1. singleCellTK
  2. Commit 8a7dfffb5691f575acecaae830d53d4c3a1b1cf9
Browse code

New version 2.7.3

Yichen Wang authored on 25/10/2022 20:23:57
Showing 312 changed files
DESCRIPTION
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 Package: singleCellTK
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 Type: Package
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 Title: Comprehensive and Interactive Analysis of Single Cell RNA-Seq Data
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-Version: 2.7.2
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+Version: 2.7.3
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 Authors@R: c(person(given="Yichen", family="Wang", email="wangych@bu.edu", role=c("aut", "cre"),
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                     comment = c(ORCID = "0000-0003-4347-5199")),
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              person(given="Irzam", family="Sarfraz", email="isarfraz@bu.edu", role=c("aut"),
NEWS.md
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+Changes in Version 2.7.3 (2022-10-25)
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+================================================================================
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+* Fixed bugs related to dependency updates
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+
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 Changes in Version 2.7.2 (2022-10-19)
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 ================================================================================
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 * Deprecated `findMarkerDiffExp()`, `findMarkerTopTable()` and `plotMarkerDiffExp()`, which are replaced by `runFindMarker()`, `getFindMarkerTopTable()` and `plotFindMarkerHeatmap()`, respectively
docs/404.html
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       </button>
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       <span class="navbar-brand">
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         <a class="navbar-link" href="index.html">singleCellTK</a>
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-        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="">2.7.2</span>
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+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="">2.7.3</span>
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       </span>
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     </div>
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docs/LICENSE-text.html
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       </button>
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       <span class="navbar-brand">
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         <a class="navbar-link" href="index.html">singleCellTK</a>
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-        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="">2.7.2</span>
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+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="">2.7.3</span>
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       </span>
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     </div>
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docs/articles/01_import_and_qc_tutorial.html
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       </button>
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       <span class="navbar-brand">
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         <a class="navbar-link" href="../index.html">singleCellTK</a>
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-        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="">2.7.2</span>
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+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="">2.7.3</span>
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       </span>
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     </div>
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       </button>
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         <a class="navbar-link" href="../index.html">singleCellTK</a>
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-        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="">2.7.2</span>
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       </span>
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     </div>
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@@ -911,13 +911,13 @@ enriched in an annotated cell type <a href="#cell-type-labeling">using
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 SingleR</a>.</p>
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 <div class="sourceCode" id="cb20"><pre class="downlit sourceCode r">
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 <code class="sourceCode R"><span><span class="co"># Returns a vector where TRUE for a type of NK cell</span></span>
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-<span><span class="va">isNKCell</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/startsWith.html" class="external-link">startsWith</a></span><span class="op">(</span><span class="fu">colData</span><span class="op">(</span><span class="va">sce</span><span class="op">)</span><span class="op">$</span><span class="va">SingleR_hpca_fine_pruned.labels</span>, <span class="st">"NK_cell"</span><span class="op">)</span></span>
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+<span><span class="va">isNKCell</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/startsWith.html" class="external-link">startsWith</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/pkg/SummarizedExperiment/man/SummarizedExperiment-class.html" class="external-link">colData</a></span><span class="op">(</span><span class="va">sce</span><span class="op">)</span><span class="op">$</span><span class="va">SingleR_hpca_fine_pruned.labels</span>, <span class="st">"NK_cell"</span><span class="op">)</span></span>
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 <span><span class="co"># Returns a vector where TRUE for a type of T cell</span></span>
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+<span><span class="va">isTCell</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/startsWith.html" class="external-link">startsWith</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/pkg/SummarizedExperiment/man/SummarizedExperiment-class.html" class="external-link">colData</a></span><span class="op">(</span><span class="va">sce</span><span class="op">)</span><span class="op">$</span><span class="va">SingleR_hpca_fine_pruned.labels</span>, <span class="st">"T_cell"</span><span class="op">)</span></span>
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 <span><span class="co"># Make up a variable with only categories of "NK_cell", "T_cell" and "Other".</span></span>
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-<span><span class="fu">colData</span><span class="op">(</span><span class="va">sce</span><span class="op">)</span><span class="op">$</span><span class="va">cell_type</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/ifelse.html" class="external-link">ifelse</a></span><span class="op">(</span><span class="va">isNKCell</span>, <span class="st">"NK_cell"</span>, <span class="st">"Other"</span><span class="op">)</span></span>
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-<span><span class="fu">colData</span><span class="op">(</span><span class="va">sce</span><span class="op">)</span><span class="op">$</span><span class="va">cell_type</span><span class="op">[</span><span class="va">isTCell</span><span class="op">]</span> <span class="op">&lt;-</span> <span class="st">"T_cell"</span></span>
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-<span><span class="fu">colData</span><span class="op">(</span><span class="va">sce</span><span class="op">)</span><span class="op">$</span><span class="va">cell_type</span><span class="op">[</span><span class="fu"><a href="https://rdrr.io/r/base/NA.html" class="external-link">is.na</a></span><span class="op">(</span><span class="fu">colData</span><span class="op">(</span><span class="va">sce</span><span class="op">)</span><span class="op">$</span><span class="va">cell_type</span><span class="op">)</span><span class="op">]</span> <span class="op">&lt;-</span> <span class="st">"Other"</span></span>
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+<span><span class="fu"><a href="https://rdrr.io/pkg/SummarizedExperiment/man/SummarizedExperiment-class.html" class="external-link">colData</a></span><span class="op">(</span><span class="va">sce</span><span class="op">)</span><span class="op">$</span><span class="va">cell_type</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/ifelse.html" class="external-link">ifelse</a></span><span class="op">(</span><span class="va">isNKCell</span>, <span class="st">"NK_cell"</span>, <span class="st">"Other"</span><span class="op">)</span></span>
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+<span><span class="fu"><a href="https://rdrr.io/pkg/SummarizedExperiment/man/SummarizedExperiment-class.html" class="external-link">colData</a></span><span class="op">(</span><span class="va">sce</span><span class="op">)</span><span class="op">$</span><span class="va">cell_type</span><span class="op">[</span><span class="va">isTCell</span><span class="op">]</span> <span class="op">&lt;-</span> <span class="st">"T_cell"</span></span>
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+<span><span class="fu"><a href="https://rdrr.io/pkg/SummarizedExperiment/man/SummarizedExperiment-class.html" class="external-link">colData</a></span><span class="op">(</span><span class="va">sce</span><span class="op">)</span><span class="op">$</span><span class="va">cell_type</span><span class="op">[</span><span class="fu"><a href="https://rdrr.io/r/base/NA.html" class="external-link">is.na</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/pkg/SummarizedExperiment/man/SummarizedExperiment-class.html" class="external-link">colData</a></span><span class="op">(</span><span class="va">sce</span><span class="op">)</span><span class="op">$</span><span class="va">cell_type</span><span class="op">)</span><span class="op">]</span> <span class="op">&lt;-</span> <span class="st">"Other"</span></span>
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 <span><span class="co"># Run differential abundance test</span></span>
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 <span><span class="va">sce</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/diffAbundanceFET.html">diffAbundanceFET</a></span><span class="op">(</span><span class="va">sce</span>, cluster <span class="op">=</span> <span class="st">"cluster"</span>, </span>
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 <span>                        variable <span class="op">=</span> <span class="st">"cell_type"</span>, </span>
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-        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="">2.7.2</span>
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 <span><span class="co">## dim: 800 800 </span></span>
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 <span><span class="co">## metadata(1): assayType</span></span>
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 <span><span class="co">## assays(2): counts logcounts</span></span>
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-<span><span class="co">## rownames(800): RNF169 FAM24B ... RASGRP2 RAPGEF6</span></span>
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 <span><span class="co">## rowData names(5): rownames ENSEMBL_ID Symbol_TENx Symbol expPerc</span></span>
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 <span><span class="co">## colData names(14): rownames Sample ... sample sizeFactor</span></span>
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 <span><span class="co">## reducedDimNames(0):</span></span>
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 <span><span class="co">## mainExpName: NULL</span></span>
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 <span><span class="co">## dim: 800 800 </span></span>
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 <span><span class="co">## metadata(2): assayType batchCorr</span></span>
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 <span><span class="co">## assays(3): counts logcounts LIMMA</span></span>
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 <span><span class="co">## colData names(14): rownames Sample ... sample sizeFactor</span></span>
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 <span><span class="co">## mainExpName: NULL</span></span>
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 name and see the reference page of this function.</p>
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 <div class="sourceCode" id="cb2"><pre class="downlit sourceCode r">
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 <code class="sourceCode R"><span><span class="va">sce</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/runSingleR.html">runSingleR</a></span><span class="op">(</span>inSCE <span class="op">=</span> <span class="va">sce</span>, useAssay <span class="op">=</span> <span class="st">"logcounts"</span>, useBltinRef <span class="op">=</span> <span class="st">"hpca"</span>, level <span class="op">=</span> <span class="st">"main"</span>, featureType <span class="op">=</span> <span class="st">"symbol"</span><span class="op">)</span></span></code></pre></div>
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 slot with the same prefix as
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 <code>"score"</code>, <code>"labels"</code>, <code>"delta.next"</code>
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@@ -406,7 +406,7 @@ wrapped in a <a href="https://rdrr.io/bioc/SingleCellExperiment/man/SingleCellEx
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 object. Refer to argument <code>useSCERef</code> and
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 <code>labelColName</code>. Additionally, the labeling can also be done
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 on cluster label if users have already performed clustering on their
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 to argument <code>labelByCluster</code>.</p>
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 <p><strong>Visualization</strong></p>
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 <p>Users can choose to visualize the labeling result on a scatter plot.
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@@ -334,12 +334,12 @@ install and set up docker in <a href="https://docs.docker.com/desktop/windows/in
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 <h4 id="running-sctk-qc-pipeline-using-docker-image">Running SCTK-QC pipeline using docker image<a class="anchor" aria-label="anchor" href="#running-sctk-qc-pipeline-using-docker-image"></a>
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 </h4>
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 <p>The Docker image can be obtained by running:</p>
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-<pre><code>docker pull campbio/sctk_qc:2.7.1</code></pre>
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+<pre><code>docker pull campbio/sctk_qc:2.7.3</code></pre>
338 338 
 <p>The usage of each argument is the same as running command line
339 339 
 analysis. Here is an example code to perform QC on CellRangerV3 data
340 340 
 with SCTK docker:</p>
341 341 
 <pre><code>docker run --rm -v /path/to/data:/SCTK_docker \
342 
-  -it campbio/sctk_qc:2.7.1 \
342 
+  -it campbio/sctk_qc:2.7.3 \
343 343 
   -b /SCTK_docker/cellranger_folder \
344 344 
   -P CellRangerV3 \
345 345 
   -s SampleName \
... ... 
