@@ -9,3 +9,5 @@ manuscript/

 ^_pkgdown\.yml$

 ^docs$

 ^pkgdown$

+.ignore

+README.Rmd

@@ -4,9 +4,11 @@ export(ContigCellDB)

 export(ContigCellDB_10XVDJ)

 export(canonicalize_by_chain)

 export(canonicalize_by_prevalence)

-export(canonicalize_by_subset)

+export(canonicalize_cell)

+export(canonicalize_cluster)

 export(cdhit)

 export(cdhit_ccdb)

+export(cluster_germline)

 export(cluster_permute_test)

 export(entropy)

 export(enumerate_pairing)

@@ -17,6 +19,7 @@ export(ig_chain_recode)

 export(modal_category)

 export(np)

 export(pairing_tables)

+export(purity)

 export(tcr_chain_recode)

 exportMethods("$")

 exportMethods("$<-")

@@ -1,6 +1,5 @@

 # To Document

 # primary_keys, primary_keys<- -- use `$` to access/replace. Table not checked for validity, but I think should be?

-# canonicalize contigs on cells

 # subset (subset a table, then equalize...)

@@ -69,12 +68,12 @@ ContigCellDB_10XVDJ = function(contig_tbl, contig_pk = c('barcode', 'contig_id')

     ContigCellDB(contig_tbl = contig_tbl, contig_pk = contig_pk, cell_pk = cell_pk)

 }

-#' Creat a method for ContigCellDB object to access its slots

+#' Access public members of ContigCellDB object

 #'

 #' @param x A ContigCellDB object

 #' @param name a slot of a ContigCellDB object (one of  `c('contig_tbl', 'cell_tbl', 'contig_pk', 'cell_pk', 'cluster_tbl', 'cluster_pk')`)

 #'

-#' @return Slots of ContigCellDB

+#' @return Slot of ContigCellDB

 #' @export

 #'

 #' @examples

@@ -89,7 +88,7 @@ setMethod("$", signature = c(x = 'ContigCellDB'), function(x, name){

     }

 })

-#' Create a function of ContigCellDB object to replace values of its slots

+#' Access public members of ContigCellDB object

 #'

 #' @param x A ContigCellDB object

 #' @param name Name of a slot for a ContigCellDB object (one of  `c('contig_tbl', 'cell_tbl', 'contig_pk', 'cell_pk', 'cluster_tbl', 'cluster_pk')`)

@@ -147,7 +146,7 @@ equalize_ccdb = function(x){

 replace_cluster_tbl = function(ccdb, cluster_tbl, contig_tbl, cluster_pk){

     if(nrow(ccdb$cluster_tbl)>0 && !missing(cluster_pk)){

-        warning("Replacing `cluster_tbl` with key ccdb$cluster_pk")

+        warning("Replacing `cluster_tbl` with ", paste(ccdb$cluster_pk, sep = ', ', '.'))

     }

     if(!missing(cluster_pk)) ccdb$cluster_pk = cluster_pk

     ccdb@cluster_tbl = cluster_tbl

new file mode 100644

@@ -0,0 +1,55 @@

+---

+output: github_document

+---

+

+<!-- README.md is generated from README.Rmd. Please edit that file -->

+

+```{r, echo = FALSE}

+knitr::opts_chunk$set(

+  collapse = TRUE,

+  comment = "#>",

+  fig.path = "man/figures/"

+)

+```

+

+# CellaRepertorium

+

+This package contains methods for clustering and analyzing single cell RepSeq data, especially as generated by [10X genomics VDJ solution](https://support.10xgenomics.com/single-cell-vdj).

+

+## Installation

+

+```

+devtools::install_github('amcdavid/CellaRepertorium')

+```

+

+Requires R >= 3.5.

+

+## Data requirements and package structure

+

+The fundamental unit this package operates on is the **contig**, which is a section of contiguously stitched reads from a single **cell**.  Each contig belongs to one (and only one) cell, however, cells generate multiple contigs.  

+

+```{r, echo = FALSE}

+knitr::include_graphics('vignettes/figure/contig_schematic.png')

+```

+

+Contigs can also belong to a **cluster**.  Because of these two many-to-one mappings, these data can be thought as a series of ragged arrays.  The links between them mean they are relational data. A `ContigCellDB` object wraps each of these objects as a sequence of three `data.frames` (well, `tibbles`, actually).   `ContigCellDB` also tracks columns (the primary keys) that unique identify each row in each of these tables.  The `contig_tbl` is the `tibble` containing **contigs**, the `cell_tbl` contains the **cells**, and the `cluster_tbl` contains the **clusters**.  

+

+The `contig_pk`, `cell_pk` and `cluster_pk` identify the columns that identify a contig, cell and cluster, respectively.  These will serve as foreign keys that link the three tables together.

+The tables are kept in sync so that subsetting the contigs will subset the cells, and clusters, and vice-versa.

+

+```{r, echo = FALSE}

+knitr::include_graphics('vignettes/figure/table_schematic.png')

+```

+

+Of course, each of these tables can contain many other columns that will serve as covariates for various analyses, such as the CDR3 sequence, or the identity of the V, D and J regions.  Various derived quantities that describe cells and clusters can also be calculated, and added to these tables, such as the medoid of a cluster --  a contig that  minimizes the average distance to all other clusters. 

+

+## Functions

+

+[a screencap of something interesting?]

