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McCarthy</em></h4> </div> <p><strong>Last updated:</strong> 2018-09-02</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. 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Below is the status of the Git repository when the results were generated: <pre><code> Ignored files: Ignored: .DS_Store Ignored: .Rhistory Ignored: .Rproj.user/ Ignored: .vscode/ Ignored: code/.DS_Store Ignored: data/raw/ Ignored: src/.DS_Store Ignored: src/Rmd/.Rhistory Untracked files: Untracked: Snakefile_clonality Untracked: Snakefile_somatic_calling Untracked: code/analysis_for_garx.Rmd Untracked: code/selection/ Untracked: code/yuanhua/ Untracked: data/canopy/ Untracked: data/cell_assignment/ Untracked: data/de_analysis_FTv62/ Untracked: data/donor_info_070818.txt Untracked: data/donor_info_core.csv Untracked: data/donor_neutrality.tsv Untracked: data/exome-point-mutations/ Untracked: data/fdr10.annot.txt.gz Untracked: data/human_H_v5p2.rdata Untracked: data/human_c2_v5p2.rdata Untracked: data/human_c6_v5p2.rdata Untracked: data/neg-bin-rsquared-petr.csv Untracked: data/neutralitytestr-petr.tsv Untracked: data/sce_merged_donors_cardelino_donorid_all_qc_filt.rds Untracked: data/sce_merged_donors_cardelino_donorid_all_with_qc_labels.rds Untracked: data/sce_merged_donors_cardelino_donorid_unstim_qc_filt.rds Untracked: data/sces/ Untracked: data/selection/ Untracked: data/simulations/ Untracked: data/variance_components/ Untracked: figures/ Untracked: output/differential_expression/ Untracked: output/donor_specific/ Untracked: output/line_info.tsv Untracked: output/nvars_by_category_by_donor.tsv Untracked: output/nvars_by_category_by_line.tsv Untracked: output/variance_components/ Untracked: references/ Untracked: tree.txt </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;"> html </td> <td style="text-align:left;"> <a href="https://cdn.rawgit.com/davismcc/fibroblast-clonality/f0ed980029a115234bc2edff312e5e52056d4eed/docs/clone_prevalences.html" target="_blank">f0ed980</a> </td> <td style="text-align:left;"> davismcc </td> <td style="text-align:left;"> 2018-08-31 </td> <td style="text-align:left;"> Build site. </td> </tr> <tr> <td style="text-align:left;"> Rmd </td> <td style="text-align:left;"> <a href="https://github.com/davismcc/fibroblast-clonality/blob/1310c939b2a3803d152ab0c3f885b905e7286dd4/analysis/clone_prevalences.Rmd" target="_blank">1310c93</a> </td> <td style="text-align:left;"> davismcc </td> <td style="text-align:left;"> 2018-08-30 </td> <td style="text-align:left;"> Tweaking plots </td> </tr> <tr> <td 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</td> <td style="text-align:left;"> 2018-08-26 </td> <td style="text-align:left;"> Build site. </td> </tr> <tr> <td style="text-align:left;"> html </td> <td style="text-align:left;"> <a href="https://cdn.rawgit.com/davismcc/fibroblast-clonality/36acf15b30f110282dd56b004c5d478d560b75e1/docs/clone_prevalences.html" target="_blank">36acf15</a> </td> <td style="text-align:left;"> davismcc </td> <td style="text-align:left;"> 2018-08-25 </td> <td style="text-align:left;"> Build site. </td> </tr> <tr> <td style="text-align:left;"> Rmd </td> <td style="text-align:left;"> <a href="https://github.com/davismcc/fibroblast-clonality/blob/d618fe52b90fd1d6e4f9613c8d7bbe3a3afde245/analysis/clone_prevalences.Rmd" target="_blank">d618fe5</a> </td> <td style="text-align:left;"> davismcc </td> <td style="text-align:left;"> 2018-08-25 </td> <td style="text-align:left;"> Updating analyses </td> </tr> <tr> <td style="text-align:left;"> html </td> <td style="text-align:left;"> <a href="https://cdn.rawgit.com/davismcc/fibroblast-clonality/090c1b94750a83d2101ffaaa654dab8150e6284b/docs/clone_prevalences.html" target="_blank">090c1b9</a> </td> <td style="text-align:left;"> davismcc </td> <td style="text-align:left;"> 2018-08-24 </td> <td style="text-align:left;"> Build site. </td> </tr> <tr> <td style="text-align:left;"> html </td> <td style="text-align:left;"> <a href="https://cdn.rawgit.com/davismcc/fibroblast-clonality/d2e8b3145e4600ec75d0d0df9ad1e210ecb1bdd3/docs/clone_prevalences.html" target="_blank">d2e8b31</a> </td> <td style="text-align:left;"> davismcc </td> <td style="text-align:left;"> 2018-08-19 </td> <td style="text-align:left;"> Build site. </td> </tr> <tr> <td style="text-align:left;"> html </td> <td style="text-align:left;"> <a href="https://cdn.rawgit.com/davismcc/fibroblast-clonality/1489d32ff1b8d5073a4170baec953cdbe4fcc14a/docs/clone_prevalences.html" target="_blank">1489d32</a> </td> <td style="text-align:left;"> davismcc </td> <td style="text-align:left;"> 2018-08-17 </td> <td style="text-align:left;"> Add html files </td> </tr> <tr> <td style="text-align:left;"> Rmd </td> <td style="text-align:left;"> <a href="https://github.com/davismcc/fibroblast-clonality/blob/a84777456428eab828494125e0b20fd8da2b16e1/analysis/clone_prevalences.Rmd" target="_blank">a847774</a> </td> <td style="text-align:left;"> davismcc </td> <td style="text-align:left;"> 2018-08-17 </td> <td style="text-align:left;"> Using “line” instead of “donor” </td> </tr> <tr> <td style="text-align:left;"> Rmd </td> <td style="text-align:left;"> <a href="https://github.com/davismcc/fibroblast-clonality/blob/1b44d28049b488f74539411ccaf222c0799c9b17/analysis/clone_prevalences.Rmd" target="_blank">1b44d28</a> </td> <td style="text-align:left;"> davismcc </td> <td style="text-align:left;"> 2018-08-13 </td> <td style="text-align:left;"> Adding simulation analysis file. </td> </tr> <tr> <td style="text-align:left;"> Rmd </td> <td style="text-align:left;"> <a href="https://github.com/davismcc/fibroblast-clonality/blob/1cbadbd5daa31e27ceca5199282f1ffde36c006c/analysis/clone_prevalences.Rmd" target="_blank">1cbadbd</a> </td> <td style="text-align:left;"> davismcc </td> <td style="text-align:left;"> 2018-08-10 </td> <td style="text-align:left;"> Updating