@@ -366,7 +366,7 @@ parameters.</p>
366 366 
 before can install it following the instruction <a href="https://sylabs.io/guides/3.1/user-guide/installation.html" class="external-link">here</a>.
367 367 
 The Singularity image for SCTK-QC can be easily built using Docker Hub
368 368 
 as a source:</p>
369 
-<pre><code>singularity pull docker://campbio/sctk_qc:2.7.1</code></pre>
369 
+<pre><code>singularity pull docker://campbio/sctk_qc:2.7.3</code></pre>
370 370 
 <p>The usage of singleCellTK Singularity image is very similar to that
371 371 
 of Docker. In Singularity 3.0+, the mount volume is <a href="https://sylabs.io/guides/3.1/user-guide/bind_paths_and_mounts.html" class="external-link">automatically
372 372 
 overlaid</a>.</p>
... ... 
@@ -385,7 +385,7 @@ mount volume, which is the path that contains the dataset and will be
385 385 
 used to store the output of QC pipeline. The example is shown as
386 386 
 below:</p>
387 387 
 <pre><code>singularity run --home=/PathToSanitizedHome \
388 
-  --bind /PathToData:/data sctk_qc_2.7.1.sif \
388 
+  --bind /PathToData:/data sctk_qc_2.7.3.sif \
389 389 
   -b /SCTK_docker/cellranger_folder \
390 390 
   -P CellRangerV3 \
391 391 
   -s SampleName \
... ... 
@@ -415,7 +415,7 @@ shown below:</p>
415 415 
 #$ -l cpu_arch=broadwell|haswell|skylake|cascadelake
416 416
417 417 
 singularity run --home=/PathToSanitizedHome  ### this also works for 'docker run'
418 
-  --bind /PathToData:/data sctk_qc_2.7.1.sif \
418 
+  --bind /PathToData:/data sctk_qc_2.7.3.sif \
419 419 
   -b /SCTK_docker/cellranger_folder \
420 420 
   -P CellRangerV3 \
421 421 
   -s SampleName \
docs/articles/cnsl_cellqc.html
History View file @ 8a7dfffb5
... ... 
@@ -34,7 +34,7 @@
34 34 
       </button>
35 35 
       <span class="navbar-brand">
36 36 
         <a class="navbar-link" href="../index.html">singleCellTK</a>
37 
-        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="">2.7.2</span>
37 
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="">2.7.3</span>
38 38 
       </span>
39 39 
     </div>
40 40
... ... 
@@ -577,13 +577,13 @@ pbmc3k
577 577 
 Singlet
578 578 
 </td>
579 579 
 <td style="text-align:right;">
580 
-0.1210292
580 
+0.1008018
581 581 
 </td>
582 582 
 <td style="text-align:right;">
583 
-0.7837616
583 
+0.7755992
584 584 
 </td>
585 585 
 <td style="text-align:right;">
586 
-0.0446885
586 
+0.0485004
587 587 
 </td>
588 588 
 <td style="text-align:right;">
589 589 
 0.0138889
... ... 
@@ -708,13 +708,13 @@ pbmc3k
708 708 
 Singlet
709 709 
 </td>
710 710 
 <td style="text-align:right;">
711 
-0.3434467
711 
+0.0802065
712 712 
 </td>
713 713 
 <td style="text-align:right;">
714 
-0.5700511
714 
+0.5726999
715 715 
 </td>
716 716 
 <td style="text-align:right;">
717 
-0.1495769
717 
+0.0071068
718 718 
 </td>
719 719 
 <td style="text-align:right;">
720 720 
 0.1527778
... ... 
@@ -937,8 +937,8 @@ parameter to <code>FALSE</code>.</p>
937 937 
 <span><span class="co">## Median features detected                                817.0000  716.0000</span></span>
938 938 
 <span><span class="co">## Scrublet - Number of doublets                             0.0000    0.0000</span></span>
939 939 
 <span><span class="co">## Scrublet - Percentage of doublets                         0.0000    0.0000</span></span>
940 
-<span><span class="co">## scDblFinder - Number of doublets                        126.0000  304.0000</span></span>
941 
-<span><span class="co">## scDblFinder - Percentage of doublets                      4.6700    5.6100</span></span>
940 
+<span><span class="co">## scDblFinder - Number of doublets                        108.0000  302.0000</span></span>
941 
+<span><span class="co">## scDblFinder - Percentage of doublets                      4.0000    5.5700</span></span>
942 942 
 <span><span class="co">## DoubletFinder - Number of doublets, Resolution 1.5      202.0000  406.0000</span></span>
943 943 
 <span><span class="co">## DoubletFinder - Percentage of doublets, Resolution 1.5    7.4800    7.4900</span></span>
944 944 
 <span><span class="co">## CXDS - Number of doublets                               132.0000  294.0000</span></span>
... ... 
@@ -957,8 +957,8 @@ parameter to <code>FALSE</code>.</p>
957 957 
 <span><span class="co">## Median features detected                                  750.0000</span></span>
958 958 
 <span><span class="co">## Scrublet - Number of doublets                               0.0000</span></span>
959 959 
 <span><span class="co">## Scrublet - Percentage of doublets                           0.0000</span></span>
960 
-<span><span class="co">## scDblFinder - Number of doublets                          430.0000</span></span>
961 
-<span><span class="co">## scDblFinder - Percentage of doublets                        5.3000</span></span>
960 
+<span><span class="co">## scDblFinder - Number of doublets                          410.0000</span></span>
961 
+<span><span class="co">## scDblFinder - Percentage of doublets                        5.0500</span></span>
962 962 
 <span><span class="co">## DoubletFinder - Number of doublets, Resolution 1.5        608.0000</span></span>
963 963 
 <span><span class="co">## DoubletFinder - Percentage of doublets, Resolution 1.5      7.4900</span></span>
964 964 
 <span><span class="co">## CXDS - Number of doublets                                 426.0000</span></span>
... ... 
@@ -1456,128 +1456,128 @@ documentation</a>.</p>
1456 1456 
 <span><span class="co">## [8] base     </span></span>
1457 1457 
 <span><span class="co">## </span></span>
1458 1458 
 <span><span class="co">## other attached packages:</span></span>
1459 
-<span><span class="co">##  [1] TENxPBMCData_1.14.0         HDF5Array_1.24.2           </span></span>
1460 
-<span><span class="co">##  [3] rhdf5_2.40.0                dplyr_1.0.10               </span></span>
1461 
-<span><span class="co">##  [5] singleCellTK_2.7.1          DelayedArray_0.22.0        </span></span>
1462 
-<span><span class="co">##  [7] Matrix_1.5-1                SingleCellExperiment_1.18.0</span></span>
1463 
-<span><span class="co">##  [9] SummarizedExperiment_1.26.1 Biobase_2.56.0             </span></span>
1464 
-<span><span class="co">## [11] GenomicRanges_1.48.0        GenomeInfoDb_1.32.4        </span></span>
1465 
-<span><span class="co">## [13] IRanges_2.30.1              S4Vectors_0.34.0           </span></span>
1466 
-<span><span class="co">## [15] BiocGenerics_0.42.0         MatrixGenerics_1.8.1       </span></span>
1459 
+<span><span class="co">##  [1] TENxPBMCData_1.15.0         HDF5Array_1.25.2           </span></span>
1460 
+<span><span class="co">##  [3] rhdf5_2.41.1                dplyr_1.0.10               </span></span>
1461 
+<span><span class="co">##  [5] singleCellTK_2.7.3          DelayedArray_0.23.2        </span></span>
1462 
+<span><span class="co">##  [7] Matrix_1.5-1                SingleCellExperiment_1.19.1</span></span>
1463 
+<span><span class="co">##  [9] SummarizedExperiment_1.27.3 Biobase_2.57.1             </span></span>
1464 
+<span><span class="co">## [11] GenomicRanges_1.49.1        GenomeInfoDb_1.33.15       </span></span>
1465 
+<span><span class="co">## [13] IRanges_2.31.2              S4Vectors_0.35.4           </span></span>
1466 
+<span><span class="co">## [15] BiocGenerics_0.43.4         MatrixGenerics_1.9.1       </span></span>
1467 1467 
 <span><span class="co">## [17] matrixStats_0.62.0         </span></span>
1468 1468 
 <span><span class="co">## </span></span>
1469 1469 
 <span><span class="co">## loaded via a namespace (and not attached):</span></span>
1470 1470 
 <span><span class="co">##   [1] rsvd_1.0.5                    svglite_2.1.0                </span></span>
1471 1471 
 <span><span class="co">##   [3] ica_1.0-3                     assertive.properties_0.0-5   </span></span>
1472 
-<span><span class="co">##   [5] Rsamtools_2.12.0              foreach_1.5.2                </span></span>
1472 
+<span><span class="co">##   [5] Rsamtools_2.13.4              foreach_1.5.2                </span></span>
1473 1473 
 <span><span class="co">##   [7] lmtest_0.9-40                 rprojroot_2.0.3              </span></span>
1474 
-<span><span class="co">##   [9] crayon_1.5.1                  spatstat.core_2.4-4          </span></span>
1475 
-<span><span class="co">##  [11] MASS_7.3-57                   rhdf5filters_1.8.0           </span></span>
1476 
-<span><span class="co">##  [13] nlme_3.1-157                  rlang_1.0.5                  </span></span>
1477 
-<span><span class="co">##  [15] XVector_0.36.0                ROCR_1.0-11                  </span></span>
1478 
-<span><span class="co">##  [17] irlba_2.3.5                   SoupX_1.6.1                  </span></span>
1479 
-<span><span class="co">##  [19] limma_3.52.3                  scater_1.24.0                </span></span>
1474 
+<span><span class="co">##   [9] crayon_1.5.2                  spatstat.core_2.4-4          </span></span>
1475 
+<span><span class="co">##  [11] MASS_7.3-58.1                 rhdf5filters_1.9.0           </span></span>
1476 
+<span><span class="co">##  [13] nlme_3.1-160                  rlang_1.0.6                  </span></span>
1477 
+<span><span class="co">##  [15] XVector_0.37.1                ROCR_1.0-11                  </span></span>
1478 
+<span><span class="co">##  [17] irlba_2.3.5.1                 SoupX_1.6.1                  </span></span>
1479 
+<span><span class="co">##  [19] limma_3.53.10                 scater_1.25.7                </span></span>
1480 1480 
 <span><span class="co">##  [21] filelock_1.0.2                xgboost_1.6.0.1              </span></span>
1481 
-<span><span class="co">##  [23] BiocParallel_1.30.3           rjson_0.2.21                 </span></span>
1481 
+<span><span class="co">##  [23] BiocParallel_1.31.14          rjson_0.2.21                 </span></span>
1482 1482 
 <span><span class="co">##  [25] bit64_4.0.5                   glue_1.6.2                   </span></span>
1483 
-<span><span class="co">##  [27] scDblFinder_1.10.0            sctransform_0.3.5            </span></span>
1483 
+<span><span class="co">##  [27] scDblFinder_1.11.3            sctransform_0.3.5            </span></span>
1484 1484 
 <span><span class="co">##  [29] parallel_4.2.1                vipor_0.4.5                  </span></span>