+

+*  `cdhit_ccdb`: An R interface to CDhit, which was originally ported by Thomas Lin Pedersen.

+*  `fine_clustering`: clustering CDR3 by edit distances (possibly using empirical amino acid substitution matrices)

+*  `cluster_permute_test`: permutation tests of cluster statistics

+*  `pairing_tables`: Generate pairings of contigs within each cell in a way that they can be plotted

+

+

@@ -1,34 +1,60 @@

+

+<!-- README.md is generated from README.Rmd. Please edit that file -->

+

 # CellaRepertorium

-This package contains methods for clustering and analyzing single cell RepSeq data, especially as generated by [10X genomics VDJ solution](https://support.10xgenomics.com/single-cell-vdj).

+This package contains methods for clustering and analyzing single cell

+RepSeq data, especially as generated by [10X genomics VDJ

+solution](https://support.10xgenomics.com/single-cell-vdj).

 ## Installation

-```

-devtools::install_github('amcdavid/CellaRepertorium')

-```

+    devtools::install_github('amcdavid/CellaRepertorium')

-Requires R>=3.5.

+Requires R \>= 3.5.

 ## Data requirements and package structure

-The fundamental unit is the **contig**, which is a section of contiguously stitched reads from a single **cell**.  Each contig belongs to one (and only one) cell, however, cells generate multiple contigs.  Contigs can also belong to a **cluster**.  Because of these two many-to-one mappings, these data can be thought as a series of ragged arrays.  The links between them mean they are relational data.

-

-[A schematic of contigs and cells should go here]

-

-A `ContigCellDB` object wraps each of these objects as a sequence of three `data.frame`s (well, `tibble`s, actually).   `ContigCellDB` also tracks columns (keys) that unique identify each row in each of these tables.  The `contig_tbl` is the `tibble` containing **contigs**, the `cell_tbl` contains the **cells**, and the `cluster_tbl` contains the **clusters**.  The `contig_pk`, `cell_pk` and `cluster_pk` identify the columns that identify a contig, cell and cluster, respectively, and must be unique in each of the respective tables.

-The tables are kept in sync so that subsetting the contigs will subset the cells, and clusters, and vice-versa.

-

-[A schematic showing table relations should go here]

-

-Of course, each of these tables can contain many other columns that will serve as covariates for various analysis, such as the CDR3 sequence, or the identity of the V, D and J regions.  Various derived quantities that describe cells and clusters can also be calculated, and added to these tables, such as the medoid of a cluster.

+The fundamental unit this package operates on is the **contig**, which

+is a section of contiguously stitched reads from a single **cell**. Each

+contig belongs to one (and only one) cell, however, cells generate

+multiple contigs.

+

+![](vignettes/figure/contig_schematic.png)<!-- -->

+

+Contigs can also belong to a **cluster**. Because of these two

+many-to-one mappings, these data can be thought as a series of ragged

+arrays. The links between them mean they are relational data. A

+`ContigCellDB` object wraps each of these objects as a sequence of three

+`data.frames` (well, `tibbles`, actually). `ContigCellDB` also tracks

+columns (the primary keys) that unique identify each row in each of

+these tables. The `contig_tbl` is the `tibble` containing **contigs**,

+the `cell_tbl` contains the **cells**, and the `cluster_tbl` contains

+the **clusters**.

+

+The `contig_pk`, `cell_pk` and `cluster_pk` identify the columns that

+identify a contig, cell and cluster, respectively. These will serve as

+foreign keys that link the three tables together. The tables are kept in

+sync so that subsetting the contigs will subset the cells, and clusters,

+and vice-versa.

+

+![](vignettes/figure/table_schematic.png)<!-- -->

+

+Of course, each of these tables can contain many other columns that will

+serve as covariates for various analyses, such as the CDR3 sequence, or

+the identity of the V, D and J regions. Various derived quantities that

+describe cells and clusters can also be calculated, and added to these

+tables, such as the medoid of a cluster – a contig that minimizes the

+average distance to all other clusters.

 ## Functions

-[a screencap of something interesting?]

-

-*  `cdhit`: An R interface to CDhit, which was originally ported by Thomas Lin Pedersen.

-*  `fine_cluster`: clustering CDR3 by edit distances (possibly using empirical amino acid substitution matrices)

-*  `cluster_permute_test`: permutation tests of cluster statistics

-

+\[a screencap of something interesting?\]

+  - `cdhit_ccdb`: An R interface to CDhit, which was originally ported

+    by Thomas Lin Pedersen.

+  - `fine_clustering`: clustering CDR3 by edit distances (possibly using

+    empirical amino acid substitution matrices)

+  - `cluster_permute_test`: permutation tests of cluster statistics

+  - `pairing_tables`: Generate pairings of contigs within each cell in a

+    way that they can be plotted

@@ -1 +1,41 @@

 destination: docs

+

+reference:

+- title: Constuction and modification

+  desc: "Functions to construct and modify a ContigCellDB"

+  contents:

+   - '`ContigCellDB`'

+   - '`$,ContigCellDB-method`'

+   - '`$<-,ContigCellDB-method`'

+- title: Clustering

+  desc: "Methods to cluster contigs"

+  contents:

+   - '`cluster_germline`'

+   - '`fine_clustering`'

+   - '`cdhit`'

+   - '`pairing_tables`'

+- title: Canonicalization

+  desc: "Methods to return single contigs for cells or clusters"

+  contents:

+   - '`canonicalize_cell`'

+   - '`canonicalize_cluster`'

+- title: Statistical testing

+  contents:

+   - '`cluster_permute_test`'

+   - '`purity`'

+- title: Datasets

+  contents:

+   - '`ccdb_ex`'

+   - '`contigs_qc`'

+   - '`canonicalize_by_prevalence`'

+- title: Internal or WIP

+  desc: "Functions that may be made internal, removed, or with interfaces subject to change."