analyses. </td> </tr> <tr> <td style="text-align:left;"> Rmd </td> <td style="text-align:left;"> <a href="https://github.com/davismcc/fibroblast-clonality/blob/2531565c0eba92e0f84ae80d0f22c5b3cb420d3b/analysis/clone_prevalences.Rmd" target="_blank">2531565</a> </td> <td style="text-align:left;"> davismcc </td> <td style="text-align:left;"> 2018-08-08 </td> <td style="text-align:left;"> Tweaking clone prevalences </td> </tr> <tr> <td style="text-align:left;"> Rmd </td> <td style="text-align:left;"> <a href="https://github.com/davismcc/fibroblast-clonality/blob/7397e0056507adf3b524c8613894152284582480/analysis/clone_prevalences.Rmd" target="_blank">7397e00</a> </td> <td style="text-align:left;"> davismcc </td> <td style="text-align:left;"> 2018-08-08 </td> <td style="text-align:left;"> Updating stylez and tweaking Rmds </td> </tr> <tr> <td style="text-align:left;"> Rmd </td> <td style="text-align:left;"> <a href="https://github.com/davismcc/fibroblast-clonality/blob/5a9a5ba35440c1bf7c0e840c760f1b1df28d88a7/analysis/clone_prevalences.Rmd" target="_blank">5a9a5ba</a> </td> <td style="text-align:left;"> davismcc </td> <td style="text-align:left;"> 2018-08-08 </td> <td style="text-align:left;"> Adding cowplot </td> </tr> <tr> <td style="text-align:left;"> Rmd </td> <td style="text-align:left;"> <a href="https://github.com/davismcc/fibroblast-clonality/blob/2a45547124e4f0732e3e830078e0057369b43fc8/analysis/clone_prevalences.Rmd" target="_blank">2a45547</a> </td> <td style="text-align:left;"> davismcc </td> <td style="text-align:left;"> 2018-08-08 </td> <td style="text-align:left;"> Adding viridis library </td> </tr> <tr> <td style="text-align:left;"> Rmd </td> <td style="text-align:left;"> <a href="https://github.com/davismcc/fibroblast-clonality/blob/d6b3b74e7dec676d6e85dfc182f64786b9070fb9/analysis/clone_prevalences.Rmd" target="_blank">d6b3b74</a> </td> <td style="text-align:left;"> davismcc </td> <td style="text-align:left;"> 2018-08-08 </td> <td style="text-align:left;"> Adding clone prevalence analysis </td> </tr> </tbody> </table> </ul> <p></details></p> <hr /> <div id="load-libraries-and-data" class="section level2"> <h2>Load libraries and data</h2> <div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r">knitr<span class="op">::</span>opts_chunk<span class="op">$</span><span class="kw">set</span>(<span class="dt">echo =</span> <span class="ot">TRUE</span>) <span class="kw">dir.create</span>(<span class="st">"figures/clone_prevalences"</span>, <span class="dt">showWarnings =</span> <span class="ot">FALSE</span>, <span class="dt">recursive =</span> <span class="ot">TRUE</span>) <span class="kw">library</span>(tidyverse) <span class="kw">library</span>(viridis) <span class="kw">library</span>(cowplot)</code></pre></div> <p>Load the Canopy clone inference results and the cell assignment results from cardelino for 32 donor fibroblast cell lines.</p> <div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r">params <-<span class="st"> </span><span class="kw">list</span>() params<span class="op">$</span>callset <-<span class="st"> "filt_lenient.cell_coverage_sites"</span> fls <-<span class="st"> </span><span class="kw">list.files</span>(<span class="st">"data/sces"</span>) fls <-<span class="st"> </span>fls[<span class="kw">grepl</span>(params<span class="op">$</span>callset, fls)] lines <-<span class="st"> </span><span class="kw">gsub</span>(<span class="st">".*ce_([a-z]+)_.*"</span>, <span class="st">"</span><span class="ch">\\</span><span class="st">1"</span>, fls) cell_assign_list <-<span class="st"> </span><span class="kw">list</span>() <span class="cf">for</span> (don <span class="cf">in</span> lines) { cell_assign_list[[don]] <-<span class="st"> </span><span class="kw">readRDS</span>(<span class="kw">file.path</span>(<span class="st">"data/cell_assignment"</span>, <span class="kw">paste0</span>(<span class="st">"cardelino_results."</span>, don, <span class="st">"."</span>, params<span class="op">$</span>callset, <span class="st">".rds"</span>))) <span class="kw">cat</span>(<span class="kw">paste</span>(<span class="st">"reading"</span>, don, <span class="st">"</span><span class="ch">\n</span><span class="st">"</span>)) }</code></pre></div> <pre><code>reading euts reading fawm reading feec reading fikt reading garx reading gesg reading heja reading hipn reading ieki reading joxm reading kuco reading laey reading lexy reading naju reading nusw reading oaaz reading oilg reading pipw reading puie reading qayj reading qolg reading qonc reading rozh reading sehl reading ualf reading vass reading vils reading vuna reading wahn reading wetu reading xugn reading zoxy </code></pre> <div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r">canopy_list <-<span class="st"> </span><span class="kw">list</span>() prev_list <-<span class="st"> </span><span class="kw">list</span>() <span class="cf">for</span> (don <span class="cf">in</span> lines) { tmp_df <-<span class="st"> </span><span class="kw">data_frame</span>( <span class="dt">line =</span> don, <span class="dt">clone =</span> <span class="kw">rownames</span>(cell_assign_list[[don]]<span class="op">$</span>tree<span class="op">$</span>P), <span class="dt">prev_canopy =</span> cell_assign_list[[don]]<span class="op">$</span>tree<span class="op">$</span>P[, <span class="dv">1</span>], <span class="dt">prev_cardelino =</span> <span class="ot">NA</span>, <span class="dt">n_cells =</span> <span class="kw">length</span>(cell_assign_list[[don]]<span class="op">$</span>clone_assigned), <span class="dt">n_assigned =</span> <span class="kw">sum</span>(cell_assign_list[[don]]<span class="op">$</span>clone_assigned <span class="op">!