<!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" />
<title>R Notebook</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/jqueryui-1.11.4/jquery-ui.min.js"></script>
<link href="site_libs/tocify-1.9.1/jquery.tocify.css" rel="stylesheet" />
<script src="site_libs/tocify-1.9.1/jquery.tocify.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-5.0.13/css/fa-svg-with-js.css" rel="stylesheet" />
<script src="site_libs/font-awesome-5.0.13/js/fontawesome-all.min.js"></script>
<script src="site_libs/font-awesome-5.0.13/js/fa-v4-shims.min.js"></script>
<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;
}
.html-widget {
margin-bottom: 20px;
}
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 -->
<script>
$(document).ready(function () {
// move toc-ignore selectors from section div to header
$('div.section.toc-ignore')
.removeClass('toc-ignore')
.children('h1,h2,h3,h4,h5').addClass('toc-ignore');
// establish options
var options = {
selectors: "h1,h2,h3",
theme: "bootstrap3",
context: '.toc-content',
hashGenerator: function (text) {
return text.replace(/[.\\/?&!#<>]/g, '').replace(/\s/g, '_').toLowerCase();
},
ignoreSelector: ".toc-ignore",
scrollTo: 0
};
options.showAndHide = true;
options.smoothScroll = true;
// tocify
var toc = $("#TOC").tocify(options).data("toc-tocify");
});
</script>
<style type="text/css">
#TOC {
margin: 25px 0px 20px 0px;
}
@media (max-width: 768px) {
#TOC {
position: relative;
width: 100%;
}
}
.toc-content {
padding-left: 30px;
padding-right: 40px;
}
div.main-container {
max-width: 1200px;
}
div.tocify {
width: 20%;
max-width: 260px;
max-height: 85%;
}
@media (min-width: 768px) and (max-width: 991px) {
div.tocify {
width: 25%;
}
}
@media (max-width: 767px) {
div.tocify {
width: 100%;
max-width: none;
}
}
.tocify ul, .tocify li {
line-height: 20px;
}
.tocify-subheader .tocify-item {
font-size: 0.90em;
padding-left: 25px;
text-indent: 0;
}
.tocify .list-group-item {
border-radius: 0px;
}
</style>
<!-- setup 3col/9col grid for toc_float and main content -->
<div class="row-fluid">
<div class="col-xs-12 col-sm-4 col-md-3">
<div id="TOC" class="tocify">
</div>
</div>
<div class="toc-content col-xs-12 col-sm-8 col-md-9">
<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">10x-adipocyte-analysis</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/workflowr">
<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">R Notebook</h1>
</div>
<p><strong>Last updated:</strong> 2018-10-30</p>
<strong>workflowr checks:</strong> <small>(Click a bullet for more information)</small>
<ul>
<li>
<p><details> <summary> <strong style="color:blue;">✔</strong> <strong>R Markdown file:</strong> up-to-date </summary></p>
<p>Great! Since the R Markdown file has been committed to the Git repository, you know the exact version of the code that produced these results.</p>
</details>
</li>
<li>
<p><details> <summary> <strong style="color:blue;">✔</strong> <strong>Environment:</strong> empty </summary></p>
<p>Great job! The global environment was empty. Objects defined in the global environment can affect the analysis in your R Markdown file in unknown ways. For reproduciblity it’s best to always run the code in an empty environment.</p>
</details>
</li>
<li>
<p><details> <summary> <strong style="color:blue;">✔</strong> <strong>Seed:</strong> <code>set.seed(20181026)</code> </summary></p>
<p>The command <code>set.seed(20181026)</code> was run prior to running the code in the R Markdown file. Setting a seed ensures that any results that rely on randomness, e.g. subsampling or permutations, are reproducible.</p>
</details>
</li>
<li>