+  contents:

+  - '`cluster_germline`'

+  - '`cluster_permute_test`'

+  - '`.cluster_permute_test`'

+  - '`entropy`'

+  - '`ig_chain_recode`'

+  - '`fancy_name_contigs`'

+  - '`fine_cluster_seqs`'

+  - '`get_canonical_representative`'

@@ -90,27 +90,26 @@

-<div class="sourceCode" id="cb1"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb1-1" data-line-number="1"><span class="co">#load_all()</span></a>

-<a class="sourceLine" id="cb1-2" data-line-number="2"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/library">library</a></span>(CellaRepertorium)</a>

-<a class="sourceLine" id="cb1-3" data-line-number="3"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/library">library</a></span>(dplyr)</a>

-<a class="sourceLine" id="cb1-4" data-line-number="4"><span class="co">#&gt; </span></a>

-<a class="sourceLine" id="cb1-5" data-line-number="5"><span class="co">#&gt; Attaching package: 'dplyr'</span></a>

-<a class="sourceLine" id="cb1-6" data-line-number="6"><span class="co">#&gt; The following objects are masked from 'package:stats':</span></a>

-<a class="sourceLine" id="cb1-7" data-line-number="7"><span class="co">#&gt; </span></a>

-<a class="sourceLine" id="cb1-8" data-line-number="8"><span class="co">#&gt;     filter, lag</span></a>

-<a class="sourceLine" id="cb1-9" data-line-number="9"><span class="co">#&gt; The following objects are masked from 'package:base':</span></a>

-<a class="sourceLine" id="cb1-10" data-line-number="10"><span class="co">#&gt; </span></a>

-<a class="sourceLine" id="cb1-11" data-line-number="11"><span class="co">#&gt;     intersect, setdiff, setequal, union</span></a>

-<a class="sourceLine" id="cb1-12" data-line-number="12"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/library">library</a></span>(ggplot2)</a>

-<a class="sourceLine" id="cb1-13" data-line-number="13"><span class="co">#&gt; Registered S3 methods overwritten by 'ggplot2':</span></a>

-<a class="sourceLine" id="cb1-14" data-line-number="14"><span class="co">#&gt;   method         from </span></a>

-<a class="sourceLine" id="cb1-15" data-line-number="15"><span class="co">#&gt;   [.quosures     rlang</span></a>

-<a class="sourceLine" id="cb1-16" data-line-number="16"><span class="co">#&gt;   c.quosures     rlang</span></a>

-<a class="sourceLine" id="cb1-17" data-line-number="17"><span class="co">#&gt;   print.quosures rlang</span></a>

-<a class="sourceLine" id="cb1-18" data-line-number="18"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/library">library</a></span>(readr)</a>

-<a class="sourceLine" id="cb1-19" data-line-number="19"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/library">library</a></span>(tidyr)</a>

-<a class="sourceLine" id="cb1-20" data-line-number="20"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/library">library</a></span>(stringr)</a>

-<a class="sourceLine" id="cb1-21" data-line-number="21"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/library">library</a></span>(purrr)</a></code></pre></div>

+<div class="sourceCode" id="cb1"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb1-1" data-line-number="1"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/library">library</a></span>(CellaRepertorium)</a>

+<a class="sourceLine" id="cb1-2" data-line-number="2"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/library">library</a></span>(dplyr)</a>

+<a class="sourceLine" id="cb1-3" data-line-number="3"><span class="co">#&gt; </span></a>

+<a class="sourceLine" id="cb1-4" data-line-number="4"><span class="co">#&gt; Attaching package: 'dplyr'</span></a>

+<a class="sourceLine" id="cb1-5" data-line-number="5"><span class="co">#&gt; The following objects are masked from 'package:stats':</span></a>

+<a class="sourceLine" id="cb1-6" data-line-number="6"><span class="co">#&gt; </span></a>

+<a class="sourceLine" id="cb1-7" data-line-number="7"><span class="co">#&gt;     filter, lag</span></a>

+<a class="sourceLine" id="cb1-8" data-line-number="8"><span class="co">#&gt; The following objects are masked from 'package:base':</span></a>

+<a class="sourceLine" id="cb1-9" data-line-number="9"><span class="co">#&gt; </span></a>

+<a class="sourceLine" id="cb1-10" data-line-number="10"><span class="co">#&gt;     intersect, setdiff, setequal, union</span></a>

+<a class="sourceLine" id="cb1-11" data-line-number="11"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/library">library</a></span>(ggplot2)</a>

+<a class="sourceLine" id="cb1-12" data-line-number="12"><span class="co">#&gt; Registered S3 methods overwritten by 'ggplot2':</span></a>

+<a class="sourceLine" id="cb1-13" data-line-number="13"><span class="co">#&gt;   method         from </span></a>

+<a class="sourceLine" id="cb1-14" data-line-number="14"><span class="co">#&gt;   [.quosures     rlang</span></a>

