<!DOCTYPE html>
<html xmlns="http://www.w3.org/1999/xhtml">
<head>
<meta charset="utf-8" />
<meta http-equiv="Content-Type" content="text/html; charset=utf-8" />
<meta name="generator" content="pandoc" />
<meta name="author" content="Joyce Hsiao" />
<title>Lists of signficant genes using different types of correlation</title>
<script src="site_libs/jquery-1.11.3/jquery.min.js"></script>
<meta name="viewport" content="width=device-width, initial-scale=1" />
<link href="site_libs/bootstrap-3.3.5/css/cosmo.min.css" rel="stylesheet" />
<script src="site_libs/bootstrap-3.3.5/js/bootstrap.min.js"></script>
<script src="site_libs/bootstrap-3.3.5/shim/html5shiv.min.js"></script>
<script src="site_libs/bootstrap-3.3.5/shim/respond.min.js"></script>
<script src="site_libs/navigation-1.1/tabsets.js"></script>
<link href="site_libs/highlightjs-9.12.0/textmate.css" rel="stylesheet" />
<script src="site_libs/highlightjs-9.12.0/highlight.js"></script>
<link href="site_libs/font-awesome-4.5.0/css/font-awesome.min.css" rel="stylesheet" />
<style type="text/css">code{white-space: pre;}</style>
<style type="text/css">
pre:not([class]) {
background-color: white;
}
</style>
<script type="text/javascript">
if (window.hljs) {
hljs.configure({languages: []});
hljs.initHighlightingOnLoad();
if (document.readyState && document.readyState === "complete") {
window.setTimeout(function() { hljs.initHighlighting(); }, 0);
}
}
</script>
<style type="text/css">
h1 {
font-size: 34px;
}
h1.title {
font-size: 38px;
}
h2 {
font-size: 30px;
}
h3 {
font-size: 24px;
}
h4 {
font-size: 18px;
}
h5 {
font-size: 16px;
}
h6 {
font-size: 12px;
}
.table th:not([align]) {
text-align: left;
}
</style>
</head>
<body>
<style type = "text/css">
.main-container {
max-width: 940px;
margin-left: auto;
margin-right: auto;
}
code {
color: inherit;
background-color: rgba(0, 0, 0, 0.04);
}
img {
max-width:100%;
height: auto;
}
.tabbed-pane {
padding-top: 12px;
}
button.code-folding-btn:focus {
outline: none;
}
</style>
<style type="text/css">
/* padding for bootstrap navbar */
body {
padding-top: 51px;
padding-bottom: 40px;
}
/* offset scroll position for anchor links (for fixed navbar) */
.section h1 {
padding-top: 56px;
margin-top: -56px;
}
.section h2 {
padding-top: 56px;
margin-top: -56px;
}
.section h3 {
padding-top: 56px;
margin-top: -56px;
}
.section h4 {
padding-top: 56px;
margin-top: -56px;
}
.section h5 {
padding-top: 56px;
margin-top: -56px;
}
.section h6 {
padding-top: 56px;
margin-top: -56px;
}
</style>
<script>
// manage active state of menu based on current page
$(document).ready(function () {
// active menu anchor
href = window.location.pathname
href = href.substr(href.lastIndexOf('/') + 1)
if (href === "")
href = "index.html";
var menuAnchor = $('a[href="' + href + '"]');
// mark it active
menuAnchor.parent().addClass('active');
// if it's got a parent navbar menu mark it active as well
menuAnchor.closest('li.dropdown').addClass('active');
});
</script>
<div class="container-fluid main-container">
<!-- tabsets -->
<script>
$(document).ready(function () {
window.buildTabsets("TOC");
});
</script>
<!-- code folding -->
<div class="navbar navbar-default navbar-fixed-top" role="navigation">
<div class="container">