<p><details> <summary> <strong style="color:blue;">✔</strong> <strong>Session information:</strong> recorded </summary></p>
<p>Great job! Recording the operating system, R version, and package versions is critical for reproducibility.</p>
</details>
</li>
<li>
<p><details> <summary> <strong style="color:blue;">✔</strong> <strong>Repository version:</strong> <a href="https://github.com/PytrikFolkertsma/10x-adipocyte-analysis/tree/f7080f1532d8fb8c8acb22d5e540da898cd2336a" target="_blank">f7080f1</a> </summary></p>
Great! You are using Git for version control. Tracking code development and connecting the code version to the results is critical for reproducibility. The version displayed above was the version of the Git repository at the time these results were generated. <br><br> Note that you need to be careful to ensure that all relevant files for the analysis have been committed to Git prior to generating the results (you can use <code>wflow_publish</code> or <code>wflow_git_commit</code>). workflowr only checks the R Markdown file, but you know if there are other scripts or data files that it depends on. Below is the status of the Git repository when the results were generated:
<pre><code>
Ignored files:
Ignored: docs/figure/
Untracked files:
Untracked: code/out/
Untracked: code/run-alignment.R
Untracked: plots/
Unstaged changes:
Modified: code/regressout-cellcycle.R
</code></pre>
Note that any generated files, e.g. HTML, png, CSS, etc., are not included in this status report because it is ok for generated content to have uncommitted changes. </details>
</li>
</ul>
<details> <summary> <small><strong>Expand here to see past versions:</strong></small> </summary>
<ul>
<table style="border-collapse:separate; border-spacing:5px;">
<thead>
<tr>
<th style="text-align:left;">
File
</th>
<th style="text-align:left;">
Version
</th>
<th style="text-align:left;">
Author
</th>
<th style="text-align:left;">
Date
</th>
<th style="text-align:left;">
Message
</th>
</tr>
</thead>
<tbody>
<tr>
<td style="text-align:left;">
Rmd
</td>
<td style="text-align:left;">
<a href="https://github.com/PytrikFolkertsma/10x-adipocyte-analysis/blob/f7080f1532d8fb8c8acb22d5e540da898cd2336a/analysis/10x-180504-general-analysis.Rmd" target="_blank">f7080f1</a>
</td>
<td style="text-align:left;">
PytrikFolkertsma
</td>
<td style="text-align:left;">
2018-10-30
</td>
<td style="text-align:left;">
wflow_publish(c(“analysis/10x-180504-general-analysis.Rmd”,
</td>
</tr>
</tbody>
</table>
</ul>
<p></details></p>
<hr />
<p>Analysis of the 10x samples: - tSNE plots - Cell cycle regression - PCA - Alignment - Marker gene expression - tSNE colored on metadata</p>
<pre class="r"><code>library(Seurat)</code></pre>
<pre><code>Loading required package: ggplot2</code></pre>
<pre><code>Loading required package: cowplot</code></pre>
<pre><code>
Attaching package: 'cowplot'</code></pre>
<pre><code>The following object is masked from 'package:ggplot2':
ggsave</code></pre>
<pre><code>Loading required package: Matrix</code></pre>
<pre class="r"><code>library(ggplot2)
library(dplyr)</code></pre>
<pre><code>
Attaching package: 'dplyr'</code></pre>
<pre><code>The following objects are masked from 'package:stats':
filter, lag</code></pre>
<pre><code>The following objects are masked from 'package:base':
intersect, setdiff, setequal, union</code></pre>
<pre class="r"><code>all10x <- readRDS('output/10x-180504')
all10x.ccregout <- readRDS('output/10x-180504-ccregout')
#all10x.aligned <- readRDS('../output/10x-180504-aligned')
#all10x.aligned.ccregout <- readRDS('../output/10x-180504-ccregout-aligned')</code></pre>