1485 
-<span><span class="co">##  [31] spatstat.sparse_2.1-1         AnnotationDbi_1.58.0         </span></span>
1486 
-<span><span class="co">##  [33] dotCall64_1.0-1               spatstat.geom_2.4-0          </span></span>
1487 
-<span><span class="co">##  [35] tidyselect_1.1.2              SeuratObject_4.1.2           </span></span>
1488 
-<span><span class="co">##  [37] fitdistrplus_1.1-8            XML_3.99-0.10                </span></span>
1485 
+<span><span class="co">##  [31] spatstat.sparse_3.0-0         AnnotationDbi_1.59.1         </span></span>
1486 
+<span><span class="co">##  [33] dotCall64_1.0-2               spatstat.geom_3.0-3          </span></span>
1487 
+<span><span class="co">##  [35] tidyselect_1.2.0              SeuratObject_4.1.2           </span></span>
1488 
+<span><span class="co">##  [37] fitdistrplus_1.1-8            XML_3.99-0.11                </span></span>
1489 1489 
 <span><span class="co">##  [39] tidyr_1.2.1                   assertive.types_0.0-3        </span></span>
1490 
-<span><span class="co">##  [41] zoo_1.8-11                    GenomicAlignments_1.32.1     </span></span>
1490 
+<span><span class="co">##  [41] zoo_1.8-11                    GenomicAlignments_1.33.1     </span></span>
1491 1491 
 <span><span class="co">##  [43] xtable_1.8-4                  magrittr_2.0.3               </span></span>
1492 
-<span><span class="co">##  [45] evaluate_0.16                 ggplot2_3.3.6                </span></span>
1493 
-<span><span class="co">##  [47] scuttle_1.6.3                 cli_3.4.0                    </span></span>
1494 
-<span><span class="co">##  [49] zlibbioc_1.42.0               dbscan_1.1-10                </span></span>
1492 
+<span><span class="co">##  [45] evaluate_0.17                 ggplot2_3.3.6                </span></span>
1493 
+<span><span class="co">##  [47] scuttle_1.7.4                 cli_3.4.1                    </span></span>
1494 
+<span><span class="co">##  [49] zlibbioc_1.43.0               dbscan_1.1-10                </span></span>
1495 1495 
 <span><span class="co">##  [51] rstudioapi_0.14               miniUI_0.1.1.1               </span></span>
1496 1496 
 <span><span class="co">##  [53] sp_1.5-0                      bslib_0.4.0                  </span></span>
1497 
-<span><span class="co">##  [55] rpart_4.1.16                  RcppEigen_0.3.3.9.2          </span></span>
1497 
+<span><span class="co">##  [55] rpart_4.1.19                  RcppEigen_0.3.3.9.2          </span></span>
1498 1498 
 <span><span class="co">##  [57] maps_3.4.0                    fields_14.1                  </span></span>
1499 
-<span><span class="co">##  [59] shiny_1.7.2                   BiocSingular_1.12.0          </span></span>
1500 
-<span><span class="co">##  [61] xfun_0.33                     cluster_2.1.3                </span></span>
1501 
-<span><span class="co">##  [63] KEGGREST_1.36.3               tibble_3.1.8                 </span></span>
1502 
-<span><span class="co">##  [65] interactiveDisplayBase_1.34.0 ggrepel_0.9.1                </span></span>
1503 
-<span><span class="co">##  [67] celda_1.12.0                  listenv_0.8.0                </span></span>
1504 
-<span><span class="co">##  [69] Biostrings_2.64.1             png_0.1-7                    </span></span>
1499 
+<span><span class="co">##  [59] shiny_1.7.2                   BiocSingular_1.13.1          </span></span>
1500 
+<span><span class="co">##  [61] xfun_0.34                     cluster_2.1.4                </span></span>
1501 
+<span><span class="co">##  [63] KEGGREST_1.37.3               tibble_3.1.8                 </span></span>
1502 
+<span><span class="co">##  [65] interactiveDisplayBase_1.35.1 ggrepel_0.9.1                </span></span>
1503 
+<span><span class="co">##  [67] celda_1.13.0                  listenv_0.8.0                </span></span>
1504 
+<span><span class="co">##  [69] Biostrings_2.65.6             png_0.1-7                    </span></span>
1505 1505 
 <span><span class="co">##  [71] future_1.28.0                 withr_2.5.0                  </span></span>
1506 1506 
 <span><span class="co">##  [73] bitops_1.0-7                  plyr_1.8.7                   </span></span>
1507 
-<span><span class="co">##  [75] assertive.base_0.0-9          GSEABase_1.58.0              </span></span>
1507 
+<span><span class="co">##  [75] assertive.base_0.0-9          GSEABase_1.59.0              </span></span>
1508 1508 
 <span><span class="co">##  [77] dqrng_0.3.0                   pROC_1.18.0                  </span></span>
1509 1509 
 <span><span class="co">##  [79] pillar_1.8.1                  cachem_1.0.6                 </span></span>
1510 
-<span><span class="co">##  [81] fs_1.5.2                      DelayedMatrixStats_1.18.0    </span></span>
1511 
-<span><span class="co">##  [83] vctrs_0.4.1                   ellipsis_0.3.2               </span></span>
1510 
+<span><span class="co">##  [81] fs_1.5.2                      DelayedMatrixStats_1.19.2    </span></span>
1511 
+<span><span class="co">##  [83] vctrs_0.5.0                   ellipsis_0.3.2               </span></span>
1512 1512 
 <span><span class="co">##  [85] generics_0.1.3                tools_4.2.1                  </span></span>
1513 1513 
 <span><span class="co">##  [87] beeswarm_0.4.0                munsell_0.5.0                </span></span>
1514 1514 
 <span><span class="co">##  [89] fastmap_1.1.0                 compiler_4.2.1               </span></span>
1515 1515 
 <span><span class="co">##  [91] abind_1.4-5                   httpuv_1.6.6                 </span></span>
1516 
-<span><span class="co">##  [93] rtracklayer_1.56.1            ExperimentHub_2.4.0          </span></span>
1516 
+<span><span class="co">##  [93] rtracklayer_1.57.0            ExperimentHub_2.5.0          </span></span>
1517 1517 
 <span><span class="co">##  [95] plotly_4.10.0                 rgeos_0.5-9                  </span></span>
1518 
-<span><span class="co">##  [97] GenomeInfoDbData_1.2.8        gridExtra_2.3                </span></span>
1519 
-<span><span class="co">##  [99] enrichR_3.1                   edgeR_3.38.4                 </span></span>
1518 
+<span><span class="co">##  [97] GenomeInfoDbData_1.2.9        gridExtra_2.3                </span></span>
1519 
+<span><span class="co">##  [99] enrichR_3.1                   edgeR_3.39.6                 </span></span>
1520 1520 
 <span><span class="co">## [101] lattice_0.20-45               deldir_1.0-6                 </span></span>
1521 1521 
 <span><span class="co">## [103] utf8_1.2.2                    later_1.3.0                  </span></span>
1522 
-<span><span class="co">## [105] BiocFileCache_2.4.0           jsonlite_1.8.0               </span></span>
1522 
+<span><span class="co">## [105] BiocFileCache_2.5.2           jsonlite_1.8.3               </span></span>
1523 1523 
 <span><span class="co">## [107] multipanelfigure_2.1.2        scales_1.2.1                 </span></span>
1524 
-<span><span class="co">## [109] graph_1.74.0                  ScaledMatrix_1.4.1           </span></span>
1525 
-<span><span class="co">## [111] pbapply_1.5-0                 sparseMatrixStats_1.8.0      </span></span>
1524 
+<span><span class="co">## [109] graph_1.75.0                  ScaledMatrix_1.5.1           </span></span>
1525 
+<span><span class="co">## [111] pbapply_1.5-0                 sparseMatrixStats_1.9.0      </span></span>
1526 1526 
 <span><span class="co">## [113] lazyeval_0.2.2                promises_1.2.0.1             </span></span>
1527 1527 
 <span><span class="co">## [115] doParallel_1.0.17             R.utils_2.12.0               </span></span>
1528 
-<span><span class="co">## [117] goftest_1.2-3                 spatstat.utils_2.3-1         </span></span>
1529 
-<span><span class="co">## [119] reticulate_1.26               rmarkdown_2.16               </span></span>
1528 
+<span><span class="co">## [117] goftest_1.2-3                 spatstat.utils_3.0-1         </span></span>
1529 
+<span><span class="co">## [119] reticulate_1.26               rmarkdown_2.17               </span></span>
1530 1530 
 <span><span class="co">## [121] pkgdown_2.0.6                 cowplot_1.1.1                </span></span>
1531 
-<span><span class="co">## [123] textshaping_0.3.6             webshot_0.5.3                </span></span>
1531 
+<span><span class="co">## [123] textshaping_0.3.6             webshot_0.5.4                </span></span>
1532 1532 
 <span><span class="co">## [125] statmod_1.4.37                Rtsne_0.16                   </span></span>
1533 1533 
 <span><span class="co">## [127] uwot_0.1.14                   igraph_1.3.5                 </span></span>
1534 
-<span><span class="co">## [129] survival_3.3-1                yaml_2.3.5                   </span></span>
1534 
+<span><span class="co">## [129] survival_3.4-0                yaml_2.3.6                   </span></span>
1535 1535 
 <span><span class="co">## [131] systemfonts_1.0.4             htmltools_0.5.3              </span></span>
1536 
-<span><span class="co">## [133] memoise_2.0.1                 BiocIO_1.6.0                 </span></span>
1536 
+<span><span class="co">## [133] memoise_2.0.1                 BiocIO_1.7.1                 </span></span>
1537 1537 
 <span><span class="co">## [135] Seurat_4.2.0                  locfit_1.5-9.6               </span></span>
1538 1538 
 <span><span class="co">## [137] here_1.0.1                    viridisLite_0.4.1            </span></span>
1539 
-<span><span class="co">## [139] digest_0.6.29                 assertthat_0.2.1             </span></span>
1539 
+<span><span class="co">## [139] digest_0.6.30                 assertthat_0.2.1             </span></span>
1540 1540 
 <span><span class="co">## [141] mime_0.12                     rappdirs_0.3.3               </span></span>
1541 
-<span><span class="co">## [143] spam_2.9-1                    RSQLite_2.2.17               </span></span>
1542 
-<span><span class="co">## [145] future.apply_1.9.1            data.table_1.14.2            </span></span>
1541 
+<span><span class="co">## [143] spam_2.9-1                    RSQLite_2.2.18               </span></span>
1542 
+<span><span class="co">## [145] future.apply_1.9.1            data.table_1.14.4            </span></span>
1543 1543 