<div class="navbar-header">
<button type="button" class="navbar-toggle collapsed" data-toggle="collapse" data-target="#navbar">
<span class="icon-bar"></span>
<span class="icon-bar"></span>
<span class="icon-bar"></span>
</button>
<a class="navbar-brand" href="index.html">fucci-seq</a>
</div>
<div id="navbar" class="navbar-collapse collapse">
<ul class="nav navbar-nav">
<li>
<a href="index.html">Home</a>
</li>
<li>
<a href="about.html">About</a>
</li>
<li>
<a href="license.html">License</a>
</li>
</ul>
<ul class="nav navbar-nav navbar-right">
<li>
<a href="https://github.com/jdblischak/fucci-seq">
<span class="fa fa-github"></span>
</a>
</li>
</ul>
</div><!--/.nav-collapse -->
</div><!--/.container -->
</div><!--/.navbar -->
<!-- Add a small amount of space between sections. -->
<style type="text/css">
div.section {
padding-top: 12px;
}
</style>
<div class="fluid-row" id="header">
<h1 class="title toc-ignore">Lists of signficant genes using different types of correlation</h1>
<h4 class="author"><em>Joyce Hsiao</em></h4>
</div>
<div id="TOC">
<ul>
<li><a href="#summary">Summary</a></li>
<li><a href="#data-and-packages">Data and packages</a></li>
<li><a href="#projected-normal-on-pcs-of-redgreen">Projected normal on PCs of Red/Green</a></li>
<li><a href="#pearsons-correlation-on-unordered-data">Pearsons correlation on unordered data</a></li>
<li><a href="#circular-linear-correlation">Circular-linear correlation</a></li>
<li><a href="#cyclical-genes-by-smash">Cyclical genes by smash</a></li>
<li><a href="#circular-linear-correlation-1">Circular-linear correlation</a></li>
<li><a href="#compare-lists">Compare lists</a></li>
<li><a href="#session-information">Session information</a></li>
</ul>
</div>
<!-- The file analysis/chunks.R contains chunks that define default settings
shared across the workflowr files. -->
<!-- Update knitr chunk options -->
<!-- Insert the date the file was last updated -->
<p><strong>Last updated:</strong> 2018-03-14</p>
<!-- Insert the code version (Git commit SHA1) if Git repository exists and R
package git2r is installed -->
<p><strong>Code version:</strong> 302b4d3</p>
<hr />
<div id="summary" class="section level2">
<h2>Summary</h2>
<p>In terms of the enrichment for cell cycle genes found in Whitfield paper, the top 200 genes in linear correlation case has 5 fold enrichment, while the top 200 genes in circular-linear correlation case has 6.9 fold enrichment. When considering the top 100 genes, the linear correlation has 6.5 fold enrichment, and the circular-linear correlation has 9.4 fold enrichment.</p>
<ul>
<li>Something strange with smash results. No overlap with correlation results at all. There’s still some unresolved issues about how to apply smash to single cell RNA-seq data. For one, how to deal with dropouts?</li>
</ul>
<hr />
</div>
<div id="data-and-packages" class="section level2">
<h2>Data and packages</h2>
<p>Packages</p>
<pre class="r"><code>library(circular)
library(conicfit)
library(Biobase)
library(dplyr)
library(matrixStats)
library(smashr)
library(NPCirc)
library(CorShrink)</code></pre>
<p>Load data</p>
<pre class="r"><code>df <- readRDS(file="../data/eset-filtered.rds")
pdata <- pData(df)
fdata <- fData(df)