<div id="qc-plots" class="section level1">
<h1>QC Plots</h1>
<pre class="r"><code>VlnPlot(all10x, features.plot='nGene', group.by='sample_name', point.size.use=-1, x.lab.rot=T)</code></pre>
<p><img src="figure/10x-180504-general-analysis.Rmd/unnamed-chunk-2-1.png" width="672" style="display: block; margin: auto;" /></p>
<pre class="r"><code>VlnPlot(all10x, features.plot='nUMI', group.by='sample_name', point.size.use=-1, x.lab.rot=T)</code></pre>
<p><img src="figure/10x-180504-general-analysis.Rmd/unnamed-chunk-3-1.png" width="672" style="display: block; margin: auto;" /></p>
<pre class="r"><code>VlnPlot(all10x, features.plot='percent.mito', group.by='sample_name', point.size.use=-1, x.lab.rot=T)</code></pre>
<p><img src="figure/10x-180504-general-analysis.Rmd/unnamed-chunk-4-1.png" width="672" style="display: block; margin: auto;" /></p>
<pre class="r"><code>GenePlot(all10x, 'nUMI', 'nGene')</code></pre>
<p><img src="figure/10x-180504-general-analysis.Rmd/unnamed-chunk-5-1.png" width="672" style="display: block; margin: auto;" /></p>
</div>
<div id="tsne" class="section level1">
<h1>TSNE</h1>
<p>Below are several tSNE plots of the 10x-180504 data. tSNE was performed on the first 15 principal components of the log-normalized scaled (nUMI and percent.mito regressed out) data.</p>
<p>Visceral and perirenal seem a bit mixed, and supraclavicular and subcutaneous too.</p>
<pre class="r"><code>TSNEPlot(all10x, pt.size=0.1, group.by='sample_name', do.label=T)</code></pre>
<p><img src="figure/10x-180504-general-analysis.Rmd/unnamed-chunk-6-1.png" width="672" style="display: block; margin: auto;" /></p>
<p>tSNE plots of samples within their depot. Peri2 and Peri3 seem to overlap really well, as well as Supra1 and Supra2, and Visce1 and Visce3.</p>
<pre class="r"><code>plot_grid(t1, t2, t3, t4)</code></pre>
<p><img src="figure/10x-180504-general-analysis.Rmd/unnamed-chunk-8-1.png" width="672" style="display: block; margin: auto;" /></p>
<p>tSNE colored on subtissue.</p>
<pre class="r"><code>TSNEPlot(all10x, group.by='depot', pt.size=0.1)</code></pre>
<p><img src="figure/10x-180504-general-analysis.Rmd/unnamed-chunk-9-1.png" width="672" style="display: block; margin: auto;" /></p>
<p>tSNE colored by cell cycle phase.</p>
<pre class="r"><code>TSNEPlot(all10x, group.by='Phase', pt.size=0.1)</code></pre>
<p><img src="figure/10x-180504-general-analysis.Rmd/unnamed-chunk-10-1.png" width="672" style="display: block; margin: auto;" /></p>
</div>
<div id="clusters" class="section level1">
<h1>Clusters</h1>
<p>Some clustering with different resolutions. res=0.5</p>
<pre class="r"><code>TSNEPlot(all10x, pt.size=0.1, group.by='res.0.5', do.label=T)</code></pre>
<p><img src="figure/10x-180504-general-analysis.Rmd/unnamed-chunk-11-1.png" width="672" style="display: block; margin: auto;" /></p>
<p>res=0.7</p>
<pre class="r"><code>TSNEPlot(all10x, pt.size=0.1, group.by='res.0.7', do.label=T)</code></pre>
<p><img src="figure/10x-180504-general-analysis.Rmd/unnamed-chunk-12-1.png" width="672" style="display: block; margin: auto;" /></p>
<p>res=1</p>
<pre class="r"><code>TSNEPlot(all10x, pt.size=0.1, group.by='res.1', do.label=T)</code></pre>
<p><img src="figure/10x-180504-general-analysis.Rmd/unnamed-chunk-13-1.png" width="672" style="display: block; margin: auto;" /></p>
<pre class="r"><code>TSNEPlot(all10x, pt.size=0.1, group.by='sample_name', do.label=T)</code></pre>
<p><img src="figure/10x-180504-general-analysis.Rmd/unnamed-chunk-14-1.png" width="672" style="display: block; margin: auto;" /></p>
</div>
<div id="cell-cycle-regression" class="section level1">