 <span><span class="co">## [147] blob_1.2.3                    R.oo_1.25.0                  </span></span>
1544 
-<span><span class="co">## [149] ragg_1.2.2                    labeling_0.4.2               </span></span>
1545 
-<span><span class="co">## [151] splines_4.2.1                 Rhdf5lib_1.18.2              </span></span>
1546 
-<span><span class="co">## [153] AnnotationHub_3.4.0           RCurl_1.98-1.8               </span></span>
1544 
+<span><span class="co">## [149] ragg_1.2.4                    labeling_0.4.2               </span></span>
1545 
+<span><span class="co">## [151] splines_4.2.1                 Rhdf5lib_1.19.2              </span></span>
1546 
+<span><span class="co">## [153] AnnotationHub_3.5.2           RCurl_1.98-1.9               </span></span>
1547 1547 
 <span><span class="co">## [155] assertive.numbers_0.0-2       colorspace_2.0-3             </span></span>
1548 
-<span><span class="co">## [157] DropletUtils_1.16.0           BiocManager_1.30.18          </span></span>
1548 
+<span><span class="co">## [157] DropletUtils_1.17.3           BiocManager_1.30.18          </span></span>
1549 1549 
 <span><span class="co">## [159] ggbeeswarm_0.6.0              assertive.files_0.0-2        </span></span>
1550 1550 
 <span><span class="co">## [161] sass_0.4.2                    Rcpp_1.0.9                   </span></span>
1551 1551 
 <span><span class="co">## [163] RANN_2.6.1                    fansi_1.0.3                  </span></span>
1552 1552 
 <span><span class="co">## [165] parallelly_1.32.1             R6_2.5.1                     </span></span>
1553 
-<span><span class="co">## [167] grid_4.2.1                    ggridges_0.5.3               </span></span>
1554 
-<span><span class="co">## [169] lifecycle_1.0.2               bluster_1.6.0                </span></span>
1555 
-<span><span class="co">## [171] curl_4.3.2                    leiden_0.4.3                 </span></span>
1553 
+<span><span class="co">## [167] grid_4.2.1                    ggridges_0.5.4               </span></span>
1554 
+<span><span class="co">## [169] lifecycle_1.0.3               bluster_1.7.0                </span></span>
1555 
+<span><span class="co">## [171] curl_4.3.3                    leiden_0.4.3                 </span></span>
1556 1556 
 <span><span class="co">## [173] jquerylib_0.1.4               svMisc_1.2.3                 </span></span>
1557 1557 
 <span><span class="co">## [175] desc_1.4.2                    RcppAnnoy_0.0.19             </span></span>
1558 
-<span><span class="co">## [177] GSVAdata_1.32.0               RColorBrewer_1.1-3           </span></span>
1558 
+<span><span class="co">## [177] GSVAdata_1.33.0               RColorBrewer_1.1-3           </span></span>
1559 1559 
 <span><span class="co">## [179] iterators_1.0.14              stringr_1.4.1                </span></span>
1560 
-<span><span class="co">## [181] htmlwidgets_1.5.4             beachmat_2.12.0              </span></span>
1561 
-<span><span class="co">## [183] polyclip_1.10-0               purrr_0.3.4                  </span></span>
1560 
+<span><span class="co">## [181] htmlwidgets_1.5.4             beachmat_2.13.4              </span></span>
1561 
+<span><span class="co">## [183] polyclip_1.10-4               purrr_0.3.5                  </span></span>
1562 1562 
 <span><span class="co">## [185] gridGraphics_0.5-1            rvest_1.0.3                  </span></span>
1563 
-<span><span class="co">## [187] mgcv_1.8-40                   globals_0.16.1               </span></span>
1564 
-<span><span class="co">## [189] fishpond_2.2.0                patchwork_1.1.2              </span></span>
1565 
-<span><span class="co">## [191] spatstat.random_2.2-0         scds_1.12.0                  </span></span>
1563 
+<span><span class="co">## [187] mgcv_1.8-41                   globals_0.16.1               </span></span>
1564 
+<span><span class="co">## [189] fishpond_2.3.21               patchwork_1.1.2              </span></span>
1565 
+<span><span class="co">## [191] spatstat.random_2.2-0         scds_1.13.1                  </span></span>
1566 1566 
 <span><span class="co">## [193] progressr_0.11.0              codetools_0.2-18             </span></span>
1567 
-<span><span class="co">## [195] FNN_1.1.3.1                   metapod_1.4.0                </span></span>
1567 
+<span><span class="co">## [195] FNN_1.1.3.1                   metapod_1.5.0                </span></span>
1568 1568 
 <span><span class="co">## [197] gtools_3.9.3                  dbplyr_2.2.1                 </span></span>
1569 1569 
 <span><span class="co">## [199] MCMCprecision_0.4.0           R.methodsS3_1.8.2            </span></span>
1570 1570 
 <span><span class="co">## [201] gtable_0.3.1                  DBI_1.1.3                    </span></span>
1571 1571 
 <span><span class="co">## [203] highr_0.9                     tensor_1.5                   </span></span>
1572 1572 
 <span><span class="co">## [205] httr_1.4.4                    KernSmooth_2.23-20           </span></span>
1573 1573 
 <span><span class="co">## [207] stringi_1.7.8                 farver_2.1.1                 </span></span>
1574 
-<span><span class="co">## [209] reshape2_1.4.4                annotate_1.74.0              </span></span>
1574 
+<span><span class="co">## [209] reshape2_1.4.4                annotate_1.75.0              </span></span>
1575 1575 
 <span><span class="co">## [211] viridis_0.6.2                 magick_2.7.3                 </span></span>
1576 1576 
 <span><span class="co">## [213] xml2_1.3.3                    combinat_0.0-8               </span></span>
1577 
-<span><span class="co">## [215] BiocNeighbors_1.14.0          kableExtra_1.3.4             </span></span>
1577 
+<span><span class="co">## [215] BiocNeighbors_1.15.1          kableExtra_1.3.4             </span></span>
1578 1578 
 <span><span class="co">## [217] restfulr_0.0.15               scattermore_0.8              </span></span>
1579 
-<span><span class="co">## [219] BiocVersion_3.15.2            scran_1.24.1                 </span></span>
1580 
-<span><span class="co">## [221] bit_4.0.4                     spatstat.data_2.2-0          </span></span>
1579 
+<span><span class="co">## [219] BiocVersion_3.16.0            scran_1.25.1                 </span></span>
1580 
+<span><span class="co">## [221] bit_4.0.4                     spatstat.data_3.0-0          </span></span>
1581 1581 
 <span><span class="co">## [223] pkgconfig_2.0.3               knitr_1.40</span></span></code></pre>
1582 1582 
 </details>
1583 1583 
 </div>
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... ... 
@@ -34,7 +34,7 @@
34 34 
       </button>
35 35 
       <span class="navbar-brand">
36 36 
         <a class="navbar-link" href="../index.html">singleCellTK</a>
37 
-        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="">2.7.2</span>
37 
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="">2.7.3</span>
38 38 
       </span>
39 39 
     </div>
40 40
... ... 
@@ -301,8 +301,8 @@ package.</p>
301 301 
 <span><span class="va">pbmc4k.droplet</span> <span class="op">&lt;-</span> <span class="fu">DropletUtils</span><span class="fu">::</span><span class="fu"><a href="https://rdrr.io/pkg/DropletUtils/man/read10xCounts.html" class="external-link">read10xCounts</a></span><span class="op">(</span><span class="va">fname</span>, col.names <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span>
302 302 
 <span></span>
303 303 
 <span><span class="co">### change the sample column</span></span>
304 
-<span><span class="fu"><a href="https://rdrr.io/r/base/names.html" class="external-link">names</a></span><span class="op">(</span><span class="fu">colData</span><span class="op">(</span><span class="va">pbmc4k.droplet</span><span class="op">)</span><span class="op">)</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"sample"</span>, <span class="st">"Barcode"</span><span class="op">)</span></span>
305 
-<span><span class="fu">colData</span><span class="op">(</span><span class="va">pbmc4k.droplet</span><span class="op">)</span><span class="op">$</span><span class="va">sample</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/rep.html" class="external-link">rep</a></span><span class="op">(</span><span class="st">"pbmc4k"</span>, <span class="fu"><a href="https://rdrr.io/r/base/nrow.html" class="external-link">ncol</a></span><span class="op">(</span><span class="fu">colData</span><span class="op">(</span><span class="va">pbmc4k.droplet</span><span class="op">)</span><span class="op">)</span><span class="op">)</span></span></code></pre></div>
304 
+<span><span class="fu"><a href="https://rdrr.io/r/base/names.html" class="external-link">names</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/pkg/SummarizedExperiment/man/SummarizedExperiment-class.html" class="external-link">colData</a></span><span class="op">(</span><span class="va">pbmc4k.droplet</span><span class="op">)</span><span class="op">)</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"sample"</span>, <span class="st">"Barcode"</span><span class="op">)</span></span>
305 
+<span><span class="fu"><a href="https://rdrr.io/pkg/SummarizedExperiment/man/SummarizedExperiment-class.html" class="external-link">colData</a></span><span class="op">(</span><span class="va">pbmc4k.droplet</span><span class="op">)</span><span class="op">$</span><span class="va">sample</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/rep.html" class="external-link">rep</a></span><span class="op">(</span><span class="st">"pbmc4k"</span>, <span class="fu"><a href="https://rdrr.io/r/base/nrow.html" class="external-link">ncol</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/pkg/SummarizedExperiment/man/SummarizedExperiment-class.html" class="external-link">colData</a></span><span class="op">(</span><span class="va">pbmc4k.droplet</span><span class="op">)</span><span class="op">)</span><span class="op">)</span></span></code></pre></div>
306 306 
 <p>SCTK also supports the importing of single-cell data from the
307 307 
 following platforms: <a href="https://support.10xgenomics.com/single-cell-gene-expression/software/pipelines/latest/what-is-cell-ranger" class="external-link">10X
308 308 
 CellRanger</a>, <a href="https://github.com/alexdobin/STAR/blob/master/docs/STARsolo.md" class="external-link">STARSolo</a>,
... ... 
