          influence the outcomes of this study is open to hypothesizing and further investigation,
          which is facilitated by direct replications and transparent reporting.</p>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph"><em itemscope=""
            itemtype="http://schema.stenci.la/Emphasis">Materials and methods</em></p>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">As described in the Registered
          Report (Blum et al., 2015), we attempted a replication of the experiments reported in
          Figures 1B and 3E-F of Lin et al., 2012. A detailed description of all protocols can be
          found in the Registered Report (Blum et al., 2015). Additional detailed experimental
          notes, data, and analysis are available on the Open Science Framework (OSF)
          (RRID:SCR_003238) (<a href="https://osf.io/mokeb/" itemscope=""
            itemtype="http://schema.stenci.la/Link">https://osf.io/mokeb/</a>; Lewis et al., 2017).
          This includes the R Markdown file (<a href="https://osf.io/vdrsh/" itemscope=""
            itemtype="http://schema.stenci.la/Link">https://osf.io/vdrsh/</a>) that was used to
          compose this manuscript, which is a reproducible document linking the results in the
          article directly to the data and code that produced them (Hartgerink, 2017).</p>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph"><em itemscope=""
            itemtype="http://schema.stenci.la/Emphasis">Cell culture</em></p>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">P493-6 cells (shared by Young
          lab, Whitehead Institute for Biomedical Research, RRID: CVCL_6783) were maintained in
          RPMI-1640 supplemented with 1% Ala-Gln and 10% tetracycline-free FBS (Clontech, Mountain
          View, CA, cat# 631105, lot# 1: A15003, lot# 2: A15032). Cells were grown at 37°C in a
          humidified atmosphere at 5% CO<sub itemscope=""
            itemtype="http://schema.stenci.la/Subscript"><span
              data-itemtype="http://schema.org/Number">2</span></sub>. Quality control data for the
          cell line are available at <a href="https://osf.io/e6ftz/" itemscope=""
            itemtype="http://schema.stenci.la/Link">https://osf.io/e6ftz/</a>. This includes results
          confirming the cell line was free of mycoplasma contamination (DDC Medical, Fairfield,
          Ohio). Additionally, STR DNA profiling of the cell line was performed (DDC Medical,
          Fairfield, Ohio).</p>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">For repression of the
          conditional p<em itemscope="" itemtype="http://schema.stenci.la/Emphasis">myc</em>-tet
          construct in P493-6 cells, 0.1 µg/ml tetracycline (Sigma-Aldrich, St. Louis, MO, T7660)
          was added to the culture medium and cells were incubated for 72 hr. Under these
          conditions, P493-6 cells did not proliferate due to a dependency on the expression of <em
            itemscope="" itemtype="http://schema.stenci.la/Emphasis">MYC</em> (Schuhmacher et al.,
          1999). For <em itemscope="" itemtype="http://schema.stenci.la/Emphasis">MYC</em>
          re-induction, cells were washed three times with growth medium and grown in
          tetracycline-free culture conditions.</p>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph"><em itemscope=""
            itemtype="http://schema.stenci.la/Emphasis">Western blot</em></p>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">P493-6 cells were harvested at
          the indicated times and total cell lysates were prepared by pelleting ~1x10<sup
            itemscope="" itemtype="http://schema.stenci.la/Superscript"><span
              data-itemtype="http://schema.org/Number">7</span></sup> cells (determined with a
          C-chip disposable hemocytometer) at 4°C at 1,200 rpm for 5 min using a refrigerated
          centrifuge (Eppendorf, Westbury, NY, model# 5810R). After cell pellets were washed once
          with ice-cold 1X PBS, pellets were resuspended in RIPA lysis buffer containing 2X
          SIGMAFAST Protease inhibitors and 2X Phosphatase inhibitor cocktails 2 and 3. Protein
          concentrations were determined using the Bradford assay according to the manufacturer’s
          instructions. Sample buffer was added to protein lysates and 50 µg of protein along with
          protein ladder was resolved by SDS-PAGE and transferred to PVDF membrane as described in
          the Registered Report (Blum et al., 2015). The membrane was blocked with 5% w/v nonfat dry
          milk in 1X TBS with 0.2% Tween-20 (TBST). Membranes were probed with rabbit anti-c-Myc <a
            href="" itemscope="" itemtype="http://schema.stenci.la/Link">clone Y69</a> (Epitomics,
          Burlingame, CA, cat# 1472-1; RRID:AB_731658); 1:5,000 dilution in 5% w/v nonfat dry
          milk/TBST and mouse anti-ß-actin <a href="" itemscope=""
            itemtype="http://schema.stenci.la/Link">clone AC-15</a> (Sigma-Aldrich, cat# A5441;
          RRID:AB_476744); 1:10,000 dilution in 5% w/v nonfat dry milk/TBST. Each incubation was
          followed by washes with TBST and the appropriate secondary antibody: HRP-conjugated donkey
          anti-rabbit (Sigma-Aldrich, cat# GERPN2124); 1:10,000 dilution in 5% w/v nonfat dry
          milk/TBST or HRP-conjugated sheep anti-mouse (Sigma-Aldrich, cat# GERPN2124); 1:10,000
          dilution in 5% w/v nonfat dry milk/TBST. Membranes were washed with TBST and incubated
          with ECL Prime Chemiluminescent reagent (Sigma-Aldrich, cat# GERPN2232) according to the
          manufacturer’s instructions. Western blot images were acquired with G:BOX iChem XT and
          GeneSnap software (RRID:SCR_014249), version 7.12.02 (Syngene, Frederick, Maryland) and
          quantified using ImageJ software (RRID:SCR_003070), version 1.50i (Schneider et al.,
          2012). All images taken are available at <a href="https://osf.io/ujg7t/" itemscope=""
            itemtype="http://schema.stenci.la/Link">https://osf.io/ujg7t/</a>.</p>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph"><em itemscope=""
            itemtype="http://schema.stenci.la/Emphasis">RNA quantification</em></p>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">P493-6 cells were harvested at
          the indicated times and total RNA extraction was performed by pelleting ~1x10<sup
            itemscope="" itemtype="http://schema.stenci.la/Superscript"><span
              data-itemtype="http://schema.org/Number">7</span></sup> cells (exact number determined
          with a C-chip disposable hemocytometer) and homogenizing the sample in 1 ml Tri Reagent
          (Sigma-Aldrich, cat# T9424) according to the manufacturer’s instructions. For each sample
          10% v/v miRNA Homogenate Additive was added, vortexed, and incubated on ice for 10 min.