=</span><span class="st"> "unassigned"</span>), <span class="dt">prop_assigned =</span> n_assigned <span class="op">/</span><span class="st"> </span>n_cells ) <span class="cf">for</span> (i <span class="cf">in</span> <span class="kw">seq_len</span>(<span class="kw">nrow</span>(tmp_df))) { tmp_df<span class="op">$</span>prev_cardelino[i] <-<span class="st"> </span>(<span class="kw">sum</span>( cell_assign_list[[don]]<span class="op">$</span>clone_assigned <span class="op">==</span><span class="st"> </span>tmp_df<span class="op">$</span>clone[i]) <span class="op">/</span><span class="st"> </span> <span class="st"> </span>tmp_df<span class="op">$</span>n_assigned[i]) } prev_list[[don]] <-<span class="st"> </span>tmp_df } df_prev <-<span class="st"> </span><span class="kw">do.call</span>(<span class="st">"rbind"</span>, prev_list) lm_eqn <-<span class="st"> </span><span class="cf">function</span>(df) { m <-<span class="st"> </span><span class="kw">lm</span>(prev_cardelino <span class="op">~</span><span class="st"> </span>prev_canopy, df); eq <-<span class="st"> </span><span class="kw">substitute</span>(<span class="kw">italic</span>(r)<span class="op">^</span><span class="dv">2</span><span class="op">~</span><span class="st">"="</span><span class="op">~</span>r2, <span class="kw">list</span>(<span class="dt">a =</span> <span class="kw">format</span>(<span class="kw">coef</span>(m)[<span class="dv">1</span>], <span class="dt">digits =</span> <span class="dv">2</span>), <span class="dt">b =</span> <span class="kw">format</span>(<span class="kw">coef</span>(m)[<span class="dv">2</span>], <span class="dt">digits =</span> <span class="dv">2</span>), <span class="dt">r2 =</span> <span class="kw">format</span>(<span class="kw">summary</span>(m)<span class="op">$</span>r.squared, <span class="dt">digits =</span> <span class="dv">3</span>))) <span class="kw">as.character</span>(<span class="kw">as.expression</span>(eq)); } ## Fit weighted regressions fits <-<span class="st"> </span>df_prev <span class="op">%>%</span> <span class="st"> </span><span class="kw">group_by</span>(clone) <span class="op">%>%</span><span class="st"> </span> <span class="st"> </span><span class="kw">do</span>(<span class="dt">fit =</span> <span class="kw">lm</span>(prev_cardelino <span class="op">~</span><span class="st"> </span>prev_canopy, <span class="dt">weights =</span> prop_assigned, <span class="dt">data =</span> .)) fits_1grp <-<span class="st"> </span>df_prev <span class="op">%>%</span> <span class="st"> </span><span class="kw">do</span>(<span class="dt">fit =</span> <span class="kw">lm</span>(prev_cardelino <span class="op">~</span><span class="st"> </span>prev_canopy, <span class="dt">weights =</span> prop_assigned, <span class="dt">data =</span> .)) le_lin_fit <-<span class="st"> </span><span class="cf">function</span>(dat) { the_fit <-<span class="st"> </span><span class="kw">lm</span>(prev_cardelino <span class="op">~</span><span class="st"> </span>prev_canopy, <span class="dt">weights =</span> prop_assigned, dat) <span class="kw">setNames</span>(<span class="kw">data.frame</span>(<span class="kw">t</span>(<span class="kw">coef</span>(the_fit))), <span class="kw">c</span>(<span class="st">"x0"</span>, <span class="st">"x1"</span>)) } fits_me <-<span class="st"> </span>df_prev <span class="op">%>%</span> <span class="st"> </span><span class="kw">group_by</span>(clone) <span class="op">%>%</span><span class="st"> </span> <span class="st"> </span><span class="kw">do</span>(<span class="kw">le_lin_fit</span>(.)) fits_me_1grp <-<span class="st"> </span>df_prev <span class="op">%>%</span> <span class="st"> </span><span class="kw">do</span>(<span class="kw">le_lin_fit</span>(.)) <span class="kw">summary</span>(fits_1grp<span class="op">$</span>fit[<span class="dv">1</span>][[<span class="dv">1</span>]])</code></pre></div> <pre><code> Call: lm(formula = prev_cardelino ~ prev_canopy, data = ., weights = prop_assigned) Weighted Residuals: Min 1Q Median 3Q Max -0.34834 -0.09832 0.01523 0.07408 0.42785 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 0.09599 0.02566 3.741 0.000315 *** prev_canopy 0.71830 0.05903 12.169 < 2e-16 *** --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 0.1423 on 94 degrees of freedom Multiple R-squared: 0.6117, Adjusted R-squared: 0.6076 F-statistic: 148.1 on 1 and 94 DF, p-value: < 2.2e-16</code></pre> </div> <div id="plot-clone-prevalences" class="section level2"> <h2>Plot clone prevalences</h2> <p>Plot the estimated clone fractions from the cells assigned to a clone by cardelino against the estimated clone fractions from Canopy.</p> <div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r">fits_1grp <span class="op">%>%</span> <span class="st"> </span>broom<span class="op">::</span><span class="kw">augment</span>(fit) <span class="op">%>%</span><span class="st"> </span> <span class="st"> </span><span class="kw">inner_join</span>(., df_prev) <span class="op">%>%</span> <span class="kw">ggplot</span>(<span class="kw">aes</span>(<span class="dt">x =</span> prev_canopy, <span class="dt">y =</span> prev_cardelino, <span class="dt">shape =</span> clone, <span class="dt">fill =</span> prop_assigned)) <span class="op">+</span> <span class="st"> </span><span class="kw">geom_abline</span>(<span class="dt">slope =</span> <span class="dv">1</span>, <span class="dt">intercept =</span> <span class="dv">0</span>, <span class="dt">colour =</span> <span class="st">"gray40"</span>, <span class="dt">linetype =</span> <span class="dv">2</span>) <span class="op">+</span> <span class="st"> </span><span class="kw">geom_ribbon</span>(<span class="kw">aes</span>(<span class="dt">ymin =</span> .fitted <span class="op">-</span><span class="st"> </span><span class="fl">1.645</span> <span class="op">*</span><span class="st"> </span>.se.fit, <span class="dt">ymax =</span> .fitted <span class="op">+</span><span class="st"> </span><span class="fl">1.645</span> <span class="op">*</span><span class="st"> </span>.se.fit), <span class="dt">fill =</span> <span class="st">"gray70"</span>, <span class="dt">alpha =</span> <span class="fl">0.7</span>) <span