@@ -322,73 +322,73 @@ function <code><a href="../reference/runDropletQC.html">runDropletQC()</a></code
322 322 
 algorithms will be run.</p>
323 323 
 <div class="sourceCode" id="cb3"><pre class="downlit sourceCode r">
324 324 
 <code class="sourceCode R"><span><span class="va">pbmc4k.droplet</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/runDropletQC.html">runDropletQC</a></span><span class="op">(</span><span class="va">pbmc4k.droplet</span><span class="op">)</span></span></code></pre></div>
325 
-<pre><code><span><span class="co">## Wed Oct 19 03:28:54 2022 ... Running 'perCellQCMetrics'</span></span></code></pre>
326 
-<pre><code><span><span class="co">## Wed Oct 19 03:28:55 2022 ... Running 'emptyDrops'</span></span></code></pre>
327 
-<pre><code><span><span class="co">## Wed Oct 19 03:29:10 2022 ... Running 'barcodeRanks'</span></span></code></pre>
325 
+<pre><code><span><span class="co">## Tue Oct 25 16:08:34 2022 ... Running 'perCellQCMetrics'</span></span></code></pre>
326 
+<pre><code><span><span class="co">## Tue Oct 25 16:08:35 2022 ... Running 'emptyDrops'</span></span></code></pre>
327 
+<pre><code><span><span class="co">## Tue Oct 25 16:08:48 2022 ... Running 'barcodeRanks'</span></span></code></pre>
328 328 
 <p>If users choose to only run a specific set of algorithms, they can
329 329 
 specify which to run with the <code>algorithms</code> parameter.</p>
330 330 
 <p>After running QC functions with SCTK, the output will be stored in
331 331 
 the <code>colData</code> slot of the <code>SingleCellExperiment</code>
332 332 
 object.</p>
333 333 
 <div class="sourceCode" id="cb7"><pre class="downlit sourceCode r">
334 
-<code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/r/utils/head.html" class="external-link">head</a></span><span class="op">(</span><span class="fu">colData</span><span class="op">(</span><span class="va">pbmc4k.droplet</span><span class="op">)</span>, <span class="fl">5</span><span class="op">)</span></span></code></pre></div>
334 
+<code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/r/utils/head.html" class="external-link">head</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/pkg/SummarizedExperiment/man/SummarizedExperiment-class.html" class="external-link">colData</a></span><span class="op">(</span><span class="va">pbmc4k.droplet</span><span class="op">)</span>, <span class="fl">5</span><span class="op">)</span></span></code></pre></div>
335 335 
 <pre><code><span><span class="co">## DataFrame with 5 rows and 16 columns</span></span>
336 336 
 <span><span class="co">##                         sample            Barcode       sum  detected</span></span>
337 337 
 <span><span class="co">##                    &lt;character&gt;        &lt;character&gt; &lt;numeric&gt; &lt;integer&gt;</span></span>
338 
-<span><span class="co">## ATCACGAAGGAGTACC-1      pbmc4k ATCACGAAGGAGTACC-1         0         0</span></span>
339 
-<span><span class="co">## GTCGGGTCACAAGCCC-1      pbmc4k GTCGGGTCACAAGCCC-1         1         1</span></span>
340 
-<span><span class="co">## AAAGTAGAGGGATGGG-1      pbmc4k AAAGTAGAGGGATGGG-1         0         0</span></span>
341 
-<span><span class="co">## CCAATCCGTACCAGTT-1      pbmc4k CCAATCCGTACCAGTT-1         0         0</span></span>
342 
-<span><span class="co">## TTCCCAGTCATTGCCC-1      pbmc4k TTCCCAGTCATTGCCC-1        37        36</span></span>
338 
+<span><span class="co">## AACCGCGGTTGAGGTG-1      pbmc4k AACCGCGGTTGAGGTG-1         1         1</span></span>
339 
+<span><span class="co">## CAAGAAAAGTCCAGGA-1      pbmc4k CAAGAAAAGTCCAGGA-1         2         2</span></span>
340 
+<span><span class="co">## TCTCTAAAGCGCCTCA-1      pbmc4k TCTCTAAAGCGCCTCA-1         0         0</span></span>
341 
+<span><span class="co">## ATTATCCAGCGTCAAG-1      pbmc4k ATTATCCAGCGTCAAG-1         4         4</span></span>
342 
+<span><span class="co">## GAGCAGAGTCCAACTA-1      pbmc4k GAGCAGAGTCCAACTA-1         0         0</span></span>
343 343 
 <span><span class="co">##                    percent.top_50 percent.top_100 percent.top_200</span></span>
344 344 
 <span><span class="co">##                         &lt;numeric&gt;       &lt;numeric&gt;       &lt;numeric&gt;</span></span>
345 
-<span><span class="co">## ATCACGAAGGAGTACC-1            NaN             NaN             NaN</span></span>
346 
-<span><span class="co">## GTCGGGTCACAAGCCC-1            100             100             100</span></span>
347 
-<span><span class="co">## AAAGTAGAGGGATGGG-1            NaN             NaN             NaN</span></span>
348 
-<span><span class="co">## CCAATCCGTACCAGTT-1            NaN             NaN             NaN</span></span>
349 
-<span><span class="co">## TTCCCAGTCATTGCCC-1            100             100             100</span></span>
345 
+<span><span class="co">## AACCGCGGTTGAGGTG-1            100             100             100</span></span>
346 
+<span><span class="co">## CAAGAAAAGTCCAGGA-1            100             100             100</span></span>
347 
+<span><span class="co">## TCTCTAAAGCGCCTCA-1            NaN             NaN             NaN</span></span>
348 
+<span><span class="co">## ATTATCCAGCGTCAAG-1            100             100             100</span></span>
349 
+<span><span class="co">## GAGCAGAGTCCAACTA-1            NaN             NaN             NaN</span></span>
350 350 
 <span><span class="co">##                    percent.top_500     total dropletUtils_emptyDrops_total</span></span>
351 351 
 <span><span class="co">##                          &lt;numeric&gt; &lt;numeric&gt;                     &lt;integer&gt;</span></span>
352 
-<span><span class="co">## ATCACGAAGGAGTACC-1             NaN         0                             0</span></span>
353 
-<span><span class="co">## GTCGGGTCACAAGCCC-1             100         1                             1</span></span>
354 
-<span><span class="co">## AAAGTAGAGGGATGGG-1             NaN         0                             0</span></span>
355 
-<span><span class="co">## CCAATCCGTACCAGTT-1             NaN         0                             0</span></span>
356 
-<span><span class="co">## TTCCCAGTCATTGCCC-1             100        37                            37</span></span>
352 
+<span><span class="co">## AACCGCGGTTGAGGTG-1             100         1                             1</span></span>
353 
+<span><span class="co">## CAAGAAAAGTCCAGGA-1             100         2                             2</span></span>
354 
+<span><span class="co">## TCTCTAAAGCGCCTCA-1             NaN         0                             0</span></span>
355 
+<span><span class="co">## ATTATCCAGCGTCAAG-1             100         4                             4</span></span>
356 
+<span><span class="co">## GAGCAGAGTCCAACTA-1             NaN         0                             0</span></span>
357 357 
 <span><span class="co">##                    dropletUtils_emptyDrops_logprob</span></span>
358 358 
 <span><span class="co">##                                          &lt;numeric&gt;</span></span>
359 
-<span><span class="co">## ATCACGAAGGAGTACC-1                              NA</span></span>
360 
-<span><span class="co">## GTCGGGTCACAAGCCC-1                              NA</span></span>
361 
-<span><span class="co">## AAAGTAGAGGGATGGG-1                              NA</span></span>
362 
-<span><span class="co">## CCAATCCGTACCAGTT-1                              NA</span></span>
363 
-<span><span class="co">## TTCCCAGTCATTGCCC-1                              NA</span></span>
359 
+<span><span class="co">## AACCGCGGTTGAGGTG-1                              NA</span></span>
360 
+<span><span class="co">## CAAGAAAAGTCCAGGA-1                              NA</span></span>
361 
+<span><span class="co">## TCTCTAAAGCGCCTCA-1                              NA</span></span>
362 
+<span><span class="co">## ATTATCCAGCGTCAAG-1                              NA</span></span>
363 
+<span><span class="co">## GAGCAGAGTCCAACTA-1                              NA</span></span>
364 364 
 <span><span class="co">##                    dropletUtils_emptyDrops_pvalue</span></span>
365 365 
 <span><span class="co">##                                         &lt;numeric&gt;</span></span>
366 
-<span><span class="co">## ATCACGAAGGAGTACC-1                             NA</span></span>
367 
-<span><span class="co">## GTCGGGTCACAAGCCC-1                             NA</span></span>
368 
-<span><span class="co">## AAAGTAGAGGGATGGG-1                             NA</span></span>
369 
-<span><span class="co">## CCAATCCGTACCAGTT-1                             NA</span></span>
370 
-<span><span class="co">## TTCCCAGTCATTGCCC-1                             NA</span></span>
366 
+<span><span class="co">## AACCGCGGTTGAGGTG-1                             NA</span></span>
367 
+<span><span class="co">## CAAGAAAAGTCCAGGA-1                             NA</span></span>
368 
+<span><span class="co">## TCTCTAAAGCGCCTCA-1                             NA</span></span>
369 
+<span><span class="co">## ATTATCCAGCGTCAAG-1                             NA</span></span>
370 
+<span><span class="co">## GAGCAGAGTCCAACTA-1                             NA</span></span>
371 371 