+<a class="sourceLine" id="cb1-15" data-line-number="15"><span class="co">#&gt;   c.quosures     rlang</span></a>

+<a class="sourceLine" id="cb1-16" data-line-number="16"><span class="co">#&gt;   print.quosures rlang</span></a>

+<a class="sourceLine" id="cb1-17" data-line-number="17"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/library">library</a></span>(readr)</a>

+<a class="sourceLine" id="cb1-18" data-line-number="18"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/library">library</a></span>(tidyr)</a>

+<a class="sourceLine" id="cb1-19" data-line-number="19"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/library">library</a></span>(stringr)</a>

+<a class="sourceLine" id="cb1-20" data-line-number="20"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/library">library</a></span>(purrr)</a></code></pre></div>

 <div id="load-filtered-contig-files" class="section level1">

 <h1 class="hasAnchor">

 <a href="#load-filtered-contig-files" class="anchor"></a>Load filtered contig files</h1>

@@ -160,10 +159,14 @@

 <a class="sourceLine" id="cb5-6" data-line-number="6"><span class="co">#&gt; `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.</span></a></code></pre></div>

 <p><img src="cdr3_clustering_files/figure-html/unnamed-chunk-5-1.png" width="700"></p>

 <p>We can also cluster by DNA identity.</p>

-<div class="sourceCode" id="cb6"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb6-1" data-line-number="1">germline_cluster =<span class="st"> </span>CellaRepertorium<span class="op">:::</span><span class="kw">cluster_germline</span>(cdb, <span class="dt">segment_keys =</span> <span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/c">c</a></span>(<span class="st">'v_gene'</span>, <span class="st">'j_gene'</span>, <span class="st">'chain'</span>), <span class="dt">cluster_name =</span> <span class="st">'segment_idx'</span>)</a>

+</div>

+<div id="cluster-by-v-j-identity" class="section level1">

+<h1 class="hasAnchor">

+<a href="#cluster-by-v-j-identity" class="anchor"></a>Cluster by V-J identity</h1>

+<div class="sourceCode" id="cb6"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb6-1" data-line-number="1">germline_cluster =<span class="st"> </span>CellaRepertorium<span class="op">:::</span><span class="kw"><a href="../reference/cluster_germline.html">cluster_germline</a></span>(cdb, <span class="dt">segment_keys =</span> <span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/c">c</a></span>(<span class="st">'v_gene'</span>, <span class="st">'j_gene'</span>, <span class="st">'chain'</span>), <span class="dt">cluster_name =</span> <span class="st">'segment_idx'</span>)</a>

 <a class="sourceLine" id="cb6-2" data-line-number="2"><span class="co">#&gt; Warning in replace_cluster_tbl(ccdb, cluster_tbl, cl_con_tbl, cluster_pk =</span></a>

-<a class="sourceLine" id="cb6-3" data-line-number="3"><span class="co">#&gt; cluster_name): Replacing `cluster_tbl` with key ccdb$cluster_pk</span></a></code></pre></div>

-<p>And by other features of the contigs. Here we cluster each contig based on the chain and V-J genes. This gives us the set of observed V-J pairings:</p>

+<a class="sourceLine" id="cb6-3" data-line-number="3"><span class="co">#&gt; cluster_name): Replacing `cluster_tbl` with DNA97, .</span></a></code></pre></div>

+<p>We can cluster by any other feature of the contigs. Here we cluster each contig based on the chain and V-J genes. This gives us the set of observed V-J pairings:</p>

 <div class="sourceCode" id="cb7"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb7-1" data-line-number="1">germline_cluster =<span class="st"> </span><span class="kw"><a href="../reference/fine_clustering.html">fine_clustering</a></span>(germline_cluster, <span class="dt">sequence_key =</span> <span class="st">'cdr3_nt'</span>, <span class="dt">type =</span> <span class="st">'DNA'</span>)</a>

 <a class="sourceLine" id="cb7-2" data-line-number="2"><span class="co">#&gt; Calculating intradistances on 700 clusters.</span></a>

 <a class="sourceLine" id="cb7-3" data-line-number="3"><span class="co">#&gt; Summarizing</span></a>

@@ -176,6 +179,10 @@

 <div class="sourceCode" id="cb8"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb8-1" data-line-number="1"><span class="kw"><a href="https://ggplot2.tidyverse.org/reference/ggplot.html">ggplot</a></span>(germline_cluster<span class="op">$</span>cluster_tbl <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/filter.html">filter</a></span>(chain <span class="op">==</span><span class="st"> 'TRB'</span>), <span class="kw"><a href="https://ggplot2.tidyverse.org/reference/aes.html">aes</a></span>(<span class="dt">x =</span> v_gene, <span class="dt">y =</span> j_gene, <span class="dt">fill =</span> avg_distance)) <span class="op">+</span><span class="st"> </span><span class="kw"><a href="https://ggplot2.tidyverse.org/reference/geom_tile.html">geom_tile</a></span>() <span class="op">+</span><span class="st"> </span><span class="kw"><a href="https://ggplot2.tidyverse.org/reference/theme.html">theme</a></span>(<span class="dt">axis.text.x =</span> <span class="kw"><a href="https://ggplot2.tidyverse.org/reference/element.html">element_text</a></span>(<span class="dt">angle =</span> <span class="dv">90</span>))</a></code></pre></div>