class="op">+</span> <span class="st"> </span><span class="kw">geom_abline</span>(<span class="kw">aes</span>(<span class="dt">intercept =</span> x0, <span class="dt">slope =</span> x1), <span class="dt">data =</span> fits_me_1grp, <span class="dt">colour =</span> <span class="st">"firebrick"</span>, <span class="dt">size =</span> <span class="dv">2</span>) <span class="op">+</span> <span class="st"> </span><span class="kw">geom_point</span>(<span class="dt">size =</span> <span class="dv">3</span>) <span class="op">+</span> <span class="st"> </span><span class="kw">xlim</span>(<span class="dv">0</span>, <span class="dv">1</span>) <span class="op">+</span><span class="st"> </span><span class="kw">ylim</span>(<span class="dv">0</span>, <span class="dv">1</span>) <span class="op">+</span> <span class="st"> </span><span class="kw">geom_text</span>(<span class="dt">x =</span> <span class="fl">0.9</span>, <span class="dt">y =</span> <span class="dv">0</span>, <span class="dt">colour =</span> <span class="st">"black"</span>, <span class="dt">label =</span> <span class="kw">lm_eqn</span>(df_prev), <span class="dt">size =</span> <span class="dv">5</span>, <span class="dt">parse =</span> <span class="ot">TRUE</span>, <span class="dt">data =</span> df_prev[<span class="dv">1</span>,]) <span class="op">+</span> <span class="st"> </span><span class="kw">scale_fill_viridis</span>(<span class="dt">name =</span> <span class="st">"fraction of</span><span class="ch">\n</span><span class="st">cells assigned"</span>, <span class="dt">limits =</span> <span class="kw">c</span>(<span class="dv">0</span>, <span class="dv">1</span>)) <span class="op">+</span> <span class="st"> </span><span class="kw">scale_shape_manual</span>(<span class="dt">values =</span> <span class="dv">21</span><span class="op">:</span><span class="dv">25</span>) <span class="op">+</span> <span class="st"> </span><span class="kw">xlab</span>(<span class="st">"Estimated clone prevalence (Canopy)"</span>) <span class="op">+</span> <span class="st"> </span><span class="kw">ylab</span>(<span class="st">"Assigned clone fraction (cardelino)"</span>)</code></pre></div> <pre><code>Joining, by = c("prev_cardelino", "prev_canopy")</code></pre> <p><img src="figure/clone_prevalences.Rmd/plot-prev-1.png" width="672" style="display: block; margin: auto;" /></p> <details> <summary><em>Expand here to see past versions of plot-prev-1.png:</em></summary> <table style="border-collapse:separate; border-spacing:5px;"> <thead> <tr> <th style="text-align:left;"> Version </th> <th style="text-align:left;"> Author </th> <th style="text-align:left;"> Date </th> </tr> </thead> <tbody> <tr> <td style="text-align:left;"> <a href="https://github.com/davismcc/fibroblast-clonality/blob/d2e8b3145e4600ec75d0d0df9ad1e210ecb1bdd3/docs/figure/clone_prevalences.Rmd/plot-prev-1.png" target="_blank">d2e8b31</a> </td> <td style="text-align:left;"> davismcc </td> <td style="text-align:left;"> 2018-08-19 </td> </tr> </tbody> </table> <p></details></p> <div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r"><span class="kw">ggsave</span>(<span class="st">"figures/clone_prevalences/clone_prev_scatter.png"</span>, <span class="dt">height =</span> <span class="dv">5</span>, <span class="dt">width =</span> <span class="dv">7</span>) <span class="kw">ggsave</span>(<span class="st">"figures/clone_prevalences/clone_prev_scatter.pdf"</span>, <span class="dt">height =</span> <span class="dv">5</span>, <span class="dt">width =</span> <span class="dv">7</span>)</code></pre></div> <p>We can also look at the same plot as above, but now faceted by the different clones.</p> <div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r">fits <span class="op">%>%</span> <span class="st"> </span>broom<span class="op">::</span><span class="kw">augment</span>(fit) <span class="op">%>%</span><span class="st"> </span> <span class="st"> </span><span class="kw">inner_join</span>(., df_prev) <span class="op">%>%</span> <span class="st"> </span><span class="kw">ggplot</span>(<span class="kw">aes</span>(<span class="dt">x =</span> prev_canopy, <span class="dt">y =</span> prev_cardelino)) <span class="op">+</span> <span class="st"> </span><span class="kw">geom_abline</span>(<span class="dt">slope =</span> <span class="dv">1</span>, <span class="dt">intercept =</span> <span class="dv">0</span>, <span class="dt">colour =</span> <span class="st">"gray40"</span>, <span class="dt">linetype =</span> <span class="dv">2</span>) <span class="op">+</span> <span class="st"> </span><span class="kw">geom_ribbon</span>(<span class="kw">aes</span>(<span class="dt">ymin =</span> .fitted <span class="op">-</span><span class="st"> </span><span class="fl">1.645</span> <span class="op">*</span><span class="st"> </span>.se.fit, <span class="dt">ymax =</span> .fitted <span class="op">+</span><span class="st"> </span><span class="fl">1.645</span> <span class="op">*</span><span class="st"> </span>.se.fit), <span class="dt">fill =</span> <span class="st">"gray70"</span>, <span class="dt">alpha =</span> <span class="fl">0.7</span>) <span class="op">+</span> <span class="st"> </span><span class="kw">geom_abline</span>(<span class="kw">aes</span>(<span class="dt">intercept =</span> x0, <span class="dt">slope =</span> x1), <span class="dt">data =</span> fits_me, <span class="dt">colour =</span> <span class="st">"firebrick"</span>, <span class="dt">size =</span> <span class="dv">2</span>) <span class="op">+</span> <span class="st"> </span><span class="kw">geom_point</span>(<span class="kw">aes</span>(<span class="dt">fill =</span> prop_assigned), <span class="dt">size =</span> <span class="dv">3</span>, <span class="dt">shape =</span> <span class="dv">21</span>) <span class="op">+</span> <span class="st"> </span><span class="kw">xlim</span>(<span class="dv">0</span>, <span class="dv">1</span>) <span class="op">+</span><span class="st"> </span><span