 <span><span class="co">##                    dropletUtils_emptyDrops_limited dropletUtils_emptyDrops_fdr</span></span>
372 372 
 <span><span class="co">##                                          &lt;logical&gt;                   &lt;numeric&gt;</span></span>
373 
-<span><span class="co">## ATCACGAAGGAGTACC-1                              NA                          NA</span></span>
374 
-<span><span class="co">## GTCGGGTCACAAGCCC-1                              NA                          NA</span></span>
375 
-<span><span class="co">## AAAGTAGAGGGATGGG-1                              NA                          NA</span></span>
376 
-<span><span class="co">## CCAATCCGTACCAGTT-1                              NA                          NA</span></span>
377 
-<span><span class="co">## TTCCCAGTCATTGCCC-1                              NA                          NA</span></span>
373 
+<span><span class="co">## AACCGCGGTTGAGGTG-1                              NA                          NA</span></span>
374 
+<span><span class="co">## CAAGAAAAGTCCAGGA-1                              NA                          NA</span></span>
375 
+<span><span class="co">## TCTCTAAAGCGCCTCA-1                              NA                          NA</span></span>
376 
+<span><span class="co">## ATTATCCAGCGTCAAG-1                              NA                          NA</span></span>
377 
+<span><span class="co">## GAGCAGAGTCCAACTA-1                              NA                          NA</span></span>
378 378 
 <span><span class="co">##                    dropletUtils_BarcodeRank_Knee</span></span>
379 379 
 <span><span class="co">##                                        &lt;integer&gt;</span></span>
380 
-<span><span class="co">## ATCACGAAGGAGTACC-1                             0</span></span>
381 
-<span><span class="co">## GTCGGGTCACAAGCCC-1                             0</span></span>
382 
-<span><span class="co">## AAAGTAGAGGGATGGG-1                             0</span></span>
383 
-<span><span class="co">## CCAATCCGTACCAGTT-1                             0</span></span>
384 
-<span><span class="co">## TTCCCAGTCATTGCCC-1                             0</span></span>
380 
+<span><span class="co">## AACCGCGGTTGAGGTG-1                             0</span></span>
381 
+<span><span class="co">## CAAGAAAAGTCCAGGA-1                             0</span></span>
382 
+<span><span class="co">## TCTCTAAAGCGCCTCA-1                             0</span></span>
383 
+<span><span class="co">## ATTATCCAGCGTCAAG-1                             0</span></span>
384 
+<span><span class="co">## GAGCAGAGTCCAACTA-1                             0</span></span>
385 385 
 <span><span class="co">##                    dropletUtils_BarcodeRank_Inflection</span></span>
386 386 
 <span><span class="co">##                                              &lt;integer&gt;</span></span>
387 
-<span><span class="co">## ATCACGAAGGAGTACC-1                                   0</span></span>
388 
-<span><span class="co">## GTCGGGTCACAAGCCC-1                                   0</span></span>
389 
-<span><span class="co">## AAAGTAGAGGGATGGG-1                                   0</span></span>
390 
-<span><span class="co">## CCAATCCGTACCAGTT-1                                   0</span></span>
391 
-<span><span class="co">## TTCCCAGTCATTGCCC-1                                   0</span></span></code></pre>
387 
+<span><span class="co">## AACCGCGGTTGAGGTG-1                                   0</span></span>
388 
+<span><span class="co">## CAAGAAAAGTCCAGGA-1                                   0</span></span>
389 
+<span><span class="co">## TCTCTAAAGCGCCTCA-1                                   0</span></span>
390 
+<span><span class="co">## ATTATCCAGCGTCAAG-1                                   0</span></span>
391 
+<span><span class="co">## GAGCAGAGTCCAACTA-1                                   0</span></span></code></pre>
392 392 
 <div style="border: 1px solid #ddd; padding: 5px; overflow-x: scroll; width:80%; ">
393 393 
 <table class="table table" style="margin-left: auto; margin-right: auto;">
394 394 
 <thead><tr>
... ... 
@@ -446,37 +446,37 @@ dropletUtils_BarcodeRank_Inflection
446 446 
 <tbody>
447 447 
 <tr>
448 448 
 <td style="text-align:left;">
449 
-ATCACGAAGGAGTACC-1
449 
+AACCGCGGTTGAGGTG-1
450 450 
 </td>
451 451 
 <td style="text-align:left;">
452 452 
 pbmc4k
453 453 
 </td>
454 454 
 <td style="text-align:left;">
455 
-ATCACGAAGGAGTACC-1
455 
+AACCGCGGTTGAGGTG-1
456 456 
 </td>
457 457 
 <td style="text-align:right;">
458 
-0
458 
+1
459 459 
 </td>
460 460 
 <td style="text-align:right;">
461 
-0
461 
+1
462 462 
 </td>
463 463 
 <td style="text-align:right;">
464 
-NaN
464 
+100
465 465 
 </td>
466 466 
 <td style="text-align:right;">
467 
-NaN
467 
+100
468 468 
 </td>
469 469 
 <td style="text-align:right;">
470 
-NaN
470 
+100
471 471 
 </td>
472 472 
 <td style="text-align:right;">
473 
-NaN
473 
+100
474 474 
 </td>
475 475 
 <td style="text-align:right;">
476 
-0
476 
+1
477 477 
 </td>
478 478 
 <td style="text-align:right;">
479 
-0
479 
+1
480 480 
 </td>
481 481 
 <td style="text-align:right;">
482 482 
 NA
... ... 
@@ -499,19 +499,19 @@ NA
499 499 
 </tr>
500 500 
 <tr>
501 501 
 <td style="text-align:left;">
502 
-GTCGGGTCACAAGCCC-1
502 
+CAAGAAAAGTCCAGGA-1
503 503 
 </td>
504 504 
 <td style="text-align:left;">
505 505 
 pbmc4k
506 506 
 </td>
507 507 
 <td style="text-align:left;">
508 
-GTCGGGTCACAAGCCC-1
508 
+CAAGAAAAGTCCAGGA-1
509 509 
 </td>
510 510 
 <td style="text-align:right;">
511 
-1
511 
+2
512 512 
 </td>
513 513 
 <td style="text-align:right;">
514 
-1
514 
+2
515 515 
 </td>
516 516 
 <td style="text-align:right;">
517 517 
 100
... ... 
@@ -526,10 +526,10 @@ GTCGGGTCACAAGCCC-1
526 526 
 100
527 527 
 </td>
528 528 
 <td style="text-align:right;">
529 
-1
529 
+2
530 530 
 </td>
531 531 
 <td style="text-align:right;">
532 
-1
532 
+2
533 533 
 </td>
534 534 
 <td style="text-align:right;">
535 535 
 NA
... ... 
@@ -552,13 +552,13 @@ NA
552 552 
 </tr>
553 553 
 <tr>
554 554 
 <td style="text-align:left;">
555 
-AAAGTAGAGGGATGGG-1
555 
+TCTCTAAAGCGCCTCA-1
556 556 
 </td>
557 557 
 <td style="text-align:left;">
558 558 
 pbmc4k
559 559 
 </td>
560 560 
 <td style="text-align:left;">
561 
-AAAGTAGAGGGATGGG-1
561 
+TCTCTAAAGCGCCTCA-1
562 562 
 </td>
563 563 
 <td style="text-align:right;">
564 564 
 0
... ... 
@@ -605,37 +605,37 @@ NA
605 605 
 </tr>
606 606 
 <tr>
607 607 
 <td style="text-align:left;">
608 
-CCAATCCGTACCAGTT-1
608 
+ATTATCCAGCGTCAAG-1
609 609 
 </td>
610 610 
 <td style="text-align:left;">
611 611 
 pbmc4k
612 612 
 </td>
613 613 
 <td style="text-align:left;">
614 
-CCAATCCGTACCAGTT-1
614 
+ATTATCCAGCGTCAAG-1
615 615 
 </td>
616 616 
 <td style="text-align:right;">
617 
-0
617 
+4
618 618 
 </td>
619 619 
 <td style="text-align:right;">
620 
-0
620 
+4
621 621 
 </td>
622 622 
 <td style="text-align:right;">
623 
-NaN
623 
+100
624 624 
 </td>
625 625 
 <td style="text-align:right;">
626 
-NaN
626 
+100
627 627 
 </td>
628 628 
 <td style="text-align:right;">
629 
-NaN
629 
+100
630 630 
 </td>
631 631 
 <td style="text-align:right;">
632 
-NaN
632 
+100
633 633 
 </td>
634 634 
 <td style="text-align:right;">
635 
-0
635 
+4
636 636 
 </td>
637 637 
 <td style="text-align:right;">
638 
-0
638 
+4
639 639 
 </td>
640 640 
 <td style="text-align:right;">
641 641 
 NA
... ... 
@@ -658,37 +658,37 @@ NA
658 658 
 </tr>
659 659 
 <tr>
660 660 
 <td style="text-align:left;">
661 
-TTCCCAGTCATTGCCC-1
661 
+GAGCAGAGTCCAACTA-1
662 662 
 </td>
663 663 
 <td style="text-align:left;">
664 664 
 pbmc4k
665 665 
 </td>
666 666 
 <td style="text-align:left;">
667 
-TTCCCAGTCATTGCCC-1
667 
+GAGCAGAGTCCAACTA-1
668 668 
 </td>
669 669 
 <td style="text-align:right;">
670 
-37
670 
+0
671 671 
 </td>
672 672 
 <td style="text-align:right;">
673 
-36
673 
+0
674 674 
 </td>
675 675 
 <td style="text-align:right;">
676 
-100
676 
+NaN
677 677 
 </td>
678 678 
 <td style="text-align:right;">
679 
-100
679 
+NaN
680 680 
 </td>
681 681 
 <td style="text-align:right;">
682 
-100
682 
+NaN
683 683 
 </td>
684 684 
 <td style="text-align:right;">
685 
-100
685 
+NaN
686 686 
 </td>
687 687 
 <td style="text-align:right;">
688 
-37
688 
+0
689 689 
 </td>
690 690 
 <td style="text-align:right;">
691 
-37
691 
+0
692 692 
 </td>
693 693 
 <td style="text-align:right;">
694 694 
 NA
... ... 
@@ -925,7 +925,7 @@ documentation</a> for detail.</p>
925 925 
 <div class="sourceCode" id="cb17"><pre class="downlit sourceCode r">
926 926 
 <code class="sourceCode R"><span><span class="co">#After filtering:</span></span>
927 927 
 <span><span class="fu"><a href="https://rdrr.io/r/base/dim.html" class="external-link">dim</a></span><span class="op">(</span><span class="va">pbmc4k.droplet</span><span class="op">)</span></span></code></pre></div>
928 
-<pre><code><span><span class="co">## [1] 33694   328</span></span></code></pre>
928 
+<pre><code><span><span class="co">## [1] 33694   309</span></span></code></pre>
929 929 
 <p>We can compare the average total UMI counts per cell before and after
930 930 
 cell filtration:</p>
931 931 
 <div class="sourceCode" id="cb19"><pre class="downlit sourceCode r">
... ... 