          For each 1 ml of Tri Reagent, 100 µl of bromochloropropane was added, vortexed for 15-30
          sec, incubated for 5 min at RT, then centrifuged at 12,000x<em itemscope=""
            itemtype="http://schema.stenci.la/Emphasis">g</em> for 10 min at 4°C. The aqueous phase
          was recovered and total RNA isolation was performed using the miRVana miRNA extraction kit
          (Ambion, Waltham, MA, cat# AM1561) according to the manufacturer’s instructions. Recovered
          RNA was eluated in 100 µl nuclease-free water. Total RNA concentrations and purity (data
          available at <a href="https://osf.io/jh5r4/" itemscope=""
            itemtype="http://schema.stenci.la/Link">https://osf.io/jh5r4/</a>) were measured using a
          NanoDrop ND-1000 (Thermo Fisher Scientific, Waltham, Massachusetts) with the NanoDrop
          Operating Software, version 3.3, and converted to ng per 1,000 cells.</p>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph"><em itemscope=""
            itemtype="http://schema.stenci.la/Emphasis">RNA extraction and NanoString nCounter
            digital gene expression assay</em></p>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">P493-6 cells were harvested at
          the indicated times and 1x10<sup itemscope=""
            itemtype="http://schema.stenci.la/Superscript"><span
              data-itemtype="http://schema.org/Number">6</span></sup> cells were collected (number
          determined with a C-chip disposable hemocytometer) and lysed directly in 100 µl Buffer RLT
          (Qiagen, Hilden, Germany, cat# 79216) supplemented with ß-mercaptoethanol to yield a
          concentration of 10,000 cells per µl. This was performed four independent times. Multiple
          4 µl aliquots were stored and shipped at -80°C with temperature monitored during shipping
          to avoid freeze/thaw cycles. Lysates were processed according to the Cell Lysate Protocol
          (nCounter Gene Expression Assay Manual, NanoString Technologies, Seattle, Washington)
          according to the manufacturer’s instructions and as described in the Registered Report
          (Blum et al., 2015). Three nCounter Reporter CodeSets (nCounter GX Human Immunology Kit,
          nCounter GX Human Kinase Kit, nCounter Custom CodeSet) encompassing
          <stencila-code-expression programming-language="r" itemscope=""
            itemtype="http://schema.stenci.la/CodeExpression"><code class="r"
              slot="text">prettyNum(length(unique(comb.means$Accession)),
              big.mark=",")</code><output slot="output"></output></stencila-code-expression> genes
          across multiple functional categories were used. Following hybridization, samples were
          immediately processed with the nCounter Analysis System (NanoString Technologies,
          NCT-PREP-120). The count data was collected using the nCounter RCC Collector Worksheet
          (NanoString Technologies), version 1.6.0 and then positive-, negative-, and housekeeping
          gene-normalized per nCounter guidelines. Expression for each gene was averaged across the
          4 independent replicate samples. Additionally, for genes that appeared on multiple
          CodeSets, expression values were averaged together to generate a single value for each
          gene. A gene was defined as transcriptionally active if its average expression was above 1
          transcript/cell at 0 hr and transcriptionally silent if below 0.5 transcript/cell. A list
          of all Reporter CodeSets and their expression values (transcripts/cell) are available at
          Figure 2 - source data 1. Additional files and analysis scripts are available at <a
            href="https://osf.io/fn2y4/" itemscope=""
            itemtype="http://schema.stenci.la/Link">https://osf.io/fn2y4/</a>.</p>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph"><em itemscope=""
            itemtype="http://schema.stenci.la/Emphasis">Statistical analysis</em></p>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">Statistical analysis was
          performed with R software (RRID:SCR<em itemscope=""
            itemtype="http://schema.stenci.la/Emphasis">001905), version 3.3.2 (R Core Team, 2017).
            All data, csv files, and analysis scripts are available on the OSF (<a
              href="https://osf.io/mokeb/" itemscope=""
              itemtype="http://schema.stenci.la/Link">https://osf.io/mokeb/</a>). Confirmatory
            statistical analysis was pre-registered (<a href="https://osf.io/nj8wb/" itemscope=""
              itemtype="http://schema.stenci.la/Link">https://osf.io/nj8wb/</a>) before the
            experimental work began as outlined in the Registered Report (Blum et al., 2015).