class="kw">ylim</span>(<span class="dv">0</span>, <span class="dv">1</span>) <span class="op">+</span> <span class="st"> </span><span class="kw">facet_wrap</span>(<span class="op">~</span>clone) <span class="op">+</span> <span class="st"> </span><span class="kw">scale_fill_viridis</span>(<span class="dt">name =</span> <span class="st">"fraction of</span><span class="ch">\n</span><span class="st">cells assigned"</span>, <span class="dt">limits =</span> <span class="kw">c</span>(<span class="dv">0</span>, <span class="dv">1</span>)) <span class="op">+</span> <span class="st"> </span><span class="kw">scale_shape_manual</span>(<span class="dt">values =</span> <span class="dv">21</span><span class="op">:</span><span class="dv">25</span>) <span class="op">+</span> <span class="st"> </span><span class="kw">xlab</span>(<span class="st">"Estimated clone prevalence (Canopy)"</span>) <span class="op">+</span> <span class="st"> </span><span class="kw">ylab</span>(<span class="st">"Assigned clone fraction (cardelino)"</span>)</code></pre></div> <pre><code>Joining, by = c("clone", "prev_cardelino", "prev_canopy")</code></pre> <p><img src="figure/clone_prevalences.Rmd/plot-prev-facet-clone-1.png" width="864" style="display: block; margin: auto;" /></p> <details> <summary><em>Expand here to see past versions of plot-prev-facet-clone-1.png:</em></summary> <table style="border-collapse:separate; border-spacing:5px;"> <thead> <tr> <th style="text-align:left;"> Version </th> <th style="text-align:left;"> Author </th> <th style="text-align:left;"> Date </th> </tr> </thead> <tbody> <tr> <td style="text-align:left;"> <a href="https://github.com/davismcc/fibroblast-clonality/blob/d2e8b3145e4600ec75d0d0df9ad1e210ecb1bdd3/docs/figure/clone_prevalences.Rmd/plot-prev-facet-clone-1.png" target="_blank">d2e8b31</a> </td> <td style="text-align:left;"> davismcc </td> <td style="text-align:left;"> 2018-08-19 </td> </tr> </tbody> </table> <p></details></p> <div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r"><span class="kw">ggsave</span>(<span class="st">"figures/clone_prevalences/clone_prev_scatter_facet_clone.png"</span>, <span class="dt">height =</span> <span class="dv">7</span>, <span class="dt">width =</span> <span class="dv">9</span>) <span class="kw">ggsave</span>(<span class="st">"figures/clone_prevalences/clone_prev_scatter_facet_clone.pdf"</span>, <span class="dt">height =</span> <span class="dv">7</span>, <span class="dt">width =</span> <span class="dv">9</span>)</code></pre></div> <p>Since there are so few lines with four clones we can also make a version of the figure above with just clone1, clone2 and clone3 and fitted a weighted regression line, with points weighted by the fraction of cells assigned for the line.</p> <div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r">fits <span class="op">%>%</span> <span class="st"> </span>broom<span class="op">::</span><span class="kw">augment</span>(fit) <span class="op">%>%</span><span class="st"> </span> <span class="st"> </span><span class="kw">inner_join</span>(., df_prev) <span class="op">%>%</span> <span class="st"> </span>dplyr<span class="op">::</span><span class="kw">filter</span>(clone <span class="op">!=</span><span class="st"> "clone4"</span>) <span class="op">%>%</span> <span class="st"> </span><span class="kw">ggplot</span>(<span class="kw">aes</span>(<span class="dt">x =</span> prev_canopy, <span class="dt">y =</span> prev_cardelino, <span class="dt">fill =</span> prop_assigned)) <span class="op">+</span> <span class="st"> </span><span class="kw">geom_abline</span>(<span class="dt">slope =</span> <span class="dv">1</span>, <span class="dt">intercept =</span> <span class="dv">0</span>, <span class="dt">colour =</span> <span class="st">"gray40"</span>, <span class="dt">linetype =</span> <span class="dv">2</span>) <span class="op">+</span> <span class="st"> </span><span class="kw">geom_ribbon</span>(<span class="kw">aes</span>(<span class="dt">ymin =</span> .fitted <span class="op">-</span><span class="st"> </span><span class="fl">1.645</span> <span class="op">*</span><span class="st"> </span>.se.fit, <span class="dt">ymax =</span> .fitted <span class="op">+</span><span class="st"> </span><span class="fl">1.645</span> <span class="op">*</span><span class="st"> </span>.se.fit), <span class="dt">fill =</span> <span class="st">"gray70"</span>, <span class="dt">alpha =</span> <span class="fl">0.7</span>) <span class="op">+</span> <span class="st"> </span><span class="kw">geom_abline</span>(<span class="kw">aes</span>(<span class="dt">intercept =</span> x0, <span class="dt">slope =</span> x1), <span class="dt">data =</span> dplyr<span class="op">::</span><span class="kw">filter</span>(fits_me, clone <span class="op">!=</span><span class="st"> "clone4"</span>), <span class="dt">colour =</span> <span class="st">"firebrick"</span>, <span class="dt">size =</span> <span class="dv">1</span>) <span class="op">+</span> <span class="st"> </span><span class="kw">geom_point</span>(<span class="dt">size =</span> <span class="dv">3</span>, <span class="dt">shape =</span> <span class="dv">21</span>) <span class="op">+</span> <span class="st"> </span><span class="kw">xlim</span>(<span class="dv">0</span>, <span class="dv">1</span>) <span class="op">+</span><span class="st"> </span><span class="kw">ylim</span>(<span class="dv">0</span>, <span class="dv">1</span>) <span class="op">+</span> <span class="st"> </span><span class="kw">facet_wrap</span>(<span class="op">~</span>clone, <span class="dt">nrow =</span> <span class="dv">1</span>) <span class="op">+</span> <span class="st"> </span><span class="kw">scale_fill_viridis</span>(<span class="dt">name =</span> <span class="st">"fraction of</span><span class="ch">\n</span><span class="st">cells assigned"</span>, <span class="dt">limits =</span> <span class="kw">c</span>(<span class="dv">0</span>, <span class="dv">1</span>)) <span