 <p><img src="cdr3_clustering_files/figure-html/unnamed-chunk-8-1.png" width="700"></p>

 <p>Average Levenstein distance of CDR3 within each pair</p>

+</div>

+<div id="some-simple-phylogenetic-relationship" class="section level1">

+<h1 class="hasAnchor">

+<a href="#some-simple-phylogenetic-relationship" class="anchor"></a>Some simple phylogenetic relationship</h1>

 <div class="sourceCode" id="cb9"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb9-1" data-line-number="1"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/library">library</a></span>(ggdendro)</a>

 <a class="sourceLine" id="cb9-2" data-line-number="2"></a>

 <a class="sourceLine" id="cb9-3" data-line-number="3"><span class="co"># This should be turned into a function in the package somehow</span></a>

@@ -205,7 +212,7 @@

 <pre><code>#&gt; 

 #&gt; [[4]]</code></pre>

 <p><img src="cdr3_clustering_files/figure-html/unnamed-chunk-9-4.png" width="700"></p>

-<div class="sourceCode" id="cb13"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb13-1" data-line-number="1">aa80 =<span class="st"> </span>CellaRepertorium<span class="op">:::</span><span class="kw">canonicalize_cluster</span>(aa80, <span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/c">c</a></span>(<span class="st">'cdr3'</span>), <span class="dt">contig_fields =</span> <span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/c">c</a></span>(<span class="st">'cdr3'</span>, <span class="st">'cdr3_nt'</span>, <span class="st">'chain'</span>, <span class="st">'v_gene'</span>, <span class="st">'d_gene'</span>, <span class="st">'j_gene'</span>))</a></code></pre></div>

+<div class="sourceCode" id="cb13"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb13-1" data-line-number="1">aa80 =<span class="st"> </span><span class="kw"><a href="../reference/canonicalize_cluster.html">canonicalize_cluster</a></span>(aa80, <span class="dt">representative =</span> <span class="st">'cdr3'</span>, <span class="dt">contig_fields =</span> <span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/c">c</a></span>(<span class="st">'cdr3'</span>, <span class="st">'cdr3_nt'</span>, <span class="st">'chain'</span>, <span class="st">'v_gene'</span>, <span class="st">'d_gene'</span>, <span class="st">'j_gene'</span>))</a></code></pre></div>

 <p>Pull the fields listed in <code>contig_fields</code> into the <code>cluster_tbl</code>, using the values found in the medoid contig</p>

 <div class="sourceCode" id="cb14"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb14-1" data-line-number="1">oligo_clusters =<span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/filter.html">filter</a></span>(aa80<span class="op">$</span>cluster_tbl, n_cluster <span class="op">&gt;=</span><span class="st"> </span>MIN_OLIGO)</a>

 <a class="sourceLine" id="cb14-2" data-line-number="2">oligo_contigs =<span class="st"> </span>aa80</a>

@@ -304,47 +311,59 @@

 <a class="sourceLine" id="cb18-9" data-line-number="9"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/stopifnot">stopifnot</a></span>( <span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/all">all</a></span>(<span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/colSums">colSums</a></span>(<span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/with">with</a></span>(oligo_cluster_stat, <span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/table">table</a></span>(chain, cluster_idx)) <span class="op">&gt;</span><span class="st"> </span><span class="dv">0</span>) <span class="op">==</span><span class="st"> </span><span class="dv">1</span>))</a>

 <a class="sourceLine" id="cb18-10" data-line-number="10"></a>

 <a class="sourceLine" id="cb18-11" data-line-number="11">mm_out =<span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/warning">suppressWarnings</a></span>(oligo_cluster_stat <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/group_by.html">group_by</a></span>(cluster_idx, chain) <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/do.html">do</a></span>( <span class="kw"><a href="https://www.rdocumentation.org/packages/lme4/topics/glmer">glmer</a></span>(<span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/cbind">cbind</a></span>(n_cluster, total_cells) <span class="op">~</span><span class="st"> </span>pop <span class="op">+</span><span class="st"> </span>weeks_premature <span class="op">+</span><span class="st"> </span>(<span class="dv">1</span><span class="op">|</span>sample), <span class="dt">data =</span> ., <span class="dt">family =</span> <span class="st">'binomial'</span>) <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/broom/topics/reexports">tidy</a></span>(<span class="dt">conf.int =</span> <span class="ot">TRUE</span>)))</a></code></pre></div>

-<div class="sourceCode" id="cb19"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb19-1" data-line-number="1">mm_outj =<span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/filter.html">filter</a></span>(<span class="kw"><a href="https://dplyr.tidyverse.org/reference/join.html">left_join</a></span>(<span class="kw"><a href="https://dplyr.tidyverse.org/reference/group_by.html">ungroup</a></span>(mm_out), <span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/unique">unique</a></span>(oligo_clusters_all <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span>(cdr3_representative, cluster_idx))), term <span class="op">%in%</span><span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/c">c</a></span>(<span class="st">'popCD31Pos'</span>, <span class="st">'weeks_premature'</span>)) <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/mutate.html">mutate</a></span>(<span class="dt">ci_lo =</span> AMmisc<span class="op">::</span><span class="kw"><a href="https://www.rdocumentation.org/packages/AMmisc/topics/clamp">clamp</a></span>(conf.low), <span class="dt">ci_hi =</span> AMmisc<span class="op">::</span><span class="kw"><a href="https://www.rdocumentation.org/packages/AMmisc/topics/clamp">clamp</a></span>(conf.high)) <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/arrange.html">arrange</a></span>(<span class="kw"><a href="https://dplyr.tidyverse.org/reference/desc.html">desc</a></span>(cdr3_representative))</a>