            Proposed analysis of gene expression data was conducted by the Wilcoxon signed-rank test
            using the method proposed by Pratt to handle zero differences (Pratt, 1959), with
            additional exploratory analysis performed using the Wilcoxon rank sum test as reported
            in the original study and a Wilcoxon rank sum test on the difference in expression of
            active genes during c-Myc induction (e.g. from 0 hr to 24 hr) compared to the difference
            in expression of silent genes over that same period (e.g. from 0 hr to 24 hr). Data were
            checked to ensure assumptions of statistical tests were met. When described in the
            results, the Bonferroni correction, to account for multiple testings, was applied to the
            alpha error by dividing the uncorrected value (.05) by the number of tests performed.
            Although the Bonferroni method is conservative, it was accounted for in the power
            calculations to ensure sample size was sufficient. In cases where the number of groups
            were 3 and the sample sizes were evenly distributed among the groups, Fisher&#39;s LSD
            test was performed resulting in an _a priori</em> significance threshold of .05. A
          meta-analysis of a common original and replication effect size was performed with a random
          effects model and the <em itemscope=""
            itemtype="http://schema.stenci.la/Emphasis">metafor</em> package (Viechtbauer, 2010)
          (available at: <a href="https://osf.io/5yscz/" itemscope=""
            itemtype="http://schema.stenci.la/Link">https://osf.io/5yscz/</a>). The sample sizes
          reported in Table 1 and Figure 3 for the gene analysis comparisons is based on the sample
          size used in the Wilcoxon signed-rank test, which removes samples with zero differences
          after ranking (Pratt, 1959). The raw original study data were shared by the original
          authors with the summary data published in the Registered Report (Blum et al., 2015) and
          was used in the power calculations to determine the sample size for this study.</p>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph"><em itemscope=""
            itemtype="http://schema.stenci.la/Emphasis">Deviations from Registered Report</em></p>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">The number of flasks, and thus
          cells, was increased when tetracycline was added to P493-6 cells to account for the cells
          not proliferating during this period (i.e. there were two Flask B’s as described in the
          Registered Report, which were pooled prior to seeding). The proposed statistical analysis
          for the western blot analysis (Protocol 1) described in the Registered Report was not
          performed since the levels of normalized c-Myc at time 0 hr was at the limit of detection.
          The number of genes analyzed in the original study, and thus listed in the Registered
          Report, was reported incorrectly as 1,388 instead of <stencila-code-expression
            programming-language="r" itemscope="" itemtype="http://schema.stenci.la/CodeExpression">
            <code class="r" slot="text">prettyNum(length(unique(o.comb.means$Accession)),
              big.mark=",")</code><output slot="output"></output></stencila-code-expression> (data
          shared by original authors). NanoString analysis was conducted using the nCounter RCC
          Collector Worksheet instead of nSolver Analysis software. Additionally, the statistical
          tests reported in Figure 3F of the original study incorrectly described the comparisons as
          between 0 hr and 1 hr instead of between 0 hr and 24 hr (scripts shared by original
          authors). The corrected values are described above for comparisons and used in the
          meta-analysis. Additional materials and instrumentation not listed in the Registered
          Report, but needed during experimentation are also listed.</p>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph"><em itemscope=""
            itemtype="http://schema.stenci.la/Emphasis">Acknowledgements</em></p>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">The Reproducibility Project:
          Cancer Biology would like to thank the original authors, particular Charles Lin (Baylor
          College of Medicine) for sharing critical reagents and data, specifically the P493-6
          cells. We would also like to thank Courtney Soderberg at the Center for Open Science for
          assistance with statistical analyses and the following companies for generously donating
          reagents to the Reproducibility Project: Cancer Biology; American Type and Tissue
          Collection (ATCC), Applied Biological Materials, BioLegend, Charles River Laboratories,
          Corning Incorporated, DDC Medical, EMD Millipore, Harlan Laboratories, LI-COR Biosciences,
          Mirus Bio, Novus Biologicals, Sigma-Aldrich, and System Biosciences (SBI).</p>
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        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph"><strong itemscope=""
            itemtype="http://schema.stenci.la/Strong">Figure Legends</strong></p>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph"><strong itemscope=""
            itemtype="http://schema.stenci.la/Strong">Figure 1. Induction of c-Myc in P493-6 cells
            and impact on total RNA levels.</strong></p>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">P493-6 cells were grown in the
          presence of tetracycline (Tet) for 72 hr and switched into Tet-free growth medium to
          induce c-Myc expression. Cells were cultured in two separate lots of serum. (<strong
            itemscope="" itemtype="http://schema.stenci.la/Strong">A</strong>) Representative