class="op">+</span> <span class="st"> </span><span class="kw">scale_shape_manual</span>(<span class="dt">values =</span> <span class="dv">21</span><span class="op">:</span><span class="dv">25</span>) <span class="op">+</span> <span class="st"> </span><span class="kw">xlab</span>(<span class="st">"Estimated clone prevalence (Canopy)"</span>) <span class="op">+</span> <span class="st"> </span><span class="kw">ylab</span>(<span class="st">"Assigned clone fraction (cardelino)"</span>) <span class="op">+</span> <span class="st"> </span><span class="kw">theme</span>(<span class="dt">axis.text =</span> <span class="kw">element_text</span>(<span class="dt">size =</span> <span class="dv">9</span>))</code></pre></div> <pre><code>Joining, by = c("clone", "prev_cardelino", "prev_canopy")</code></pre> <p><img src="figure/clone_prevalences.Rmd/plot-prev-facet-clone-3clones-1.png" width="816" style="display: block; margin: auto;" /></p> <details> <summary><em>Expand here to see past versions of plot-prev-facet-clone-3clones-1.png:</em></summary> <table style="border-collapse:separate; border-spacing:5px;"> <thead> <tr> <th style="text-align:left;"> Version </th> <th style="text-align:left;"> Author </th> <th style="text-align:left;"> Date </th> </tr> </thead> <tbody> <tr> <td style="text-align:left;"> <a href="https://github.com/davismcc/fibroblast-clonality/blob/d2e8b3145e4600ec75d0d0df9ad1e210ecb1bdd3/docs/figure/clone_prevalences.Rmd/plot-prev-facet-clone-3clones-1.png" target="_blank">d2e8b31</a> </td> <td style="text-align:left;"> davismcc </td> <td style="text-align:left;"> 2018-08-19 </td> </tr> </tbody> </table> <p></details></p> <div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r"><span class="kw">ggsave</span>(<span class="st">"figures/clone_prevalences/clone_prev_scatter_facet_clone_no_clone4.png"</span>, <span class="dt">height =</span> <span class="fl">4.5</span>, <span class="dt">width =</span> <span class="fl">8.5</span>) <span class="kw">ggsave</span>(<span class="st">"figures/clone_prevalences/clone_prev_scatter_facet_clone_no_clone4.pdf"</span>, <span class="dt">height =</span> <span class="fl">4.5</span>, <span class="dt">width =</span> <span class="fl">8.5</span>)</code></pre></div> <p>Let us also make a version of the plot above with the line <em>joxm</em> highlighted as this line is used as an example in the paper.</p> <div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r">fits <span class="op">%>%</span> <span class="st"> </span>broom<span class="op">::</span><span class="kw">augment</span>(fit) <span class="op">%>%</span><span class="st"> </span> <span class="st"> </span><span class="kw">inner_join</span>(., df_prev) <span class="op">%>%</span> <span class="st"> </span>dplyr<span class="op">::</span><span class="kw">filter</span>(clone <span class="op">!=</span><span class="st"> "clone4"</span>) <span class="op">%>%</span> <span class="st"> </span>dplyr<span class="op">::</span><span class="kw">mutate</span>(<span class="dt">labs =</span> <span class="kw">ifelse</span>(line <span class="op">==</span><span class="st"> "joxm"</span>, <span class="st">"joxm"</span>, <span class="st">""</span>)) <span class="op">%>%</span> <span class="st"> </span><span class="kw">ggplot</span>(<span class="kw">aes</span>(<span class="dt">x =</span> prev_canopy, <span class="dt">y =</span> prev_cardelino, <span class="dt">fill =</span> prop_assigned)) <span class="op">+</span> <span class="st"> </span><span class="kw">geom_abline</span>(<span class="dt">slope =</span> <span class="dv">1</span>, <span class="dt">intercept =</span> <span class="dv">0</span>, <span class="dt">colour =</span> <span class="st">"gray40"</span>, <span class="dt">linetype =</span> <span class="dv">2</span>) <span class="op">+</span> <span class="st"> </span><span class="kw">geom_ribbon</span>(<span class="kw">aes</span>(<span class="dt">ymin =</span> .fitted <span class="op">-</span><span class="st"> </span><span class="fl">1.645</span> <span class="op">*</span><span class="st"> </span>.se.fit, <span class="dt">ymax =</span> .fitted <span class="op">+</span><span class="st"> </span><span class="fl">1.645</span> <span class="op">*</span><span class="st"> </span>.se.fit), <span class="dt">fill =</span> <span class="st">"gray70"</span>, <span class="dt">alpha =</span> <span class="fl">0.7</span>) <span class="op">+</span> <span class="st"> </span><span class="kw">geom_abline</span>(<span class="kw">aes</span>(<span class="dt">intercept =</span> x0, <span class="dt">slope =</span> x1), <span class="dt">data =</span> dplyr<span class="op">::</span><span class="kw">filter</span>(fits_me, clone <span class="op">!=</span><span class="st"> "clone4"</span>), <span class="dt">colour =</span> <span class="st">"firebrick"</span>, <span class="dt">size =</span> <span class="dv">1</span>) <span class="op">+</span> <span class="st"> </span>ggrepel<span class="op">::</span><span class="kw">geom_label_repel</span>(<span class="kw">aes</span>(<span class="dt">label =</span> labs), <span class="dt">fill =</span> <span class="st">"gray90"</span>, <span class="dt">size =</span> <span class="fl">3.5</span>, <span class="dt">box.padding =</span> <span class="fl">0.1</span>, <span class="dt">label.padding =</span> <span class="fl">0.15</span>) <span class="op">+</span> <span class="st"> </span><span class="kw">geom_point</span>(<span class="dt">size =</span> <span class="dv">3</span>, <span class="dt">shape =</span> <span class="dv">21</span>) <span class="op">+</span> <span class="st"> </span><span class="kw">xlim</span>(<span class="dv">0</span>, <span class="dv">1</span>) <span class="op">+</span><span class="st"> </span><span class="kw">ylim</span>(<span class="dv">0</span>, <span class="dv">1</span>) <span class="op">+</span> <span class="st"> </span><span class="kw">facet_wrap</span>(<span class="op">~</span>clone, <span class="dt">nrow =</span> <span class="dv">1</span>) <span class="op">+</span> <span class="st"> </span><span class="kw">scale_fill_viridis</span>(<span class="dt">name =</span> <span class="st">"fraction of</span><span class="ch">\n</span><span class="st">cells assigned"</span>, <span class="dt">limits =</span> <span class="kw">c</span>(<span class="dv">0</span>, <span class="dv">1</span>)) <span class="op">+</span> <span class="st"> </span><span class="kw">scale_shape_manual</span>(<span class="dt">values =</span> <span class="dv">21</span><span class="op">:</span><span class="dv">25</span>) <span class="op">+</span> <span class="st"> </span><span class="kw">scale_colour_manual</span>(<span class="dt">values =</span> <span class="kw">c</span>(<span class="st">"black"</span>, <span class="st">"firebrick"</span>), <span class="dt">guide =</span> <span class="ot">FALSE</span>) <span class="op">+</span> <span class="st"> </span><span class="kw">xlab</span>(<span class="st">"Estimated clone prevalence (Canopy)"</span>) <span class="op">+</span> <span class="st"> </span><span class="kw">ylab</span>(<span class="st">"Assigned clone fraction (cardelino)"</span>) <span class="op">+</span> <span class="st"> </span><span class="kw">theme_cowplot</span>(<span class="dt">font_size =</span> <span class="dv">17</span>)</code></pre></div> <pre><code>Joining, by = c("clone", "prev_cardelino", "prev_canopy")</code></pre> <p><img src="figure/clone_prevalences.Rmd/plot-prev-facet-clone-3clones-joxm-1.png" width="816" style="display: block; margin: auto;" /></p> <details> <summary><em>Expand here to see past versions of plot-prev-facet-clone-3clones-joxm-1.png:</em></summary> <table style="border-collapse:separate; border-spacing:5px;"> <thead> <tr> <th style="text-align:left;"> Version </th> <th style="text-align:left;"> Author </th> <th style="text-align:left;"> Date </th> </tr> </thead> <tbody> <tr> <td style="text-align:left;"> <a href="https://github.com/davismcc/fibroblast-clonality/blob/f0ed980029a115234bc2edff312e5e52056d4eed/docs/figure/clone_prevalences.Rmd/plot-prev-facet-clone-3clones-joxm-1.png" target="_blank">f0ed980</a> </td> <td style="text-align:left;"> davismcc </td> <td style="text-align:left;"> 2018-08-31 </td> </tr> <tr> <td style="text-align:left;"> <a href="https://github.com/davismcc/fibroblast-clonality/blob/ca3438f9274dbc7adf4aacc25b0fb017bc2d41fe/docs/figure/clone_prevalences.Rmd/plot-prev-facet-clone-3clones-joxm-1.png" target="_blank">ca3438f</a> </td> <td style="text-align:left;"> davismcc </td> <td style="text-align:left;"> 2018-08-29 </td> </tr> </tbody> </table> <p></details></p> <div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r"><span class="kw">ggsave</span>(<span class="st">"figures/clone_prevalences/clone_prev_scatter_facet_clone_no_clone4_joxmlabel.png"</span>, <span class="dt">height =</span> <span class="fl">4.5</span>, <span class="dt">width =</span> <span class="fl">8.5</span>) <span class="kw">ggsave</span>(<span class="st">"figures/clone_prevalences/clone_prev_scatter_facet_clone_no_clone4_joxmlabel.pdf"</span>, <span class="dt">height =</span> <span class="fl">4.5</span>, <span class="dt">width =</span> <span class="fl">8.5</span>) <span class="kw">ggsave</span>(<span class="st">"figures/clone_prevalences/clone_prev_scatter_facet_clone_no_clone4_joxmlabel_wide.png"</span>, <span class="dt">height =</span> <span class="fl">4.5</span>, <span class="dt">width =</span> <span class="fl">13.5</span>) <span class="kw">ggsave</span>(<span class="st">"figures/clone_prevalences/clone_prev_scatter_facet_clone_no_clone4_joxmlabel_wide.pdf"</span>, <span class="dt">height =</span> <span class="fl">4.5</span>, <span class="dt">width =</span> <span class="fl">13.5</span>)</code></pre></div> <p>Also look at what happens if we filter out lines that have fewer than 75% of cells assigned (25 lines).</p> <div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r">df_prev <span class="op">%>%</span> <span class="st"> </span>dplyr<span class="op">::</span><span class="kw">filter</span>(clone <span class="op">!=</span><span class="st"> "clone4"</span>, prop_assigned <span class="op">></span><span class="st"> </span><span class="fl">0.75</span>) <span class="op">%>%</span> <span class="st"> </span><span class="kw">ggplot</span>(<span class="kw">aes</span>(<span class="dt">x =</span> prev_canopy, <span class="dt">y =</span> prev_cardelino, <span class="dt">shape =</span> clone, <span class="dt">fill =</span> prop_assigned)) <span class="op">+</span> <span class="st"> </span><span class="kw">geom_abline</span>(<span class="dt">slope =</span> <span class="dv">1</span>, <span class="dt">intercept =</span> <span class="dv">0</span>, <span class="dt">colour =</span> <span class="st">"gray40"</span>, <span class="dt">linetype =</span> <span class="dv">2</span>) <span class="op">+</span> <span class="st"> </span><span class="kw">geom_smooth</span>(<span class="kw">aes</span>(<span class="dt">group =</span> <span class="dv">1</span>), <span class="dt">method =</span> <span class="st">"lm"</span>, <span class="dt">colour =</span> <span class="st">"firebrick"</span>) <span class="op">+</span> <span class="st"> </span><span class="kw">geom_point</span>(<span class="dt">size =</span> <span class="dv">3</span>) <span class="op">+</span> <span class="st"> </span><span class="kw">xlim</span>(<span class="dv">0</span>, <span class="dv">1</span>) <span class="op">+</span><span class="st"> </span><span class="kw">ylim</span>(<span class="dv">0</span>, <span class="dv">1</span>) <span class="op">+</span> <span class="st"> </span><span class="kw">facet_wrap</span>(<span class="op">~</span>clone, <span class="dt">nrow =</span> <span class="dv">1</span>) <span class="op">+</span> <span class="st"> </span><span class="kw">scale_fill_viridis</span>(<span class="dt">name =</span> <span class="st">"fraction of</span><span