# select endogeneous genes
counts <- exprs(df)[grep("ENSG", rownames(df)), ]
log2cpm.all <- readRDS("../output/seqdata-batch-correction.Rmd/log2cpm.rds")
# log2cpm.adjust <- readRDS("../output/seqdata-batch-correction.Rmd/log2cpm.adjust.rds")
log2cpm <- log2cpm.all[grep("ENSG", rownames(log2cpm.all)), ]
# import corrected intensities
pdata.adj <- readRDS("../output/images-normalize-anova.Rmd/pdata.adj.rds")
macosko <- readRDS("../data/cellcycle-genes-previous-studies/rds/macosko-2015.rds")
source("../code/images-circle-ordering-npreg.R")</code></pre>
<hr />
</div>
<div id="projected-normal-on-pcs-of-redgreen" class="section level2">
<h2>Projected normal on PCs of Red/Green</h2>
<pre class="r"><code>pc.fucci <- prcomp(subset(pdata.adj,
select=c("rfp.median.log10sum.adjust",
"gfp.median.log10sum.adjust")),
center = T, scale. = T)
library(circular)
Theta.fucci <- coord2rad(pc.fucci$x)
log2cpm.ordered <- log2cpm[,order(as.numeric(Theta.fucci))]
Theta.fucci.ordered <- Theta.fucci[order(as.numeric(Theta.fucci))]</code></pre>
<p>–</p>
</div>
<div id="pearsons-correlation-on-unordered-data" class="section level2">
<h2>Pearsons correlation on unordered data</h2>
<pre class="r"><code>cors <- sapply(1:nrow(log2cpm), function(g) {
cor(Theta.fucci, log2cpm[g,])
})
nsamp.nonzero <- rowSums(log2cpm>0)
cors.shrink <- CorShrinkVector(cors, nsamp.nonzero, report_model = TRUE)
out.cors <- with(cors.shrink$model$result, data.frame(PosteriorMean, svalue))
rownames(out.cors) <- rownames(log2cpm)
out.cors.nosig <- out.cors[out.cors$svalue > .01,]
out.cors.sig <- out.cors[out.cors$svalue < .01,]
out.cors.sig.sorted <- out.cors.sig[order(out.cors.sig$svalue),]
# check macosko genes enrichment
mean(rownames(out.cors.sig) %in% macosko$ensembl)/mean(rownames(out.cors.nosig) %in% macosko$ensembl)</code></pre>
<pre><code>[1] 5.528023</code></pre>
<pre class="r"><code>mean((rownames(out.cors)[order(out.cors$svalue)])[1:200] %in% macosko$ensembl)/mean((rownames(out.cors)[order(out.cors$svalue)])[200:nrow(out.cors)] %in% macosko$ensembl)</code></pre>
<pre><code>[1] 4.925439</code></pre>
<pre class="r"><code>mean((rownames(out.cors)[order(out.cors$svalue)])[1:100] %in% macosko$ensembl)/mean((rownames(out.cors)[order(out.cors$svalue)])[100:nrow(out.cors)] %in% macosko$ensembl)</code></pre>
<pre><code>[1] 6.508723</code></pre>
<p>Save output.</p>
<pre class="r"><code>write.table((rownames(out.cors)[order(out.cors$svalue)])[1:200],
row.names = F, col.names = F, quote = F,
file = "../output/images-circle-ordering-sigcorgenes.Rmd/position.expression.lin.top200.txt")</code></pre>
<hr />
</div>
<div id="circular-linear-correlation" class="section level2">
<h2>Circular-linear correlation</h2>
<pre class="r"><code>library(Directional)
cors.circlin <- sapply(1:nrow(log2cpm), function(g) {
sqrt(circlin.cor(Theta.fucci, log2cpm[g,])[1])
})
nsamp.nonzero <- rowSums(log2cpm>0)
cors.circlin.shrink <- CorShrinkVector(cors.circlin, nsamp.nonzero, report_model = TRUE)
out.cors.circlin <- with(cors.circlin.shrink$model$result, data.frame(PosteriorMean, svalue))
rownames(out.cors.circlin) <- rownames(log2cpm)
out.cors.circlin.nosig <- out.cors.circlin[out.cors.circlin$svalue > .01,]