          Western blot using an anti-c-Myc antibody (top panels) or an anti-ß-Actin antibody (bottom
          panel). Two exposures of the anti-c-Myc antibody are presented to facilitate detection of
          c-Myc. (<strong itemscope="" itemtype="http://schema.stenci.la/Strong">B</strong>)
          Quantification of total RNA levels (ng of total RNA per 1,000 cells) for cells at 0, 1,
          and 24 hr after release from Tet. Means reported and error bars represent s.e.m. from
          <stencila-code-expression programming-language="r" itemscope=""
            itemtype="http://schema.stenci.la/CodeExpression"><code class="r"
              slot="text">length(subset(data2, Lot==1 &amp; Time==0)$value)</code><output
              slot="output"></output></stencila-code-expression> independent biological repeats. For
          serum lot one, one-way ANOVA on total RNA levels of all groups; <em itemscope=""
            itemtype="http://schema.stenci.la/Emphasis">F</em>(<stencila-code-expression
            programming-language="r" itemscope="" itemtype="http://schema.stenci.la/CodeExpression">
            <code class="r" slot="text">summary(fit1)[[1]][["Df"]][1]</code><output
              slot="output"></output></stencila-code-expression>, <stencila-code-expression
            programming-language="r" itemscope="" itemtype="http://schema.stenci.la/CodeExpression">
            <code class="r" slot="text">summary(fit1)[[1]][["Df"]][2]</code><output
              slot="output"></output></stencila-code-expression>) = <stencila-code-expression
            programming-language="r" itemscope="" itemtype="http://schema.stenci.la/CodeExpression">
            <code class="r" slot="text">round(summary(fit1)[[1]][["F
              value"]][1],digits=2)</code><output slot="output"></output></stencila-code-expression>
          , <em itemscope="" itemtype="http://schema.stenci.la/Emphasis">p</em> =
          <stencila-code-expression programming-language="r" itemscope=""
            itemtype="http://schema.stenci.la/CodeExpression"><code class="r"
              slot="text">sub('^(-)?0[.]','\\1.', round(summary(fit1)[[1]][["Pr(&gt;F)"]][1], digits
              = 3))</code><output slot="output"></output></stencila-code-expression>. Planned
          contrast between 0 hr and 24 hr; <em itemscope=""
            itemtype="http://schema.stenci.la/Emphasis">t</em>(<stencila-code-expression
            programming-language="r" itemscope="" itemtype="http://schema.stenci.la/CodeExpression">
            <code class="r" slot="text">contrast1$df</code><output slot="output"></output>
          </stencila-code-expression>) = <stencila-code-expression programming-language="r"
            itemscope="" itemtype="http://schema.stenci.la/CodeExpression"><code class="r"
              slot="text">round(contrast1$t.ratio,2)</code><output slot="output"></output>
          </stencila-code-expression>, <em itemscope=""
            itemtype="http://schema.stenci.la/Emphasis">p</em> = <stencila-code-expression
            programming-language="r" itemscope="" itemtype="http://schema.stenci.la/CodeExpression">
            <code class="r"
              slot="text">sub('^(-)?0[.]','\\1.',round(contrast1$p.value,3))</code><output
              slot="output"></output></stencila-code-expression> with <em itemscope=""
            itemtype="http://schema.stenci.la/Emphasis">a priori</em> alpha level = .05. For serum
          lot two, one-way ANOVA on total RNA levels of all groups; <em itemscope=""
            itemtype="http://schema.stenci.la/Emphasis">F</em>(<stencila-code-expression
            programming-language="r" itemscope="" itemtype="http://schema.stenci.la/CodeExpression">
            <code class="r" slot="text">summary(fit2)[[1]][["Df"]][1]</code><output
              slot="output"></output></stencila-code-expression>, <stencila-code-expression
            programming-language="r" itemscope="" itemtype="http://schema.stenci.la/CodeExpression">
            <code class="r" slot="text">summary(fit2)[[1]][["Df"]][2]</code><output
              slot="output"></output></stencila-code-expression>) = <stencila-code-expression
            programming-language="r" itemscope="" itemtype="http://schema.stenci.la/CodeExpression">
            <code class="r" slot="text">round(summary(fit2)[[1]][["F
              value"]][1],digits=2)</code><output slot="output"></output></stencila-code-expression>
          , <em itemscope="" itemtype="http://schema.stenci.la/Emphasis">p</em> =
          <stencila-code-expression programming-language="r" itemscope=""
            itemtype="http://schema.stenci.la/CodeExpression"><code class="r"
              slot="text">sub('^(-)?0[.]','\\1.', round(summary(fit2)[[1]][["Pr(&gt;F)"]][1], digits
              = 5))</code><output slot="output"></output></stencila-code-expression>. Planned
          contrast between 0 hr and 24 hr; <em itemscope=""
            itemtype="http://schema.stenci.la/Emphasis">t</em>(<stencila-code-expression
            programming-language="r" itemscope="" itemtype="http://schema.stenci.la/CodeExpression">
            <code class="r" slot="text">contrast2$df</code><output slot="output"></output>
          </stencila-code-expression>) = <stencila-code-expression programming-language="r"
            itemscope="" itemtype="http://schema.stenci.la/CodeExpression"><code class="r"
              slot="text">round(contrast2$t.ratio,2)</code><output slot="output"></output>
          </stencila-code-expression>, <em itemscope=""
            itemtype="http://schema.stenci.la/Emphasis">p</em> = <stencila-code-expression
            programming-language="r" itemscope="" itemtype="http://schema.stenci.la/CodeExpression">
            <code class="r"
              slot="text">sub('^(-)?0[.]','\\1.',round(contrast2$p.value,4))</code><output