<h1>Cell cycle regression</h1>
<p>T-SNE of the data with cell cycle effects regressed out. There does not seem to be a lot of structure within clusters now.</p>
<pre class="r"><code>TSNEPlot(all10x.ccregout, pt.size=0.1, group.by='sample_name')</code></pre>
<p><img src="figure/10x-180504-general-analysis.Rmd/unnamed-chunk-15-1.png" width="672" style="display: block; margin: auto;" /></p>
<p>No cell cycle effect anymore.</p>
<pre class="r"><code>TSNEPlot(all10x.ccregout, pt.size=0.1, group.by='Phase')</code></pre>
<p><img src="figure/10x-180504-general-analysis.Rmd/unnamed-chunk-16-1.png" width="672" style="display: block; margin: auto;" /></p>
<p>Subtissues</p>
<pre class="r"><code>plot_grid(t1, t2, t3, t4)</code></pre>
<p><img src="figure/10x-180504-general-analysis.Rmd/unnamed-chunk-18-1.png" width="672" style="display: block; margin: auto;" /></p>
<pre class="r"><code>TSNEPlot(all10x.ccregout, pt.size=0.1, group.by='depot')</code></pre>
<p><img src="figure/10x-180504-general-analysis.Rmd/unnamed-chunk-19-1.png" width="672" style="display: block; margin: auto;" /></p>
</div>
<div id="pca" class="section level1">
<h1>PCA</h1>
<p>Some PCA plots. PC1 seems to capture cell cycle effects, and PC2 seems to capture some of the sample variability.</p>
<pre class="r"><code>PCAPlot(all10x, group.by='Phase', pt.size=0.1)</code></pre>
<p><img src="figure/10x-180504-general-analysis.Rmd/unnamed-chunk-20-1.png" width="672" style="display: block; margin: auto;" /></p>
<pre class="r"><code>PCAPlot(all10x, group.by='sample_name', pt.size=0.1)</code></pre>
<p><img src="figure/10x-180504-general-analysis.Rmd/unnamed-chunk-21-1.png" width="672" style="display: block; margin: auto;" /></p>
<p>PCA plot of the cell cycle regressed out data. There is no cell cycle effect anymore.</p>
<pre class="r"><code>PCAPlot(all10x.ccregout, group.by='Phase', pt.size=0.1)</code></pre>
<p><img src="figure/10x-180504-general-analysis.Rmd/unnamed-chunk-22-1.png" width="672" style="display: block; margin: auto;" /></p>
<pre class="r"><code>PCAPlot(all10x.ccregout, group.by='sample_name', pt.size=0.1)</code></pre>
<p><img src="figure/10x-180504-general-analysis.Rmd/unnamed-chunk-23-1.png" width="672" style="display: block; margin: auto;" /></p>
</div>
<div id="alignment" class="section level1">
<h1>Alignment</h1>
<p>Alignment of the data with and without cell cycle effects regressed out. Both were aligned on 30 subspaces, tSNE was performed on the first 15 CCs.</p>
<p>tSNE of the aligned data.</p>
<pre class="r"><code>#TSNEPlot(all10x.aligned, group.by='sample_name', pt.size=0.1)</code></pre>
<p>tSNE of the aligned data coloured on cell cycle phase.</p>
<pre class="r"><code>#TSNEPlot(all10x.aligned, group.by='Phase', pt.size=0.1)</code></pre>
<p>tSNE of the aligned data with cell cycle effects regressed out.</p>
<pre class="r"><code>#TSNEPlot(all10x.aligned.ccregout, group.by='sample_name', pt.size=0.1)</code></pre>
<p>tSNE of the aligned data with cell cycle effects regressed out, colored by phase.</p>
<pre class="r"><code>#TSNEPlot(all10x.aligned.ccregout, group.by='Phase', pt.size=0.1)</code></pre>
<p>tSNE of the aligned data with cell cycle effects regressed out, colored by subtissue</p>
<pre class="r"><code>#TSNEPlot(all10x.aligned.ccregout, group.by='sample_name2', pt.size=0.1)</code></pre>
</div>
<div id="metadata-plots" class="section level1">
<h1>Metadata plots</h1>
<pre class="r"><code>FeaturePlot(all10x, c("nGene"), cols.use = c("grey","blue"), no.legend=F)</code></pre>
<p><img src="figure/10x-180504-general-analysis.Rmd/unnamed-chunk-29-1.png" width="672" style="display: block; margin: auto;" /></p>