+<div class="sourceCode" id="cb19"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb19-1" data-line-number="1">mm_outj =<span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/filter.html">filter</a></span>(<span class="kw"><a href="https://dplyr.tidyverse.org/reference/join.html">left_join</a></span>(<span class="kw"><a href="https://dplyr.tidyverse.org/reference/group_by.html">ungroup</a></span>(mm_out), <span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/unique">unique</a></span>(oligo_clusters_all <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span>(representative, cluster_idx))), term <span class="op">%in%</span><span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/c">c</a></span>(<span class="st">'popCD31Pos'</span>, <span class="st">'weeks_premature'</span>)) <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/mutate.html">mutate</a></span>(<span class="dt">ci_lo =</span> AMmisc<span class="op">::</span><span class="kw"><a href="https://www.rdocumentation.org/packages/AMmisc/topics/clamp">clamp</a></span>(conf.low), <span class="dt">ci_hi =</span> AMmisc<span class="op">::</span><span class="kw"><a href="https://www.rdocumentation.org/packages/AMmisc/topics/clamp">clamp</a></span>(conf.high)) <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/arrange.html">arrange</a></span>(<span class="kw"><a href="https://dplyr.tidyverse.org/reference/desc.html">desc</a></span>(representative))</a>

 <a class="sourceLine" id="cb19-2" data-line-number="2"></a>

-<a class="sourceLine" id="cb19-3" data-line-number="3"><span class="kw"><a href="https://ggplot2.tidyverse.org/reference/ggplot.html">ggplot</a></span>(mm_outj, <span class="kw"><a href="https://ggplot2.tidyverse.org/reference/aes.html">aes</a></span>(<span class="dt">x =</span> cdr3_representative, <span class="dt">ymin =</span> ci_lo, <span class="dt">ymax =</span> ci_hi, <span class="dt">y =</span> <span class="kw">clamp</span>(estimate))) <span class="op">+</span><span class="st"> </span><span class="kw"><a href="https://ggplot2.tidyverse.org/reference/geom_linerange.html">geom_pointrange</a></span>() <span class="op">+</span><span class="st"> </span><span class="kw"><a href="https://ggplot2.tidyverse.org/reference/facet_wrap.html">facet_wrap</a></span>(<span class="op">~</span>term, <span class="dt">scales =</span> <span class="st">'free'</span>) <span class="op">+</span><span class="st"> </span><span class="kw"><a href="https://ggplot2.tidyverse.org/reference/coord_flip.html">coord_flip</a></span>() <span class="op">+</span><span class="st"> </span><span class="kw"><a href="https://ggplot2.tidyverse.org/reference/ggtheme.html">theme_minimal</a></span>() <span class="op">+</span><span class="st"> </span><span class="kw"><a href="https://ggplot2.tidyverse.org/reference/geom_abline.html">geom_hline</a></span>(<span class="dt">yintercept =</span> <span class="dv">0</span>, <span class="dt">lty =</span> <span class="dv">2</span>) <span class="op">+</span><span class="st"> </span><span class="kw"><a href="https://ggplot2.tidyverse.org/reference/labs.html">xlab</a></span>(<span class="st">"Isomorph"</span>) <span class="op">+</span><span class="st"> </span><span class="kw"><a href="https://ggplot2.tidyverse.org/reference/labs.html">ylab</a></span>(<span class="st">"log odds of isomorph"</span>)</a></code></pre></div>

+<a class="sourceLine" id="cb19-3" data-line-number="3"><span class="kw"><a href="https://ggplot2.tidyverse.org/reference/ggplot.html">ggplot</a></span>(mm_outj, <span class="kw"><a href="https://ggplot2.tidyverse.org/reference/aes.html">aes</a></span>(<span class="dt">x =</span> representative, <span class="dt">ymin =</span> ci_lo, <span class="dt">ymax =</span> ci_hi, <span class="dt">y =</span> <span class="kw">clamp</span>(estimate))) <span class="op">+</span><span class="st"> </span><span class="kw"><a href="https://ggplot2.tidyverse.org/reference/geom_linerange.html">geom_pointrange</a></span>() <span class="op">+</span><span class="st"> </span><span class="kw"><a href="https://ggplot2.tidyverse.org/reference/facet_wrap.html">facet_wrap</a></span>(<span class="op">~</span>term, <span class="dt">scales =</span> <span class="st">'free'</span>) <span class="op">+</span><span class="st"> </span><span class="kw"><a href="https://ggplot2.tidyverse.org/reference/coord_flip.html">coord_flip</a></span>() <span class="op">+</span><span class="st"> </span><span class="kw"><a href="https://ggplot2.tidyverse.org/reference/ggtheme.html">theme_minimal</a></span>() <span class="op">+</span><span class="st"> </span><span class="kw"><a href="https://ggplot2.tidyverse.org/reference/geom_abline.html">geom_hline</a></span>(<span class="dt">yintercept =</span> <span class="dv">0</span>, <span class="dt">lty =</span> <span class="dv">2</span>) <span class="op">+</span><span class="st"> </span><span class="kw"><a href="https://ggplot2.tidyverse.org/reference/labs.html">xlab</a></span>(<span class="st">"Isomorph"</span>) <span class="op">+</span><span class="st"> </span><span class="kw"><a href="https://ggplot2.tidyverse.org/reference/labs.html">ylab</a></span>(<span class="st">"log odds of isomorph"</span>)</a></code></pre></div>