              slot="output"></output></stencila-code-expression> with <em itemscope=""
            itemtype="http://schema.stenci.la/Emphasis">a priori</em> alpha level = .05. Additional
          details for this experiment can be found at <a href="https://osf.io/tfd57/" itemscope=""
            itemtype="http://schema.stenci.la/Link">https://osf.io/tfd57/</a>.</p>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph"><strong itemscope=""
            itemtype="http://schema.stenci.la/Strong">Figure 2. Digital gene expression
            analysis.</strong></p>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">P493-6 cells grown in the
          presence of tetracycline (Tet) for 72 hr for repression of the conditional p<em
            itemscope="" itemtype="http://schema.stenci.la/Emphasis">myc</em>-tet construct, were
          switched into Tet-free growth medium to induce c-Myc expression. Cells were cultured in
          two separate lots of serum. Transcripts/cell estimates from NanoString nCounter gene
          expression assays (<stencila-code-expression programming-language="r" itemscope=""
            itemtype="http://schema.stenci.la/CodeExpression"><code class="r"
              slot="text">prettyNum(length(unique(comb.means$Accession)),
              big.mark=",")</code><output slot="output"></output></stencila-code-expression> genes
          assay) for active (left) and silent (right) genes at 0, 1, and 24 hr after release from
          Tet. Active genes expressed greater than 1 transcript/cell. Silent genes expressed less
          than 0.5 transcript/cell. Box and whisker plots with median represented as the line
          through the box and whiskers representing values within 1.5 IQR of the first and third
          quartile. Cells grown in serum lot one: active genes = <stencila-code-expression
            programming-language="r" itemscope="" itemtype="http://schema.stenci.la/CodeExpression">
            <code class="r" slot="text">length(active_0hr_l1)</code><output slot="output"></output>
          </stencila-code-expression>, silent genes = <stencila-code-expression
            programming-language="r" itemscope="" itemtype="http://schema.stenci.la/CodeExpression">
            <code class="r" slot="text">length(silent_0hr_l1)</code><output slot="output"></output>
          </stencila-code-expression>. Cells grown in serum lot two: active genes =
          <stencila-code-expression programming-language="r" itemscope=""
            itemtype="http://schema.stenci.la/CodeExpression"><code class="r"
              slot="text">length(active_0hr_l2)</code><output slot="output"></output>
          </stencila-code-expression>, silent genes = <stencila-code-expression
            programming-language="r" itemscope="" itemtype="http://schema.stenci.la/CodeExpression">
            <code class="r" slot="text">length(silent_0hr_l2)</code><output slot="output"></output>
          </stencila-code-expression>. Confirmatory analysis is reported in Table 1 and exploratory
          statistical analysis is reported in Table 2 and Table 3. Additional details for this
          experiment can be found at <a href="https://osf.io/fn2y4/" itemscope=""
            itemtype="http://schema.stenci.la/Link">https://osf.io/fn2y4/</a>.</p>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph"><strong itemscope=""
            itemtype="http://schema.stenci.la/Strong">Figure 2 - figure supplement 1. Logarithmic
            expression of genes.</strong></p>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">This is the same experiment as
          in Figure 2. (<strong itemscope=""
            itemtype="http://schema.stenci.la/Strong">A</strong>-<strong itemscope=""
            itemtype="http://schema.stenci.la/Strong">B</strong>, <strong itemscope=""
            itemtype="http://schema.stenci.la/Strong">E</strong>-<strong itemscope=""
            itemtype="http://schema.stenci.la/Strong">F</strong>) Gene expression data plotted on a
          log2 transformed scale for active (<strong itemscope=""
            itemtype="http://schema.stenci.la/Strong">A</strong>, <strong itemscope=""
            itemtype="http://schema.stenci.la/Strong">E</strong>) and silent (<strong itemscope=""
            itemtype="http://schema.stenci.la/Strong">B</strong>, <strong itemscope=""
            itemtype="http://schema.stenci.la/Strong">F</strong>) genes at 0, 1, and 24 hr after
          release from Tet for both lots of serum. (<strong itemscope=""
            itemtype="http://schema.stenci.la/Strong">C</strong>-<strong itemscope=""
            itemtype="http://schema.stenci.la/Strong">D</strong>, <strong itemscope=""
            itemtype="http://schema.stenci.la/Strong">G</strong>-<strong itemscope=""
            itemtype="http://schema.stenci.la/Strong">H</strong>) Box and whisker plots showing gene
          expression changes (log2 ratio) between the indicated times for active (<strong
            itemscope="" itemtype="http://schema.stenci.la/Strong">C</strong>, <strong itemscope=""
            itemtype="http://schema.stenci.la/Strong">G</strong>) and silent (<strong itemscope=""
            itemtype="http://schema.stenci.la/Strong">D</strong>, <strong itemscope=""
            itemtype="http://schema.stenci.la/Strong">H</strong>) genes. Median represented as the
          line through the box and whiskers representing values within 1.5 IQR of the first and
          third quartile. Additional details for this experiment can be found at <a
            href="https://osf.io/fn2y4/" itemscope=""
            itemtype="http://schema.stenci.la/Link">https://osf.io/fn2y4/</a>.</p>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph"><strong itemscope=""
            itemtype="http://schema.stenci.la/Strong">Figure 2 - figure supplement 2. Comparison of