<pre class="r"><code>FeaturePlot(all10x, c("percent.mito"), cols.use = c("grey","blue"), no.legend=F)</code></pre>
<p><img src="figure/10x-180504-general-analysis.Rmd/unnamed-chunk-30-1.png" width="672" style="display: block; margin: auto;" /></p>
<pre class="r"><code>FeaturePlot(all10x, c("nUMI"), cols.use = c("grey","blue"), no.legend=F)</code></pre>
<p><img src="figure/10x-180504-general-analysis.Rmd/unnamed-chunk-31-1.png" width="672" style="display: block; margin: auto;" /></p>
<p>Diff</p>
<pre class="r"><code>TSNEPlot(all10x, group.by='diff', pt.size=0.1)</code></pre>
<p><img src="figure/10x-180504-general-analysis.Rmd/unnamed-chunk-32-1.png" width="672" style="display: block; margin: auto;" /></p>
<pre class="r"><code>all10x@meta.data['diff_int'] <- unlist(lapply(as.vector(unlist(all10x@meta.data$diff)), function(x){return(strtoi(strsplit(x, '%')))}))
FeaturePlot(all10x, features.plot='diff_int', cols.use=c('gray', 'blue'), no.legend=F)</code></pre>
<p><img src="figure/10x-180504-general-analysis.Rmd/unnamed-chunk-33-1.png" width="672" style="display: block; margin: auto;" /></p>
<p>ucp1.ctrl</p>
<pre class="r"><code>TSNEPlot(all10x, group.by='ucp1.ctrl', pt.size=0.1)</code></pre>
<p><img src="figure/10x-180504-general-analysis.Rmd/unnamed-chunk-34-1.png" width="672" style="display: block; margin: auto;" /></p>
<p>ucp1.ne</p>
<pre class="r"><code>TSNEPlot(all10x, group.by='ucp1.ne', pt.size=0.1)</code></pre>
<p><img src="figure/10x-180504-general-analysis.Rmd/unnamed-chunk-35-1.png" width="672" style="display: block; margin: auto;" /></p>
<p>bmi</p>
<pre class="r"><code>TSNEPlot(all10x, group.by='bmi', pt.size=0.1)</code></pre>
<p><img src="figure/10x-180504-general-analysis.Rmd/unnamed-chunk-36-1.png" width="672" style="display: block; margin: auto;" /></p>
<p>age</p>
<pre class="r"><code>TSNEPlot(all10x, group.by='age', pt.size=0.1)</code></pre>
<p><img src="figure/10x-180504-general-analysis.Rmd/unnamed-chunk-37-1.png" width="672" style="display: block; margin: auto;" /></p>
<pre class="r"><code>VlnPlot(all10x, group.by='sample_name', features.plot=c('nGene'), point.size.use = -1, x.lab.rot=T)</code></pre>
<p><img src="figure/10x-180504-general-analysis.Rmd/unnamed-chunk-38-1.png" width="672" style="display: block; margin: auto;" /></p>
<pre class="r"><code>VlnPlot(all10x, group.by='sample_name', features.plot=c('nUMI'), point.size.use = -1, x.lab.rot=T)</code></pre>
<p><img src="figure/10x-180504-general-analysis.Rmd/unnamed-chunk-39-1.png" width="672" style="display: block; margin: auto;" /></p>
<pre class="r"><code>VlnPlot(all10x, group.by='sample_name', features.plot=c('percent.mito'), point.size.use = -1, x.lab.rot=T)</code></pre>
<p><img src="figure/10x-180504-general-analysis.Rmd/unnamed-chunk-40-1.png" width="672" style="display: block; margin: auto;" /></p>
</div>
<div id="mixture-cluster-12" class="section level1">
<h1>Mixture cluster 12</h1>
<p>Sample composition in cluster 12.</p>
<pre class="r"><code>cluster12 <- SubsetData(all10x, cells.use=rownames(all10x@meta.data)[which(all10x@meta.data$res.0.5 %in% 12)])
rotate_x <- function(data, column_to_plot, labels_vec, rot_angle) {
plt <- barplot(data[[column_to_plot]], col='steelblue', xaxt="n")
text(plt, par("usr")[3], labels = labels_vec, srt = rot_angle, adj = c(1.1,1.1), xpd = TRUE, cex=1)
}
rotate_x((cluster12@meta.data %>% count(sample_name))[,2], 'n', as.vector(unlist((cluster12@meta.data %>% count(sample_name))[,1])), 45)</code></pre>
<p><img src="figure/10x-180504-general-analysis.Rmd/unnamed-chunk-41-1.png" width="672" style="display: block; margin: auto;" /></p>