 <p>We test if the binomial rate of clone expression differs between CD31+/- or term, for each clone.</p>

 </div>

 <div id="clonal-pairs" class="section level1">

 <h1 class="hasAnchor">

 <a href="#clonal-pairs" class="anchor"></a>Clonal pairs</h1>

-<div class="sourceCode" id="cb20"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb20-1" data-line-number="1">class_colors =<span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/reexports.html">data_frame</a></span>(<span class="dt">chain =</span>  <span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/unique">unique</a></span>(aa80<span class="op">$</span>cluster_tbl<span class="op">$</span>chain)) <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/mutate.html">mutate</a></span>(<span class="dt">class_color =</span>  RColorBrewer<span class="op">::</span><span class="kw"><a href="https://www.rdocumentation.org/packages/RColorBrewer/topics/ColorBrewer">brewer.pal</a></span>(<span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/length">length</a></span>(chain),<span class="st">"Set1"</span>)[<span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/seq">seq_along</a></span>(chain)])</a>

-<a class="sourceLine" id="cb20-2" data-line-number="2"><span class="co">#&gt; Warning: `data_frame()` is deprecated, use `tibble()`.</span></a>

-<a class="sourceLine" id="cb20-3" data-line-number="3"><span class="co">#&gt; This warning is displayed once per session.</span></a>

-<a class="sourceLine" id="cb20-4" data-line-number="4"><span class="co">#&gt; Warning in RColorBrewer::brewer.pal(length(chain), "Set1"): minimal value for n is 3, returning requested palette with 3 different levels</span></a>

-<a class="sourceLine" id="cb20-5" data-line-number="5"></a>

-<a class="sourceLine" id="cb20-6" data-line-number="6">aa80<span class="op">$</span>cluster_pk =<span class="st"> 'representative'</span></a>

-<a class="sourceLine" id="cb20-7" data-line-number="7">pairing_list =<span class="st"> </span><span class="kw"><a href="../reference/pairing_tables.html">pairing_tables</a></span>(aa80, <span class="dt">table_order =</span> <span class="dv">2</span>, <span class="dt">orphan_level =</span> <span class="dv">1</span>, <span class="dt">min_expansion =</span> <span class="dv">2</span>, <span class="dt">cluster_keys =</span> <span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/c">c</a></span>(<span class="st">'cdr3'</span>, <span class="st">'representative'</span>, <span class="st">'chain'</span>, <span class="st">'v_gene'</span>, <span class="st">'j_gene'</span>, <span class="st">'avg_distance'</span>))</a>

-<a class="sourceLine" id="cb20-8" data-line-number="8"><span class="co">#&gt; Warning: Factor `cluster_idx.2` contains implicit NA, consider using</span></a>

-<a class="sourceLine" id="cb20-9" data-line-number="9"><span class="co">#&gt; `forcats::fct_explicit_na`</span></a>

-<a class="sourceLine" id="cb20-10" data-line-number="10"><span class="co">#&gt; Warning: Column `representative` joining factors with different levels,</span></a>

-<a class="sourceLine" id="cb20-11" data-line-number="11"><span class="co">#&gt; coercing to character vector</span></a></code></pre></div>

-<div class="sourceCode" id="cb21"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb21-1" data-line-number="1">pairs_plt =<span class="st"> </span><span class="kw"><a href="https://ggplot2.tidyverse.org/reference/ggplot.html">ggplot</a></span>(pairing_list<span class="op">$</span>cell_tbl, <span class="kw"><a href="https://ggplot2.tidyverse.org/reference/aes.html">aes</a></span>(<span class="dt">x =</span> cluster_idx<span class="fl">.1</span>_fct, <span class="dt">y =</span> cluster_idx<span class="fl">.2</span>_fct, <span class="dt">color =</span> sample, <span class="dt">shape =</span> pop)) <span class="op">+</span><span class="st"> </span><span class="kw"><a href="https://ggplot2.tidyverse.org/reference/geom_jitter.html">geom_jitter</a></span>(<span class="dt">width =</span> <span class="fl">.3</span>, <span class="dt">height =</span> <span class="fl">.3</span>) <span class="op">+</span><span class="st"> </span><span class="kw"><a href="https://ggplot2.tidyverse.org/reference/ggtheme.html">theme_minimal</a></span>()</a>

+<div class="sourceCode" id="cb20"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb20-1" data-line-number="1">class_colors =<span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/reexports.html">tibble</a></span>(<span class="dt">chain =</span>  <span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/unique">unique</a></span>(aa80<span class="op">$</span>cluster_tbl<span class="op">$</span>chain)) <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/mutate.html">mutate</a></span>(<span class="dt">class_color =</span>  RColorBrewer<span class="op">::</span><span class="kw"><a href="https://www.rdocumentation.org/packages/RColorBrewer/topics/ColorBrewer">brewer.pal</a></span>(<span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/length">length</a></span>(chain),<span class="st">"Set1"</span>)[<span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/seq">seq_along</a></span>(chain)])</a>