            gene expression data as continuous.</strong></p>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">This is the same experiment as
          in Figure 2. (<strong itemscope=""
            itemtype="http://schema.stenci.la/Strong">A</strong>-<strong itemscope=""
            itemtype="http://schema.stenci.la/Strong">C</strong>, <strong itemscope=""
            itemtype="http://schema.stenci.la/Strong">E</strong>-<strong itemscope=""
            itemtype="http://schema.stenci.la/Strong">G</strong>) Scatter plots of log2 transformed
          gene expression data for all genes analyzed at the indicated times on the y and x axes for
          both lots of serum. Active genes are blue, silent genes are red, and genes that are
          neither active or silent (expression was more than 0.5 transcript/cell and less than 1
          transcript/cell at time 0 hr) are white. (<strong itemscope=""
            itemtype="http://schema.stenci.la/Strong">D</strong>, <strong itemscope=""
            itemtype="http://schema.stenci.la/Strong">H</strong>) Box and whisker plots showing gene
          expression changes (log2 ratio) between the indicated times for all genes analyzed for
          both lots of serum. Median represented as the line through the box and whiskers
          representing values within 1.5 IQR of the first and third quartile. Additional details for
          this experiment can be found at <a href="https://osf.io/fn2y4/" itemscope=""
            itemtype="http://schema.stenci.la/Link">https://osf.io/fn2y4/</a>.</p>
        <figure itemscope="" itemtype="http://schema.stenci.la/Figure" title="Table"><label
            data-itemprop="label">Table</label>
          <stencila-code-chunk itemscope="" itemtype="http://schema.stenci.la/CodeChunk"
            data-include="FALSE" data-programminglanguage="r">
            <pre class="language-r" itemscope="" itemtype="http://schema.stenci.la/CodeBlock"
              slot="text"><code>table1_active &lt;- data.frame(dat[c(1:5)]) #subsets on active genes
table1_active &lt;- melt(table1_active,id.vars = c(&quot;Study&quot;,&quot;Label&quot;)) #melts on Study and Label Variables
table1_active$interaction &lt;- interaction(table1_active$Study,table1_active$variable) 
table1_active &lt;- reshape(table1_active, idvar=&quot;interaction&quot;, timevar = &quot;Label&quot;,direction=&quot;wide&quot;)
table1_active &lt;- table1_active[,c(2:4,7,10)]

table1_silent &lt;- data.frame(dat[c(1:2,6:8)]) #subsets on silent genes
table1_silent &lt;- melt(table1_silent,id.vars = c(&quot;Study&quot;,&quot;Label&quot;)) #melts on Study and Label Variables
table1_silent$interaction &lt;- interaction(table1_silent$Study,table1_silent$variable)
table1_silent &lt;- reshape(table1_silent, idvar=&quot;interaction&quot;, timevar = &quot;Label&quot;,direction=&quot;wide&quot;)
table1_silent &lt;- table1_silent[,c(2:4,7,10)]

table1 &lt;- rbind(table1_active,table1_silent) #combines silent and active into one data frame

#changes column names
colnames(table1) &lt;- c(&quot;Study&quot;,&quot;Comparison&quot;,&quot;Z value&quot;,&quot;p value&quot;,&quot;sample size (n)&quot;)
#creates comparison column/ renames comparisons
table1$Comparison &lt;- rep(c(rep(&quot;0hr vs 1hr&quot;,3),rep(&quot;0hr vs 24hr&quot;,3),rep(&quot;1hr vs 24hr&quot;,3)),2)
rownames(table1) &lt;- NULL #deletes row names
table1$Study &lt;- as.character(table1$Study) #Makes &#39;study&#39; variable as character 
table1[c(2:3,5:6,8:9,11:12,14:15,17:18),2] &lt;- c(&quot;&quot;,&quot;&quot;)
#label active and silent categories
table1$Genes &lt;- c(c(&quot;Active&quot;,rep(c(&quot;&quot;),8)),c(&quot;Silent&quot;,rep(c(&quot;&quot;),8)))
table1 &lt;- table1[,c(6,2,1,3:5)]
</code></pre>
          </stencila-code-chunk>
          <figcaption>
            <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">1. Confirmatory statistical
              tests.</p>
          </figcaption>
        </figure>
        <stencila-code-chunk itemscope="" itemtype="http://schema.stenci.la/CodeChunk" data-echo="F"
          data-programminglanguage="r">
          <pre class="language-r" itemscope="" itemtype="http://schema.stenci.la/CodeBlock"
            slot="text"><code>library(pander)
pander(table1)</code></pre>
        </stencila-code-chunk>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">These confirmatory statistical
          tests relate to the data presented in Figure 2. Wilcoxon signed-rank test, which treat the
          data as paired, were conducted for the original study (Lin et al., 2012) and this
          replication attempt (RP:CB). Uncorrected <em itemscope=""
            itemtype="http://schema.stenci.la/Emphasis">p</em> values are reported with an <em
            itemscope="" itemtype="http://schema.stenci.la/Emphasis">a priori</em> significance
          threshold of <stencila-code-expression programming-language="r" itemscope=""
            itemtype="http://schema.stenci.la/CodeExpression"><code class="r"
              slot="text">sub('^(-)?0[.]','\\1.',round(0.05/3, digits = 4))</code><output
              slot="output"></output></stencila-code-expression>. Sample sizes reported are based on
          the sample size used in the tests. Additional details for this experiment can be found at
          <a href="https://osf.io/fn2y4/" itemscope=""
            itemtype="http://schema.stenci.la/Link">https://osf.io/fn2y4/</a>.</p>
        <figure itemscope="" itemtype="http://schema.stenci.la/Figure" title="Table"><label
            data-itemprop="label">Table</label>
          <stencila-code-chunk itemscope="" itemtype="http://schema.stenci.la/CodeChunk"
            data-include="FALSE" data-programminglanguage="r">
            <pre class="language-r" itemscope="" itemtype="http://schema.stenci.la/CodeBlock"
              slot="text"><code>#Subsets on only Wilcoxon Rank-Sum Tests
WilcoxonRS &lt;- dat[c(1,9:12)]