</div>
<div id="figures-for-report" class="section level1">
<h1>Figures for report</h1>
<pre class="r"><code>fig1</code></pre>
<p><img src="figure/10x-180504-general-analysis.Rmd/fig1-1.png" width="1152" style="display: block; margin: auto;" /></p>
<pre class="r"><code>#Supplementary figures
sfig1 <- plot_grid(
VlnPlot(all10x, group.by='sample_name', features.plot=c('nGene'), point.size.use = -1, x.lab.rot=T, size.x.use=8),
VlnPlot(all10x, group.by='sample_name', features.plot=c('nUMI'), point.size.use = -1, x.lab.rot=T, size.x.use=8),
VlnPlot(all10x, group.by='sample_name', features.plot=c('percent.mito'), point.size.use = -1, x.lab.rot=T, size.x.use=8),
labels=c('a', 'b', 'c'), nrow=1
)
save_plot("plots/sfig1_180504_qcplots.pdf", sfig1, base_width=12, base_height=3)
sfig1</code></pre>
<p><img src="figure/10x-180504-general-analysis.Rmd/fig2-1.png" width="1152" style="display: block; margin: auto;" /></p>
<div id="session-information" class="section level2">
<h2>Session information</h2>
<pre class="r"><code>sessionInfo()</code></pre>
<pre><code>R version 3.4.3 (2017-11-30)
Platform: x86_64-redhat-linux-gnu (64-bit)
Running under: Red Hat Enterprise Linux
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] stats graphics grDevices utils datasets methods base
other attached packages:
[1] bindrcpp_0.2.2 dplyr_0.7.6 Seurat_2.3.4 Matrix_1.2-14
[5] cowplot_0.9.3 ggplot2_3.0.0
loaded via a namespace (and not attached):
[1] Rtsne_0.13 colorspace_1.3-2 class_7.3-14
[4] modeltools_0.2-22 ggridges_0.5.0 mclust_5.4.1
[7] rprojroot_1.3-2 htmlTable_1.12 base64enc_0.1-3
[10] rstudioapi_0.7 proxy_0.4-22 flexmix_2.3-14
[13] bit64_0.9-7 mvtnorm_1.0-8 codetools_0.2-15
[16] splines_3.4.3 R.methodsS3_1.7.1 robustbase_0.93-2
[19] knitr_1.20 Formula_1.2-3 jsonlite_1.5
[22] workflowr_1.1.1 ica_1.0-2 cluster_2.0.7-1
[25] kernlab_0.9-27 png_0.1-7 R.oo_1.22.0
[28] compiler_3.4.3 httr_1.3.1 backports_1.1.2
[31] assertthat_0.2.0 lazyeval_0.2.1 lars_1.2
[34] acepack_1.4.1 htmltools_0.3.6 tools_3.4.3
[37] igraph_1.2.2 gtable_0.2.0 glue_1.3.0
[40] RANN_2.6 reshape2_1.4.3 Rcpp_0.12.18
[43] trimcluster_0.1-2.1 gdata_2.18.0 ape_5.1
[46] nlme_3.1-137 iterators_1.0.10 fpc_2.1-11.1
[49] gbRd_0.4-11 lmtest_0.9-36 stringr_1.3.1
[52] irlba_2.3.2 gtools_3.8.1 DEoptimR_1.0-8
[55] MASS_7.3-50 zoo_1.8-3 scales_1.0.0
[58] doSNOW_1.0.16 parallel_3.4.3 RColorBrewer_1.1-2
[61] yaml_2.2.0 reticulate_1.10 pbapply_1.3-4
[64] gridExtra_2.3 rpart_4.1-13 segmented_0.5-3.0
[67] latticeExtra_0.6-28 stringi_1.2.4 foreach_1.4.4
[70] checkmate_1.8.5 caTools_1.17.1.1 bibtex_0.4.2
[73] Rdpack_0.9-0 SDMTools_1.1-221 rlang_0.2.2
[76] pkgconfig_2.0.2 dtw_1.20-1 prabclus_2.2-6
[79] bitops_1.0-6 evaluate_0.11 lattice_0.20-35
[82] ROCR_1.0-7 purrr_0.2.5 bindr_0.1.1
[85] labeling_0.3 htmlwidgets_1.2 bit_1.1-14
[88] tidyselect_0.2.4 plyr_1.8.4 magrittr_1.5
[91] R6_2.2.2 snow_0.4-2 gplots_3.0.1
[94] Hmisc_4.1-1 pillar_1.3.0 whisker_0.3-2
[97] foreign_0.8-70 withr_2.1.2 fitdistrplus_1.0-9
[100] mixtools_1.1.0 survival_2.42-6 nnet_7.3-12
[103] tsne_0.1-3 tibble_1.4.2 crayon_1.3.4
[106] hdf5r_1.0.0 KernSmooth_2.23-15 rmarkdown_1.10
[109] grid_3.4.3 data.table_1.11.4 git2r_0.23.0
[112] metap_1.0 digest_0.6.15 diptest_0.75-7
[115] tidyr_0.8.1 R.utils_2.7.0 stats4_3.4.3
[118] munsell_0.5.0 </code></pre>
</div>
</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 reproducible <a href="http://rmarkdown.rstudio.com">R Markdown</a>
analysis was created with
<a href="https://github.com/jdblischak/workflowr">workflowr</a> 1.1.1
</p>
<hr>
</div>
</div>
</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>