@@ -958,73 +958,72 @@ documentation</a>.</p>
958 958 
 <span><span class="co">## [8] base     </span></span>
959 959 
 <span><span class="co">## </span></span>
960 960 
 <span><span class="co">## other attached packages:</span></span>
961 
-<span><span class="co">##  [1] BiocFileCache_2.4.0         dbplyr_2.2.1               </span></span>
962 
-<span><span class="co">##  [3] dplyr_1.0.10                singleCellTK_2.7.2         </span></span>
963 
-<span><span class="co">##  [5] DelayedArray_0.22.0         Matrix_1.5-1               </span></span>
964 
-<span><span class="co">##  [7] SingleCellExperiment_1.18.0 SummarizedExperiment_1.26.1</span></span>
965 
-<span><span class="co">##  [9] Biobase_2.56.0              GenomicRanges_1.48.0       </span></span>
966 
-<span><span class="co">## [11] GenomeInfoDb_1.32.4         IRanges_2.30.1             </span></span>
967 
-<span><span class="co">## [13] S4Vectors_0.34.0            BiocGenerics_0.42.0        </span></span>
968 
-<span><span class="co">## [15] MatrixGenerics_1.8.1        matrixStats_0.62.0         </span></span>
961 
+<span><span class="co">##  [1] BiocFileCache_2.5.2         dbplyr_2.2.1               </span></span>
962 
+<span><span class="co">##  [3] dplyr_1.0.10                singleCellTK_2.7.3         </span></span>
963 
+<span><span class="co">##  [5] DelayedArray_0.23.2         Matrix_1.5-1               </span></span>
964 
+<span><span class="co">##  [7] SingleCellExperiment_1.19.1 SummarizedExperiment_1.27.3</span></span>
965 
+<span><span class="co">##  [9] Biobase_2.57.1              GenomicRanges_1.49.1       </span></span>
966 
+<span><span class="co">## [11] GenomeInfoDb_1.33.15        IRanges_2.31.2             </span></span>
967 
+<span><span class="co">## [13] S4Vectors_0.35.4            BiocGenerics_0.43.4        </span></span>
968 
+<span><span class="co">## [15] MatrixGenerics_1.9.1        matrixStats_0.62.0         </span></span>
969 969 
 <span><span class="co">## </span></span>
970 970 
 <span><span class="co">## loaded via a namespace (and not attached):</span></span>
971 971 
 <span><span class="co">##   [1] ggbeeswarm_0.6.0          colorspace_2.0-3         </span></span>
972 
-<span><span class="co">##   [3] ellipsis_0.3.2            rprojroot_2.0.3          </span></span>
973 
-<span><span class="co">##   [5] GSVAdata_1.32.0           scuttle_1.6.3            </span></span>
974 
-<span><span class="co">##   [7] XVector_0.36.0            BiocNeighbors_1.14.0     </span></span>
975 
-<span><span class="co">##   [9] fs_1.5.2                  rstudioapi_0.14          </span></span>
976 
-<span><span class="co">##  [11] farver_2.1.1              ggrepel_0.9.1            </span></span>
977 
-<span><span class="co">##  [13] bit64_4.0.5               fansi_1.0.3              </span></span>
978 
-<span><span class="co">##  [15] xml2_1.3.3                codetools_0.2-18         </span></span>
979 
-<span><span class="co">##  [17] R.methodsS3_1.8.2         sparseMatrixStats_1.8.0  </span></span>
980 
-<span><span class="co">##  [19] cachem_1.0.6              knitr_1.40               </span></span>
981 
-<span><span class="co">##  [21] scater_1.24.0             jsonlite_1.8.0           </span></span>
982 
-<span><span class="co">##  [23] png_0.1-7                 R.oo_1.25.0              </span></span>
983 
-<span><span class="co">##  [25] HDF5Array_1.24.2          compiler_4.2.1           </span></span>
984 
-<span><span class="co">##  [27] httr_1.4.4                dqrng_0.3.0              </span></span>
985 
-<span><span class="co">##  [29] assertthat_0.2.1          fastmap_1.1.0            </span></span>
986 
-<span><span class="co">##  [31] limma_3.52.3              cli_3.4.0                </span></span>
987 
-<span><span class="co">##  [33] BiocSingular_1.12.0       htmltools_0.5.3          </span></span>
988 
-<span><span class="co">##  [35] tools_4.2.1               rsvd_1.0.5               </span></span>
989 
-<span><span class="co">##  [37] gtable_0.3.1              glue_1.6.2               </span></span>
990 
-<span><span class="co">##  [39] GenomeInfoDbData_1.2.8    rappdirs_0.3.3           </span></span>
991 
-<span><span class="co">##  [41] Rcpp_1.0.9                jquerylib_0.1.4          </span></span>
992 
-<span><span class="co">##  [43] pkgdown_2.0.6             vctrs_0.4.1              </span></span>
993 
-<span><span class="co">##  [45] rhdf5filters_1.8.0        svglite_2.1.0            </span></span>
994 
-<span><span class="co">##  [47] DelayedMatrixStats_1.18.0 xfun_0.33                </span></span>
995 
-<span><span class="co">##  [49] stringr_1.4.1             rvest_1.0.3              </span></span>
996 
-<span><span class="co">##  [51] beachmat_2.12.0           lifecycle_1.0.2          </span></span>
997 
-<span><span class="co">##  [53] irlba_2.3.5               gtools_3.9.3             </span></span>
998 
-<span><span class="co">##  [55] edgeR_3.38.4              zlibbioc_1.42.0          </span></span>
999 
-<span><span class="co">##  [57] scales_1.2.1              ragg_1.2.2               </span></span>
1000 
-<span><span class="co">##  [59] parallel_4.2.1            rhdf5_2.40.0             </span></span>
1001 
-<span><span class="co">##  [61] yaml_2.3.5                curl_4.3.2               </span></span>
1002 
-<span><span class="co">##  [63] memoise_2.0.1             reticulate_1.26          </span></span>
1003 
-<span><span class="co">##  [65] gridExtra_2.3             ggplot2_3.3.6            </span></span>
1004 
-<span><span class="co">##  [67] sass_0.4.2                stringi_1.7.8            </span></span>
1005 
-<span><span class="co">##  [69] RSQLite_2.2.17            highr_0.9                </span></span>
1006 
-<span><span class="co">##  [71] desc_1.4.2                ScaledMatrix_1.4.1       </span></span>
1007 
-<span><span class="co">##  [73] filelock_1.0.2            BiocParallel_1.30.3      </span></span>
1008 
-<span><span class="co">##  [75] rlang_1.0.5               pkgconfig_2.0.3          </span></span>
1009 
-<span><span class="co">##  [77] systemfonts_1.0.4         bitops_1.0-7             </span></span>
1010 
-<span><span class="co">##  [79] evaluate_0.16             lattice_0.20-45          </span></span>
1011 
-<span><span class="co">##  [81] purrr_0.3.4               Rhdf5lib_1.18.2          </span></span>
1012 
-<span><span class="co">##  [83] labeling_0.4.2            cowplot_1.1.1            </span></span>
1013 
-<span><span class="co">##  [85] bit_4.0.4                 tidyselect_1.1.2         </span></span>
1014 
-<span><span class="co">##  [87] magrittr_2.0.3            R6_2.5.1                 </span></span>
1015 
-<span><span class="co">##  [89] generics_0.1.3            fishpond_2.2.0           </span></span>
1016 
-<span><span class="co">##  [91] DBI_1.1.3                 withr_2.5.0              </span></span>
1017 
-<span><span class="co">##  [93] pillar_1.8.1              svMisc_1.2.3             </span></span>
1018 
-<span><span class="co">##  [95] RCurl_1.98-1.8            tibble_3.1.8             </span></span>
1019 
-<span><span class="co">##  [97] DropletUtils_1.16.0       utf8_1.2.2               </span></span>
1020 
-<span><span class="co">##  [99] rmarkdown_2.16            viridis_0.6.2            </span></span>
1021 
-<span><span class="co">## [101] locfit_1.5-9.6            grid_4.2.1               </span></span>
1022 
-<span><span class="co">## [103] blob_1.2.3                webshot_0.5.3            </span></span>
1023 
-<span><span class="co">## [105] digest_0.6.29             R.utils_2.12.0           </span></span>
1024 
-<span><span class="co">## [107] textshaping_0.3.6         munsell_0.5.0            </span></span>
1025 
-<span><span class="co">## [109] kableExtra_1.3.4          beeswarm_0.4.0           </span></span>
1026 
-<span><span class="co">## [111] viridisLite_0.4.1         vipor_0.4.5              </span></span>
1027 
-<span><span class="co">## [113] bslib_0.4.0</span></span></code></pre>
972 
+<span><span class="co">##   [3] rprojroot_2.0.3           GSVAdata_1.33.0          </span></span>
973 
+<span><span class="co">##   [5] scuttle_1.7.4             XVector_0.37.1           </span></span>
974 
+<span><span class="co">##   [7] BiocNeighbors_1.15.1      fs_1.5.2                 </span></span>
975 
+<span><span class="co">##   [9] rstudioapi_0.14           farver_2.1.1             </span></span>
976 
+<span><span class="co">##  [11] ggrepel_0.9.1             bit64_4.0.5              </span></span>
977 
+<span><span class="co">##  [13] fansi_1.0.3               xml2_1.3.3               </span></span>
978 
+<span><span class="co">##  [15] codetools_0.2-18          R.methodsS3_1.8.2        </span></span>
979 
+<span><span class="co">##  [17] sparseMatrixStats_1.9.0   cachem_1.0.6             </span></span>
980 
+<span><span class="co">##  [19] knitr_1.40                scater_1.25.7            </span></span>
981 
+<span><span class="co">##  [21] jsonlite_1.8.3            png_0.1-7                </span></span>
982 
+<span><span class="co">##  [23] R.oo_1.25.0               HDF5Array_1.25.2         </span></span>
983 
+<span><span class="co">##  [25] compiler_4.2.1            httr_1.4.4               </span></span>
984 
+<span><span class="co">##  [27] dqrng_0.3.0               assertthat_0.2.1         </span></span>
985 
+<span><span class="co">##  [29] fastmap_1.1.0             limma_3.53.10            </span></span>
986 
+<span><span class="co">##  [31] cli_3.4.1                 BiocSingular_1.13.1      </span></span>
987 
+<span><span class="co">##  [33] htmltools_0.5.3           tools_4.2.1              </span></span>
988 
+<span><span class="co">##  [35] rsvd_1.0.5                gtable_0.3.1             </span></span>
989 
+<span><span class="co">##  [37] glue_1.6.2                GenomeInfoDbData_1.2.9   </span></span>
990 
+<span><span class="co">##  [39] rappdirs_0.3.3            Rcpp_1.0.9               </span></span>
991 
+<span><span class="co">##  [41] jquerylib_0.1.4           pkgdown_2.0.6            </span></span>
992 
+<span><span class="co">##  [43] vctrs_0.5.0               rhdf5filters_1.9.0       </span></span>
993 
+<span><span class="co">##  [45] svglite_2.1.0             DelayedMatrixStats_1.19.2</span></span>
994 
+<span><span class="co">##  [47] xfun_0.34                 stringr_1.4.1            </span></span>
995 