out.cors.circlin.sig <- out.cors.circlin[out.cors.circlin$svalue < .01,]
out.cors.circlin.sig.sorted <- out.cors.circlin[order(out.cors.circlin$svalue),]
# check macosko genes enrichment
mean(rownames(out.cors.circlin.sig) %in% macosko$ensembl)/mean(rownames(out.cors.circlin.nosig) %in% macosko$ensembl)</code></pre>
<pre><code>[1] 3.266438</code></pre>
<pre class="r"><code>mean((rownames(out.cors.circlin)[order(out.cors.circlin$svalue)])[1:200] %in% macosko$ensembl)/mean((rownames(out.cors.circlin)[order(out.cors.circlin$svalue)])[200:nrow(out.cors.circlin)] %in% macosko$ensembl)</code></pre>
<pre><code>[1] 3.486831</code></pre>
<pre class="r"><code>mean((rownames(out.cors.circlin)[order(out.cors.circlin$svalue)])[1:100] %in% macosko$ensembl)/mean((rownames(out.cors.circlin)[order(out.cors.circlin$svalue)])[100:nrow(out.cors.circlin)] %in% macosko$ensembl)</code></pre>
<pre><code>[1] 4.760504</code></pre>
<p>Save output.</p>
<pre class="r"><code>write.table((rownames(out.cors.circlin)[order(out.cors.circlin$svalue)])[1:200],
row.names = F, col.names = F, quote = F,
file = "../output/images-circle-ordering-sigcorgenes.Rmd/position.expression.cir.lin.top200.txt")</code></pre>
<hr />
</div>
<div id="cyclical-genes-by-smash" class="section level2">
<h2>Cyclical genes by smash</h2>
<pre class="r"><code>partitions <- partitionSamples.n(c(1:length(Theta.fucci)), 1, c(512,400))$partitions
indices.train <- partitions[[1]][[1]]
Y.train <- Theta.fucci.ordered[indices.train]
X.train <- log2cpm.ordered[,indices.train]
out.smash <- mclapply(1:nrow(log2cpm), function(g) {
xx.train <- X.train[g,]
is.zeros <- which(xx.train == 0)
not.zeros <- which(xx.train != 0)
xx.train.impute <- xx.train
if (length(is.zeros) > 1) {
for (j in 1:length(is.zeros)) {
pos <- is.zeros[j]
if (pos == 1) {impute.val <- xx.train[pos+1]}
if (pos == length(xx.train.impute)) {impute.val <- xx.train[pos-1]}
if (pos > 1 & pos < length(xx.train.impute)) {
impute.val <- min(xx.train[not.zeros], na.rm=T) }
xx.train.impute[pos] <- impute.val
}
} else { xx.train.impute <- xx.train}
fit.smash.xx <- smash(x = xx.train.impute)
pve <- 1- var(xx.train.impute-fit.smash.xx)/var(xx.train.impute)
return(list(xx.smash=fit.smash.xx,
xx.train.impute = xx.train.impute,
pve=pve))
}, mc.cores=10) </code></pre>
<pre class="r"><code>out.smash.fit <- do.call(rbind, lapply(out.smash, "[[", 1))
rownames(out.smash.fit) <- rownames(log2cpm)
out.smash.traindata <- do.call(rbind, lapply(out.smash, "[[", 2))
rownames(out.smash.traindata) <- rownames(log2cpm)
out.smash.pve <- sapply(out.smash, "[[", 3)
names(out.smash.pve) <- rownames(log2cpm)</code></pre>
<p>Save output.</p>
<pre class="r"><code>saveRDS(out.smash.pve, file = "../output/images-circle-ordering-sigcorgenes.Rmd/out.smash.pve.rds")
saveRDS(out.smash.traindata,
file = "../output/images-circle-ordering-sigcorgenes.Rmd/out.smash.traindata.rds")
saveRDS(out.smash.fit, file = "../output/images-circle-ordering-sigcorgenes.Rmd/out.smash.fit.rds")
write.table(names(out.smash.pve)[out.smash.pve > .5],
row.names = F, col.names = F, quote = F,
file = "../output/images-circle-ordering-sigcorgenes.Rmd/expression.smash.txt")</code></pre>
<pre class="r"><code>out.smash.pve <- readRDS("../output/images-circle-ordering-sigcorgenes.Rmd/out.smash.pve.rds")