table2_active &lt;- melt(WilcoxonRS,id.vars = c(&quot;Study&quot;,&quot;Label.1&quot;)) #melts on Study and Label Variables
table2_active$interaction &lt;- interaction(table2_active$Study,table2_active$variable) 
table2_active &lt;- reshape(table2_active, idvar=&quot;interaction&quot;, timevar = &quot;Label.1&quot;,direction=&quot;wide&quot;)
table2_active &lt;- table2_active[,c(2:4,7,10)]

table2_silent &lt;- data.frame(dat[c(1,9,13:15)]) #subsets on silent genes
table2_silent &lt;- melt(table2_silent,id.vars = c(&quot;Study&quot;,&quot;Label.1&quot;)) #melts on Study and Label Variables
table2_silent$interaction &lt;- interaction(table2_silent$Study,table2_silent$variable)
table2_silent &lt;- reshape(table2_silent, idvar=&quot;interaction&quot;, timevar = &quot;Label.1&quot;,direction=&quot;wide&quot;)
table2_silent &lt;- table2_silent[,c(2:4,7,10)]

table2 &lt;- rbind(table2_active,table2_silent) #combines silent and active into one data frame

#changes column names
colnames(table2) &lt;- c(&quot;Study&quot;,&quot;Comparison&quot;,&quot;W value&quot;,&quot;p value&quot;,&quot;sample size (n)&quot;)
#creates comparison column/ renames comparisons
table2$Comparison &lt;- rep(c(rep(&quot;0hr vs 1hr&quot;,3),rep(&quot;0hr vs 24hr&quot;,3),rep(&quot;1hr vs 24hr&quot;,3)),2)
rownames(table2) &lt;- NULL #deletes row names
table2$Study &lt;- as.character(table2$Study) #Makes &#39;study&#39; variable as character 
table2[c(2:3,5:6,8:9,11:12,14:15,17:18),2] &lt;- c(&quot;&quot;,&quot;&quot;)
#label active and silent categories
table2$Genes &lt;- c(c(&quot;Active&quot;,rep(c(&quot;&quot;),8)),c(&quot;Silent&quot;,rep(c(&quot;&quot;),8)))
table2 &lt;- table2[,c(6,2,1,3:5)]
</code></pre>
          </stencila-code-chunk>
          <figcaption>
            <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">2. Exploratory statistical
              tests.</p>
          </figcaption>
        </figure>
        <stencila-code-chunk itemscope="" itemtype="http://schema.stenci.la/CodeChunk" data-echo="F"
          data-programminglanguage="r">
          <pre class="language-r" itemscope="" itemtype="http://schema.stenci.la/CodeBlock"
            slot="text"><code>library(pander)
pander(table2)</code></pre>
        </stencila-code-chunk>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">These exploratory statistical
          tests relate to the data presented in Figure 2. Wilcoxon rank sum tests, which treat the
          data as unpaired, were conducted for the original study (Lin et al., 2012) and this
          replication attempt (RP:CB). Uncorrected <em itemscope=""
            itemtype="http://schema.stenci.la/Emphasis">p</em> values are reported. Sample sizes
          reported are based on treating genes as unpaired between conditions. Additional details
          for this experiment can be found at <a href="https://osf.io/fn2y4/" itemscope=""
            itemtype="http://schema.stenci.la/Link">https://osf.io/fn2y4/</a>.</p>
        <figure itemscope="" itemtype="http://schema.stenci.la/Figure" title="Table"><label
            data-itemprop="label">Table</label>
          <stencila-code-chunk itemscope="" itemtype="http://schema.stenci.la/CodeChunk"
            data-include="FALSE" data-programminglanguage="r">
            <pre class="language-r" itemscope="" itemtype="http://schema.stenci.la/CodeBlock"
              slot="text"><code>diff &lt;- dat[c(1,16:19)]

# only needed if first column consists of numbers
diff[[1]] &lt;- as.character(diff[[1]])
diff[2,3:5] &lt;- as.character(diff[2,3:5])

table3 &lt;- melt(diff,id.vars = c(&quot;Study&quot;,&quot;Label.2&quot;)) #melts on Study and Label Variables
table3$interaction &lt;- interaction(table3$Study,table3$variable) 
table3 &lt;- reshape(table3, idvar=&quot;interaction&quot;, timevar = &quot;Label.2&quot;,direction=&quot;wide&quot;)
table3 &lt;- table3[,c(2:4,7,10)]

#changes column names
colnames(table3) &lt;- c(&quot;Study&quot;,&quot;Comparison&quot;,&quot;W value&quot;,&quot;p value&quot;,&quot;sample size (n)&quot;)
#creates comparison column/ renames comparisons
table3$Comparison &lt;- rep(c(rep(&quot;0hr vs 1hr&quot;,3),rep(&quot;0hr vs 24hr&quot;,3),rep(&quot;1hr vs 24hr&quot;,3)))
rownames(table3) &lt;- NULL #deletes row names
table3$Study &lt;- as.character(table3$Study) #Makes &#39;study&#39; variable as character 
table3[c(2:3,5:6,8:9),2] &lt;- c(&quot;&quot;,&quot;&quot;)
table3 &lt;- table3[,c(2,1,3:5)]
</code></pre>
          </stencila-code-chunk>
          <figcaption>
            <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">3. Exploratory statistical
              tests.</p>
          </figcaption>
        </figure>
        <stencila-code-chunk itemscope="" itemtype="http://schema.stenci.la/CodeChunk" data-echo="F"
          data-programminglanguage="r">
          <pre class="language-r" itemscope="" itemtype="http://schema.stenci.la/CodeBlock"
            slot="text"><code>pander(table3)</code></pre>
        </stencila-code-chunk>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">These exploratory statistical
          tests relate to the data presented in Figure 2. Wilcoxon rank sum tests were conducted for
          the original study (Lin et al., 2012) and this replication attempt (RP:CB) on the
          difference in expression of active genes during c-Myc induction (e.g. from 0 hr to 24 hr)
          compared to the difference in expression of silent genes over that same period (e.g. from
          0 hr to 24 hr). Uncorrected <em itemscope=""
            itemtype="http://schema.stenci.la/Emphasis">p</em> values are reported. Sample sizes
          reported are based on number of active and silent genes used in the tests. Additional
          details for this experiment can be found at <a href="https://osf.io/fn2y4/" itemscope=""