+<span><span class="co">##  [49] rvest_1.0.3               beachmat_2.13.4          </span></span>
996 
+<span><span class="co">##  [51] lifecycle_1.0.3           irlba_2.3.5.1            </span></span>
997 
+<span><span class="co">##  [53] gtools_3.9.3              edgeR_3.39.6             </span></span>
998 
+<span><span class="co">##  [55] zlibbioc_1.43.0           scales_1.2.1             </span></span>
999 
+<span><span class="co">##  [57] ragg_1.2.4                parallel_4.2.1           </span></span>
1000 
+<span><span class="co">##  [59] rhdf5_2.41.1              yaml_2.3.6               </span></span>
1001 
+<span><span class="co">##  [61] curl_4.3.3                memoise_2.0.1            </span></span>
1002 
+<span><span class="co">##  [63] reticulate_1.26           gridExtra_2.3            </span></span>
1003 
+<span><span class="co">##  [65] ggplot2_3.3.6             sass_0.4.2               </span></span>
1004 
+<span><span class="co">##  [67] stringi_1.7.8             RSQLite_2.2.18           </span></span>
1005 
+<span><span class="co">##  [69] highr_0.9                 desc_1.4.2               </span></span>
1006 
+<span><span class="co">##  [71] ScaledMatrix_1.5.1        filelock_1.0.2           </span></span>
1007 
+<span><span class="co">##  [73] BiocParallel_1.31.14      rlang_1.0.6              </span></span>
1008 
+<span><span class="co">##  [75] pkgconfig_2.0.3           systemfonts_1.0.4        </span></span>
1009 
+<span><span class="co">##  [77] bitops_1.0-7              evaluate_0.17            </span></span>
1010 
+<span><span class="co">##  [79] lattice_0.20-45           purrr_0.3.5              </span></span>
1011 
+<span><span class="co">##  [81] Rhdf5lib_1.19.2           labeling_0.4.2           </span></span>
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+<span><span class="co">##  [83] cowplot_1.1.1             bit_4.0.4                </span></span>
1013 
+<span><span class="co">##  [85] tidyselect_1.2.0          magrittr_2.0.3           </span></span>
1014 
+<span><span class="co">##  [87] R6_2.5.1                  generics_0.1.3           </span></span>
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+<span><span class="co">##  [89] fishpond_2.3.21           DBI_1.1.3                </span></span>
1016 
+<span><span class="co">##  [91] pillar_1.8.1              withr_2.5.0              </span></span>
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+<span><span class="co">##  [93] svMisc_1.2.3              RCurl_1.98-1.9           </span></span>
1018 
+<span><span class="co">##  [95] tibble_3.1.8              DropletUtils_1.17.3      </span></span>
1019 
+<span><span class="co">##  [97] utf8_1.2.2                rmarkdown_2.17           </span></span>
1020 
+<span><span class="co">##  [99] viridis_0.6.2             locfit_1.5-9.6           </span></span>
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+<span><span class="co">## [101] grid_4.2.1                blob_1.2.3               </span></span>
1022 
+<span><span class="co">## [103] webshot_0.5.4             digest_0.6.30            </span></span>
1023 
+<span><span class="co">## [105] R.utils_2.12.0            textshaping_0.3.6        </span></span>
1024 
+<span><span class="co">## [107] munsell_0.5.0             kableExtra_1.3.4         </span></span>
1025 
+<span><span class="co">## [109] beeswarm_0.4.0            viridisLite_0.4.1        </span></span>
1026 
+<span><span class="co">## [111] vipor_0.4.5               bslib_0.4.0</span></span></code></pre>
1028 1027 
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422 422 
 <p>Here, we present some of the most basic operations on cell
423 
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424 
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425 
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426 426 
 <div class="sourceCode" id="cb1"><pre class="downlit sourceCode r">
427 427 
 <code class="sourceCode R"><span><span class="co"># Get a dataset</span></span>
428 428 
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430 430 
 <span></span>
431 431 
 <span><span class="co">## Add new information to SCE object</span></span>
432 432 
 <span><span class="va">n</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/seq.html" class="external-link">seq</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/nrow.html" class="external-link">ncol</a></span><span class="op">(</span><span class="va">sce</span><span class="op">)</span><span class="op">)</span> <span class="co"># A numeric vector of the same size as the number of cells</span></span>
433 
-<span><span class="fu">colData</span><span class="op">(</span><span class="va">sce</span><span class="op">)</span><span class="op">$</span><span class="va">n</span> <span class="op">&lt;-</span> <span class="va">n</span></span>
433 
+<span><span class="fu"><a href="https://rdrr.io/pkg/SummarizedExperiment/man/SummarizedExperiment-class.html" class="external-link">colData</a></span><span class="op">(</span><span class="va">sce</span><span class="op">)</span><span class="op">$</span><span class="va">n</span> <span class="op">&lt;-</span> <span class="va">n</span></span>
434 434 
 <span></span>
435 435 
 <span><span class="co">## Extract information from SCE</span></span>
436 
-<span><span class="va">barcodes</span> <span class="op">&lt;-</span> <span class="fu">colData</span><span class="op">(</span><span class="va">sce</span><span class="op">)</span><span class="op">$</span><span class="va">Barcode</span></span>
436 
+<span><span class="va">barcodes</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/pkg/SummarizedExperiment/man/SummarizedExperiment-class.html" class="external-link">colData</a></span><span class="op">(</span><span class="va">sce</span><span class="op">)</span><span class="op">$</span><span class="va">Barcode</span></span>
437 437 
 <span></span>
438 438 
 <span><span class="co">## Remove an annotation</span></span>
439 
-<span><span class="fu">colData</span><span class="op">(</span><span class="va">sce</span><span class="op">)</span><span class="op">$</span><span class="va">Tissue_status</span> <span class="op">&lt;-</span> <span class="cn">NULL</span></span></code></pre></div>
439 
+<span><span class="fu"><a href="https://rdrr.io/pkg/SummarizedExperiment/man/SummarizedExperiment-class.html" class="external-link">colData</a></span><span class="op">(</span><span class="va">sce</span><span class="op">)</span><span class="op">$</span><span class="va">Tissue_status</span> <span class="op">&lt;-</span> <span class="cn">NULL</span></span></code></pre></div>
440 440 
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441 441 
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442 442 
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464 464 
 <br><code>assayName</code>: name of the output normalized assay
465 465 
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466 466 
 </details><details><summary>Compute <b>Z-Score</b>:</summary><div class="sourceCode" id="cb7"><pre class="downlit sourceCode r">
467 
-<code class="sourceCode R"><span>  <span class="fu">assay</span><span class="op">(</span><span class="va">sce</span>, <span class="st">"countsZScore"</span><span class="op">)</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/computeZScore.html">computeZScore</a></span><span class="op">(</span>counts <span class="op">=</span> <span class="fu">assay</span><span class="op">(</span><span class="va">sce</span>, <span class="st">"counts"</span><span class="op">)</span><span class="op">)</span></span></code></pre></div>
467 
+<code class="sourceCode R"><span>  <span class="fu"><a href="https://rdrr.io/pkg/SummarizedExperiment/man/SummarizedExperiment-class.html" class="external-link">assay</a></span><span class="op">(</span><span class="va">sce</span>, <span class="st">"countsZScore"</span><span class="op">)</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/computeZScore.html">computeZScore</a></span><span class="op">(</span>counts <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/pkg/SummarizedExperiment/man/SummarizedExperiment-class.html" class="external-link">assay</a></span><span class="op">(</span><span class="va">sce</span>, <span class="st">"counts"</span><span class="op">)</span><span class="op">)</span></span></code></pre></div>
468 468 
 <p>The parameters to the above function include: <br><br><code>counts</code>: input matrix to scale with Z-Score <br><br></p>
469 469 
 </details><details><summary>Matrix <b>trimming</b>:</summary><div class="sourceCode" id="cb8"><pre class="downlit sourceCode r">
470 
-<code class="sourceCode R"><span>  <span class="fu">assay</span><span class="op">(</span><span class="va">sce</span>, <span class="st">"countsTrimmed"</span><span class="op">)</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/trimCounts.html">trimCounts</a></span><span class="op">(</span>counts <span class="op">=</span> <span class="fu">assay</span><span class="op">(</span><span class="va">sce</span>, <span class="st">"counts"</span><span class="op">)</span>, trimValue <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fl">10</span>, <span class="op">-</span><span class="fl">10</span><span class="op">)</span><span class="op">)</span></span></code></pre></div>
470 
+<code class="sourceCode R"><span>  <span class="fu"><a href="https://rdrr.io/pkg/SummarizedExperiment/man/SummarizedExperiment-class.html" class="external-link">assay</a></span><span class="op">(</span><span class="va">sce</span>, <span class="st">"countsTrimmed"</span><span class="op">)</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/trimCounts.html">trimCounts</a></span><span class="op">(</span>counts <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/pkg/SummarizedExperiment/man/SummarizedExperiment-class.html" class="external-link">assay</a></span><span class="op">(</span><span class="va">sce</span>, <span class="st">"counts"</span><span class="op">)</span>, trimValue <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fl">10</span>, <span class="op">-</span><span class="fl">10</span><span class="op">)</span><span class="op">)</span></span></code></pre></div>
471 471 
 <p>The parameters to the above function include: <br><br><code>counts</code>: an input <code>SingleCellExperiment</code> object
472 472 
 <br><code>trimValue</code>: a <code>numeric(2)</code> vector with the
473 473 
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