out.smash.cyclical <- which(out.smash.pve > .1)
out.smash.notcyclical <- which(out.smash.pve < .1)
mean(names(out.smash.pve)[out.smash.pve > .5] %in% macosko$ensembl)/mean(names(out.smash.pve)[out.smash.pve < .5] %in% macosko$ensembl) </code></pre>
<pre><code>[1] 0.08888094</code></pre>
<hr />
</div>
<div id="circular-linear-correlation-1" class="section level2">
<h2>Circular-linear correlation</h2>
<pre class="r"><code>library(Directional)
cors.circlin <- sapply(1:nrow(log2cpm), function(g) {
sqrt(circlin.cor(Theta.fucci, log2cpm[g,])[1])
})
nsamp.nonzero <- rowSums(log2cpm>0)
cors.circlin.shrink <- CorShrinkVector(cors.circlin, nsamp.nonzero, report_model = TRUE)
out.cors.circlin <- with(cors.circlin.shrink$model$result, data.frame(PosteriorMean, svalue))
rownames(out.cors.circlin) <- rownames(log2cpm)
out.cors.circlin.nosig <- out.cors.circlin[out.cors.circlin$svalue > .001,]
out.cors.circlin.sig <- out.cors.circlin[out.cors.circlin$svalue < .001,]
out.cors.circlin.sig.sorted <- out.cors.circlin[order(out.cors.circlin$svalue),]
# check macosko genes enrichment
mean(rownames(out.cors.circlin.sig) %in% macosko$ensembl)/mean(rownames(out.cors.circlin.nosig) %in% macosko$ensembl)</code></pre>
<pre><code>[1] 3.095129</code></pre>
<p>Save output.</p>
<pre class="r"><code>write.table(out.cors.circlin.sig.sorted, row.names = F, col.names = F, quote = F,
file = "../output/images-circle-ordering-sigcorgenes.Rmd/position.expression.cir.lin.siggenes.txt")</code></pre>
<hr />
</div>
<div id="compare-lists" class="section level2">
<h2>Compare lists</h2>
<pre class="r"><code>library(VennDiagram)
grid.draw(venn.diagram(list(linear=(rownames(out.cors)[order(out.cors$svalue)])[1:200],
circ.linear=(rownames(out.cors.circlin)[order(out.cors.circlin$svalue)])[1:200],
smash=(names(out.smash.pve)[order(out.smash.pve, decreasing = T)])[1:200]),
filename = NULL))
grid.draw(venn.diagram(list(linear=(rownames(out.cors)[order(out.cors$svalue)])[1:500],
circ.linear=(rownames(out.cors.circlin)[order(out.cors.circlin$svalue)])[1:500],
smash=(names(out.smash.pve)[order(out.smash.pve, decreasing = T)])[1:500]),
filename = NULL))</code></pre>
<p><img src="figure/images-circle-ordering-sigcorgenes.Rmd/unnamed-chunk-14-1.png" width="672" style="display: block; margin: auto;" /></p>
<hr />
</div>
<div id="session-information" class="section level2">
<h2>Session information</h2>
<pre class="r"><code>sessionInfo()</code></pre>
<pre><code>R version 3.4.1 (2017-06-30)
Platform: x86_64-redhat-linux-gnu (64-bit)
Running under: Scientific Linux 7.2 (Nitrogen)
Matrix products: default
BLAS/LAPACK: /usr/lib64/R/lib/libRblas.so
locale:
[1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
[3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
[5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8
[7] LC_PAPER=en_US.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
attached base packages:
[1] grid parallel stats graphics grDevices utils datasets
[8] methods base
other attached packages:
[1] VennDiagram_1.6.19 futile.logger_1.4.3 Directional_3.0
[4] CorShrink_0.1.1 NPCirc_2.0.1 smashr_1.0.5
[7] caTools_1.17.1 data.table_1.10.4-3 Matrix_1.2-10
[10] wavethresh_4.6.8 MASS_7.3-47 ashr_2.2-7
