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<h1 class="title toc-ignore">Intensity within and across plates</h1>
<h4 class="author"><em>Joyce Hsiao</em></h4>
</div>
<!-- The file analysis/chunks.R contains chunks that define default settings
shared across the workflowr files. -->
<!-- Update knitr chunk options -->
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<p><strong>Last updated:</strong> 2017-12-11</p>
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package git2r is installed -->
<p><strong>Code version:</strong> ab4fe7a</p>
<hr />
<div id="introductionsummary" class="section level2">
<h2>Introduction/summary</h2>
<ol style="list-style-type: decimal">
<li><p>Intensity distribution within each individual: for all three channels, we observe variation between single cell samples from the six individuals in both mean and variance; further, within each individual, the differences between single cell samples from different plates are dramatic, in both mean and variance.</p></li>
<li><p>Intensity correlation for each individual: high correlation between DAPI and GFP but not as much for between DAPI and RFP or between RFP and GREEN</p></li>
<li><p>Trying out PCA: The first PC explains 63% of variation in the data, and the second PC explains 27% of variation in the data. First PC correlated with RFP, GFP and DAPI and also correlated with nucleus size. The direction of correlation is the same for size and intensity metrics. Also, first PC is not correlated with batch, individual labels, perimeter or eccentricity.</p></li>
</ol>
<hr />
</div>
<div id="load-data" class="section level2">
<h2>Load data</h2>
<p><span class="math inline">\(~\)</span></p>
<pre class="r"><code>ints <- readRDS(file="/project2/gilad/joycehsiao/fucci-seq/data/intensity.rds")</code></pre>
<hr />
</div>
<div id="individual-variation-within-plate-and-across-plates" class="section level2">
<h2>Individual variation within plate and across plates</h2>
<p><strong>RFP</strong></p>
<p><img src="figure/images-qc-variation.Rmd/unnamed-chunk-3-1.png" width="1056" style="display: block; margin: auto;" /></p>
<p><span class="math inline">\(~\)</span></p>
<p><strong>GFP</strong></p>
<p><img src="figure/images-qc-variation.Rmd/unnamed-chunk-4-1.png" width="1056" style="display: block; margin: auto;" /></p>
<p><span class="math inline">\(~\)</span></p>
<p><strong>DAPI</strong></p>
<p><span class="math inline">\(~\)</span></p>
<p><img src="figure/images-qc-variation.Rmd/unnamed-chunk-5-1.png" width="1056" style="display: block; margin: auto;" /></p>
<hr />
</div>
<div id="intensity-correlation" class="section level2">
<h2>Intensity correlation</h2>
<p><span class="math inline">\(~\)</span></p>
<p><img src="figure/images-qc-variation.Rmd/unnamed-chunk-6-1.png" width="672" style="display: block; margin: auto;" /><img src="figure/images-qc-variation.Rmd/unnamed-chunk-6-2.png" width="672" style="display: block; margin: auto;" /><img src="figure/images-qc-variation.Rmd/unnamed-chunk-6-3.png" width="672" style="display: block; margin: auto;" /></p>
<hr />
</div>
<div id="pca" class="section level2">
<h2>PCA</h2>
<p>Proportion of variance explained by the 3 PCS.</p>
<pre><code>[1] 0.63063931 0.27099047 0.09837022</code></pre>
<p><strong>RFP versus PCs</strong></p>
<p><img src="figure/images-qc-variation.Rmd/unnamed-chunk-8-1.png" width="1152" style="display: block; margin: auto;" /></p>
<p><span class="math inline">\(~\)</span></p>
<p><strong>GFP versus PCs</strong></p>
<p><span class="math inline">\(~\)</span></p>
<p><img src="figure/images-qc-variation.Rmd/unnamed-chunk-9-1.png" width="1152" style="display: block; margin: auto;" /></p>
<p><span class="math inline">\(~\)</span></p>
<p><strong>DAPI versus PCs</strong></p>
<p><span class="math inline">\(~\)</span></p>
<p><img src="figure/images-qc-variation.Rmd/unnamed-chunk-10-1.png" width="1152" style="display: block; margin: auto;" /></p>
<p><span class="math inline">\(~\)</span></p>
<p><strong>Plate versus PCs</strong></p>
<p><span class="math inline">\(~\)</span></p>
<p><img src="figure/images-qc-variation.Rmd/unnamed-chunk-11-1.png" width="1152" style="display: block; margin: auto;" /></p>
<p><span class="math inline">\(~\)</span></p>
<p><strong>Individual label versus PCs</strong></p>
<p><span class="math inline">\(~\)</span></p>
<p><img src="figure/images-qc-variation.Rmd/unnamed-chunk-12-1.png" width="1152" style="display: block; margin: auto;" /></p>
<p><span class="math inline">\(~\)</span></p>
<p><strong>Nucleus size versus PCs</strong></p>
<p><span class="math inline">\(~\)</span></p>
<p><img src="figure/images-qc-variation.Rmd/unnamed-chunk-13-1.png" width="1152" style="display: block; margin: auto;" /></p>
<p><span class="math inline">\(~\)</span></p>
<p><strong>Eccentricity versus PCs</strong></p>
<p><span class="math inline">\(~\)</span></p>
<p><img src="figure/images-qc-variation.Rmd/unnamed-chunk-14-1.png" width="1152" style="display: block; margin: auto;" /></p>
<p><span class="math inline">\(~\)</span></p>
<p><strong>Perimeter versus PCs</strong></p>
<p><span class="math inline">\(~\)</span></p>
<p><img src="figure/images-qc-variation.Rmd/unnamed-chunk-15-1.png" width="1152" style="display: block; margin: auto;" /></p>
<p><span class="math inline">\(~\)</span></p>
<hr />
</div>
<div id="session-information" class="section level2">
<h2>Session information</h2>
<pre><code>R version 3.4.1 (2017-06-30)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Scientific Linux 7.2 (Nitrogen)
Matrix products: default
BLAS: /home/joycehsiao/miniconda3/envs/fucci-seq/lib/R/lib/libRblas.so
LAPACK: /home/joycehsiao/miniconda3/envs/fucci-seq/lib/R/lib/libRlapack.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] parallel stats graphics grDevices utils datasets methods
[8] base
other attached packages:
[1] scales_0.4.1 Biobase_2.38.0 BiocGenerics_0.24.0
[4] RColorBrewer_1.1-2 wesanderson_0.3.2 cowplot_0.8.0
[7] ggplot2_2.2.1 dplyr_0.7.0 data.table_1.10.4
loaded via a namespace (and not attached):
[1] Rcpp_0.12.14 knitr_1.16 magrittr_1.5 munsell_0.4.3
[5] colorspace_1.3-2 R6_2.2.0 rlang_0.1.2 stringr_1.2.0
[9] plyr_1.8.4 tools_3.4.1 grid_3.4.1 gtable_0.2.0
[13] git2r_0.19.0 htmltools_0.3.6 lazyeval_0.2.0 yaml_2.1.14
[17] rprojroot_1.2 digest_0.6.12 assertthat_0.1 tibble_1.3.3
[21] glue_1.1.1 evaluate_0.10.1 rmarkdown_1.6 labeling_0.3
[25] stringi_1.1.2 compiler_3.4.1 backports_1.0.5 </code></pre>
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