            itemtype="http://schema.stenci.la/Link">https://osf.io/fn2y4/</a>.</p>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph"><strong itemscope=""
            itemtype="http://schema.stenci.la/Strong">Figure 3. Meta-analyses of each
            effect.</strong></p>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">Effect size and 95% confidence
          interval are presented for Lin et al., 2012, this replication study (RP:CB), and a random
          effects meta-analysis of those two effects. Cohen’s <em itemscope=""
            itemtype="http://schema.stenci.la/Emphasis">d</em> is the standardized difference
          between the two measurements, with a larger positive value indicating total RNA levels are
          increased at 24 hr compared to 0 hr. The effect size <em itemscope=""
            itemtype="http://schema.stenci.la/Emphasis">r</em> is a standardized measure of the
          correlation (strength and direction) of the association between gene expression and c-Myc
          induction, with a larger positive value indicating gene expression increased during the
          course of c-Myc induction. Sample sizes used in Lin et al., 2012 and this replication
          attempt are reported under the study name. (<strong itemscope=""
            itemtype="http://schema.stenci.la/Strong">A</strong>) Total RNA levels in P493-6 cells 0
          hr compared to 24 hr after release from tetracycline (meta-analysis <em itemscope=""
            itemtype="http://schema.stenci.la/Emphasis">p</em> = <stencila-code-expression
            programming-language="r" itemscope="" itemtype="http://schema.stenci.la/CodeExpression">
            <code class="r" slot="text">sub('^(-)?0[.]','\\1.',round(exp_meta$pval,4))</code><output
              slot="output"></output></stencila-code-expression>). (<strong itemscope=""
            itemtype="http://schema.stenci.la/Strong">B</strong>) Gene expression of active or
          silent genes are shown for all comparisons. Active genes: 0 hr compared to 1 hr
          (meta-analysis <em itemscope="" itemtype="http://schema.stenci.la/Emphasis">p</em> =
          <stencila-code-expression programming-language="r" itemscope=""
            itemtype="http://schema.stenci.la/CodeExpression"><code class="r"
              slot="text">scinot(a.meta.0v1$pval)$coeff</code><output slot="output"></output>
          </stencila-code-expression>x10<sup itemscope=""
            itemtype="http://schema.stenci.la/Superscript">
            <stencila-code-expression programming-language="r" itemscope=""
              itemtype="http://schema.stenci.la/CodeExpression"><code class="r"
                slot="text">scinot(a.meta.0v1$pval)$exp</code><output slot="output"></output>
            </stencila-code-expression>
          </sup>), 0 hr compared to 24 hr (meta-analysis <em itemscope=""
            itemtype="http://schema.stenci.la/Emphasis">p</em> = <stencila-code-expression
            programming-language="r" itemscope="" itemtype="http://schema.stenci.la/CodeExpression">
            <code class="r" slot="text">scinot(a.meta.0v24$pval)$coeff</code><output
              slot="output"></output></stencila-code-expression>x10<sup itemscope=""
            itemtype="http://schema.stenci.la/Superscript">
            <stencila-code-expression programming-language="r" itemscope=""
              itemtype="http://schema.stenci.la/CodeExpression"><code class="r"
                slot="text">scinot(a.meta.0v24$pval)$exp</code><output slot="output"></output>
            </stencila-code-expression>
          </sup>), 1 hr compared to 24 hr (meta-analysis <em itemscope=""
            itemtype="http://schema.stenci.la/Emphasis">p</em> = <stencila-code-expression
            programming-language="r" itemscope="" itemtype="http://schema.stenci.la/CodeExpression">
            <code class="r"
              slot="text">sub('^(-)?0[.]','\\1.',round(a.meta.1v24$pval,4))</code><output
              slot="output"></output></stencila-code-expression>). Silent genes: 0 hr compared to 1
          hr (meta-analysis <em itemscope="" itemtype="http://schema.stenci.la/Emphasis">p</em> =
          <stencila-code-expression programming-language="r" itemscope=""
            itemtype="http://schema.stenci.la/CodeExpression"><code class="r"
              slot="text">sub('^(-)?0[.]','\\1.',round(s.meta.0v1$pval,3))</code><output
              slot="output"></output></stencila-code-expression>), 0 hr compared to 24 hr
          (meta-analysis <em itemscope="" itemtype="http://schema.stenci.la/Emphasis">p</em> =
          <stencila-code-expression programming-language="r" itemscope=""
            itemtype="http://schema.stenci.la/CodeExpression"><code class="r"
              slot="text">scinot(s.meta.0v24$pval)$coeff</code><output slot="output"></output>
          </stencila-code-expression>x10<sup itemscope=""
            itemtype="http://schema.stenci.la/Superscript">
            <stencila-code-expression programming-language="r" itemscope=""
              itemtype="http://schema.stenci.la/CodeExpression"><code class="r"
                slot="text">scinot(s.meta.0v24$pval)$exp</code><output slot="output"></output>
            </stencila-code-expression>
          </sup>), 1 hr compared to 24 hr (meta-analysis <em itemscope=""
            itemtype="http://schema.stenci.la/Emphasis">p</em> = <stencila-code-expression
            programming-language="r" itemscope="" itemtype="http://schema.stenci.la/CodeExpression">
            <code class="r"
              slot="text">sub('^(-)?0[.]','\\1.',round(s.meta.1v24$pval,4))</code><output
              slot="output"></output></stencila-code-expression>). Additional details for these
          meta-analyses can be found at <a href="https://osf.io/5yscz/" itemscope=""
            itemtype="http://schema.stenci.la/Link">https://osf.io/5yscz/</a>.</p>
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