[13] Rcpp_0.12.16 matrixStats_0.53.1 dplyr_0.7.4
[16] Biobase_2.38.0 BiocGenerics_0.24.0 conicfit_1.0.4
[19] geigen_2.1 pracma_2.1.4 circular_0.4-93
loaded via a namespace (and not attached):
[1] mvtnorm_1.0-7 lattice_0.20-35 assertthat_0.2.0
[4] rprojroot_1.3-2 digest_0.6.15 foreach_1.4.4
[7] mime_0.5 truncnorm_1.0-8 slam_0.1-42
[10] R6_2.2.2 plyr_1.8.4 futile.options_1.0.0
[13] backports_1.1.2 RcppZiggurat_0.1.4 evaluate_0.10.1
[16] pillar_1.2.1 rlang_0.2.0 pscl_1.5.2
[19] misc3d_0.8-4 rmarkdown_1.9 stringr_1.3.0
[22] htmlwidgets_1.0 shiny_1.0.5 compiler_3.4.1
[25] httpuv_1.3.6.2 pkgconfig_2.0.1 SQUAREM_2017.10-1
[28] shape_1.4.4 htmltools_0.3.6 tibble_1.4.2
[31] codetools_0.2-15 bitops_1.0-6 jsonlite_1.5
[34] xtable_1.8-2 git2r_0.21.0 magrittr_1.5
[37] Rfast_1.8.8 stringi_1.1.7 reshape2_1.4.3
[40] doParallel_1.0.11 bindrcpp_0.2 boot_1.3-19
[43] lambda.r_1.2 iterators_1.0.9 tools_3.4.1
[46] glue_1.2.0 movMF_0.2-2 crosstalk_1.0.0
[49] plotrix_3.7 yaml_2.1.18 knitr_1.20
[52] bindr_0.1.1 </code></pre>
</div>
<!-- Adjust MathJax settings so that all math formulae are shown using
TeX fonts only; see
http://docs.mathjax.org/en/latest/configuration.html. This will make
the presentation more consistent at the cost of the webpage sometimes
taking slightly longer to load. Note that this only works because the
footer is added to webpages before the MathJax javascript. -->
<script type="text/x-mathjax-config">
MathJax.Hub.Config({
"HTML-CSS": { availableFonts: ["TeX"] }
});
</script>
<hr>
<p>
This <a href="http://rmarkdown.rstudio.com">R Markdown</a> site was created with <a href="https://github.com/jdblischak/workflowr">workflowr</a>
</p>
<hr>
<!-- To enable disqus, uncomment the section below and provide your disqus_shortname -->
<!-- disqus
<div id="disqus_thread"></div>
<script type="text/javascript">
/* * * CONFIGURATION VARIABLES: EDIT BEFORE PASTING INTO YOUR WEBPAGE * * */
var disqus_shortname = 'rmarkdown'; // required: replace example with your forum shortname
/* * * DON'T EDIT BELOW THIS LINE * * */
(function() {
var dsq = document.createElement('script'); dsq.type = 'text/javascript'; dsq.async = true;
dsq.src = '//' + disqus_shortname + '.disqus.com/embed.js';
(document.getElementsByTagName('head')[0] || document.getElementsByTagName('body')[0]).appendChild(dsq);
})();
</script>
<noscript>Please enable JavaScript to view the <a href="http://disqus.com/?ref_noscript">comments powered by Disqus.</a></noscript>
<a href="http://disqus.com" class="dsq-brlink">comments powered by <span class="logo-disqus">Disqus</span></a>
-->
</div>
<script>
// add bootstrap table styles to pandoc tables
function bootstrapStylePandocTables() {
$('tr.header').parent('thead').parent('table').addClass('table table-condensed');
}
$(document).ready(function () {
bootstrapStylePandocTables();
});
</script>
<!-- dynamically load mathjax for compatibility with self-contained -->
<script>
(function () {
var script = document.createElement("script");
script.type = "text/javascript";
script.src = "https://mathjax.rstudio.com/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML";
document.getElementsByTagName("head")[0].appendChild(script);
})();
</script>
</body>
</html>