class="ch">\n</span><span class="st">cells assigned"</span>, <span class="dt">limits =</span> <span class="kw">c</span>(<span class="dv">0</span>, <span class="dv">1</span>)) <span class="op">+</span> <span class="st"> </span><span class="kw">scale_shape_manual</span>(<span class="dt">values =</span> <span class="dv">21</span><span class="op">:</span><span class="dv">25</span>) <span class="op">+</span> <span class="st"> </span><span class="kw">xlab</span>(<span class="st">"Estimated clone prevalence (Canopy)"</span>) <span class="op">+</span> <span class="st"> </span><span class="kw">ylab</span>(<span class="st">"Assigned clone fraction (cardelino)"</span>)</code></pre></div> <p><img src="figure/clone_prevalences.Rmd/plot-prev-facet-clone-3clones-linefilt-1.png" width="1008" style="display: block; margin: auto;" /></p> <details> <summary><em>Expand here to see past versions of plot-prev-facet-clone-3clones-linefilt-1.png:</em></summary> <table style="border-collapse:separate; border-spacing:5px;"> <thead> <tr> <th style="text-align:left;"> Version </th> <th style="text-align:left;"> Author </th> <th style="text-align:left;"> Date </th> </tr> </thead> <tbody> <tr> <td style="text-align:left;"> <a href="https://github.com/davismcc/fibroblast-clonality/blob/d2e8b3145e4600ec75d0d0df9ad1e210ecb1bdd3/docs/figure/clone_prevalences.Rmd/plot-prev-facet-clone-3clones-linefilt-1.png" target="_blank">d2e8b31</a> </td> <td style="text-align:left;"> davismcc </td> <td style="text-align:left;"> 2018-08-19 </td> </tr> </tbody> </table> <p></details></p> <div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r"><span class="kw">ggsave</span>(<span class="st">"figures/clone_prevalences/clone_prev_scatter_facet_clone_no_clone4_75pctassigned.png"</span>, <span class="dt">height =</span> <span class="fl">4.5</span>, <span class="dt">width =</span> <span class="fl">10.5</span>) <span class="kw">ggsave</span>(<span class="st">"figures/clone_prevalences/clone_prev_scatter_facet_clone_no_clone4_75pctassigned.pdf"</span>, <span class="dt">height =</span> <span class="fl">4.5</span>, <span class="dt">width =</span> <span class="fl">10.5</span>)</code></pre></div> </div> <div id="session-information" class="section level2"> <h2>Session information</h2> <div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r">devtools<span class="op">::</span><span class="kw">session_info</span>()</code></pre></div> <pre><code>Session info -------------------------------------------------------------</code></pre> <pre><code> setting value version R version 3.5.1 (2018-07-02) system x86_64, darwin15.6.0 ui X11 language (EN) collate en_GB.UTF-8 tz Europe/London date 2018-09-02 </code></pre> <pre><code>Packages -----------------------------------------------------------------</code></pre> <pre><code> package * version date source assertthat 0.2.0 2017-04-11 CRAN (R 3.5.0) backports 1.1.2 2017-12-13 CRAN (R 3.5.0) base * 3.5.1 2018-07-05 local bindr 0.1.1 2018-03-13 CRAN (R 3.5.0) bindrcpp * 0.2.2 2018-03-29 CRAN (R 3.5.0) broom 0.5.0 2018-07-17 CRAN (R 3.5.0) cellranger 1.1.0 2016-07-27 CRAN (R 3.5.0) cli 1.0.0 2017-11-05 CRAN (R 3.5.0) colorspace 1.3-2 2016-12-14 CRAN (R 3.5.0) compiler 3.5.1 2018-07-05 local cowplot * 0.9.3 2018-07-15 CRAN (R 3.5.0) crayon 1.3.4 2017-09-16 CRAN (R 3.5.0) datasets * 3.5.1 2018-07-05 local devtools 1.13.6 2018-06-27 CRAN (R 3.5.0) digest 0.6.16 2018-08-22 CRAN (R 3.5.0) dplyr * 0.7.6 2018-06-29 CRAN (R 3.5.1) evaluate 0.11 2018-07-17 CRAN (R 3.5.0) forcats * 0.3.0 2018-02-19 CRAN (R 3.5.0) ggplot2 * 3.0.0 2018-07-03 CRAN (R 3.5.0) ggrepel 0.8.0 2018-05-09 CRAN (R 3.5.0) git2r 0.23.0 2018-07-17 CRAN (R 3.5.0) glue 1.3.0 2018-07-17 CRAN (R 3.5.0) graphics * 3.5.1 2018-07-05 local grDevices * 3.5.1 2018-07-05 local grid 3.5.1 2018-07-05 local gridExtra 2.3 2017-09-09 CRAN (R 3.5.0) gtable 0.2.0 2016-02-26 CRAN (R 3.5.0) haven 1.1.2 2018-06-27 CRAN (R 3.5.0) hms 0.4.2 2018-03-10 CRAN (R 3.5.0) htmltools 0.3.6 2017-04-28 CRAN (R 3.5.0) httr 1.3.1 2017-08-20 CRAN (R 3.5.0) jsonlite 1.5 2017-06-01 CRAN (R 3.5.0) knitr 1.20 2018-02-20 CRAN (R 3.5.0) labeling 0.3 2014-08-23 CRAN (R 3.5.0) lattice 0.20-35 2017-03-25 CRAN (R 3.5.1) lazyeval 0.2.1 2017-10-29 CRAN (R 3.5.0) lubridate 1.7.4 2018-04-11 CRAN (R 3.5.0) magrittr 1.5 2014-11-22 CRAN (R 3.5.0) memoise 1.1.0 2017-04-21 CRAN (R 3.5.0) methods * 3.5.1 2018-07-05 local modelr 0.1.2 2018-05-11 CRAN (R 3.5.0) munsell 0.5.0 2018-06-12 CRAN (R 3.5.0) nlme 3.1-137 2018-04-07 CRAN (R 3.5.1) pillar 1.3.0 2018-07-14 CRAN (R 3.5.0) pkgconfig 2.0.2 2018-08-16 CRAN (R 3.5.0) plyr 1.8.4 2016-06-08 CRAN (R 3.5.0) purrr * 0.2.5 2018-05-29 CRAN (R 3.5.0) R.methodsS3 1.7.1 2016-02-16 CRAN (R 3.5.0) R.oo 1.22.0 2018-04-22 CRAN (R 3.5.0) R.utils 2.7.0 2018-08-27 CRAN (R 3.5.0) R6 2.2.2 2017-06-17 CRAN (R 3.5.0) Rcpp 0.12.18 2018-07-23 CRAN (R 3.5.0) readr * 1.1.1 2017-05-16 CRAN (R 3.5.0) readxl 1.1.0 2018-04-20 CRAN (R 3.5.0) rlang 0.2.2 2018-08-16 CRAN (R 3.5.0) rmarkdown 1.10 2018-06-11 CRAN (R 3.5.0) rprojroot 1.3-2 2018-01-03 CRAN (R 3.5.0) rstudioapi 0.7 2017-09-07 CRAN (R 3.5.0) rvest 0.3.2 2016-06-17 CRAN (R 3.5.0) scales 1.0.0 2018-08-09 CRAN (R 3.5.0) stats * 3.5.1 2018-07-05 local stringi 1.2.4 2018-07-20 CRAN (R 3.5.0) stringr * 1.3.1 2018-05-10 CRAN (R 3.5.0) tibble * 1.4.2 2018-01-22 CRAN (R 3.5.0) tidyr * 0.8.1 2018-05-18 CRAN (R 3.5.0) tidyselect 0.2.4 2018-02-26 CRAN (R 3.5.0) tidyverse * 1.2.1 2017-11-14 CRAN (R 3.5.0) tools 3.5.1 2018-07-05 local utils * 3.5.1 2018-07-05 local viridis * 0.5.1 2018-03-29 CRAN (R 3.5.0) viridisLite * 0.3.0 2018-02-01 CRAN (R 3.5.0) whisker 0.3-2 2013-04-28 CRAN (R 3.5.0) withr 2.1.2 2018-03-15 CRAN (R 3.5.0) workflowr 1.1.1 2018-07-06 CRAN (R 3.5.0) xml2 1.2.0 2018-01-24 CRAN (R 3.5.0) yaml 2.2.0 2018-07-25 CRAN (R 3.5.1)</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. 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