+<a class="sourceLine" id="cb20-2" data-line-number="2"><span class="co">#&gt; Warning in RColorBrewer::brewer.pal(length(chain), "Set1"): minimal value for n is 3, returning requested palette with 3 different levels</span></a>

+<a class="sourceLine" id="cb20-3" data-line-number="3"></a>

+<a class="sourceLine" id="cb20-4" data-line-number="4">aa80<span class="op">$</span>cluster_pk =<span class="st"> 'representative'</span></a>

+<a class="sourceLine" id="cb20-5" data-line-number="5">pairing_list =<span class="st"> </span><span class="kw"><a href="../reference/pairing_tables.html">pairing_tables</a></span>(aa80, <span class="dt">table_order =</span> <span class="dv">2</span>, <span class="dt">orphan_level =</span> <span class="dv">1</span>, <span class="dt">min_expansion =</span> <span class="dv">3</span>, <span class="dt">cluster_keys =</span> <span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/c">c</a></span>(<span class="st">'cdr3'</span>, <span class="st">'representative'</span>, <span class="st">'chain'</span>, <span class="st">'v_gene'</span>, <span class="st">'j_gene'</span>, <span class="st">'avg_distance'</span>))</a>

+<a class="sourceLine" id="cb20-6" data-line-number="6"><span class="co">#&gt; Warning: Factor `cluster_idx.2` contains implicit NA, consider using</span></a>

+<a class="sourceLine" id="cb20-7" data-line-number="7"><span class="co">#&gt; `forcats::fct_explicit_na`</span></a>

+<a class="sourceLine" id="cb20-8" data-line-number="8"><span class="co">#&gt; Warning: Column `representative` joining factors with different levels,</span></a>

+<a class="sourceLine" id="cb20-9" data-line-number="9"><span class="co">#&gt; coercing to character vector</span></a></code></pre></div>

+<div class="sourceCode" id="cb21"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb21-1" data-line-number="1">pairs_plt =<span class="st"> </span><span class="kw"><a href="https://ggplot2.tidyverse.org/reference/ggplot.html">ggplot</a></span>(pairing_list<span class="op">$</span>cell_tbl, <span class="kw"><a href="https://ggplot2.tidyverse.org/reference/aes.html">aes</a></span>(<span class="dt">x =</span> cluster_idx<span class="fl">.1</span>_fct, <span class="dt">y =</span> cluster_idx<span class="fl">.2</span>_fct, <span class="dt">color =</span> sample, <span class="dt">shape =</span> pop)) <span class="op">+</span><span class="st"> </span><span class="kw"><a href="https://ggplot2.tidyverse.org/reference/geom_jitter.html">geom_jitter</a></span>(<span class="dt">width =</span> <span class="fl">.2</span>, <span class="dt">height =</span> <span class="fl">.2</span>) <span class="op">+</span><span class="st"> </span><span class="kw"><a href="https://ggplot2.tidyverse.org/reference/ggtheme.html">theme_minimal</a></span>() <span class="op">+</span><span class="st"> </span><span class="kw"><a href="https://ggplot2.tidyverse.org/reference/labs.html">xlab</a></span>(<span class="st">'TRB'</span>) <span class="op">+</span><span class="st"> </span><span class="kw"><a href="https://ggplot2.tidyverse.org/reference/labs.html">ylab</a></span>(<span class="st">'TRA'</span>)</a>

 <a class="sourceLine" id="cb21-2" data-line-number="2"></a>

-<a class="sourceLine" id="cb21-3" data-line-number="3">ylab =<span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/reexports.html">data_frame</a></span>(<span class="dt">cdr3_representative =</span>  <span class="kw"><a href="https://ggplot2.tidyverse.org/reference/ggplot_build.html">ggplot_build</a></span>(pairs_plt)<span class="op">$</span>layout<span class="op">$</span>panel_params[[<span class="dv">1</span>]]<span class="op">$</span>y.label) <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/join.html">left_join</a></span>(feature_tbl) <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/mutate.html">mutate</a></span>(<span class="dt">class_color =</span> <span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/ifelse">ifelse</a></span>(<span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/NA">is.na</a></span>(class_color), <span class="st">'#E41A1C'</span>, class_color))</a>

-<a class="sourceLine" id="cb21-4" data-line-number="4"></a>

-<a class="sourceLine" id="cb21-5" data-line-number="5">xlab =<span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/reexports.html">data_frame</a></span>(<span class="dt">cdr3_representative =</span>  <span class="kw"><a href="https://ggplot2.tidyverse.org/reference/ggplot_build.html">ggplot_build</a></span>(pairs_plt)<span class="op">$</span>layout<span class="op">$</span>panel_params[[<span class="dv">1</span>]]<span class="op">$</span>x.label) <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/join.html">left_join</a></span>(feature_tbl) <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/mutate.html">mutate</a></span>(<span class="dt">class_color =</span> <span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/ifelse">ifelse</a></span>(<span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/NA">is.na</a></span>(class_color), <span class="st">'#E41A1C'</span>, class_color))</a>

-<a class="sourceLine" id="cb21-6" data-line-number="6"></a>

-<a class="sourceLine" id="cb21-7" data-line-number="7">pairs_plt =<span class="st"> </span>pairs_plt <span class="op">+</span><span class="st"> </span><span class="kw"><a href="https://ggplot2.tidyverse.org/reference/theme.html">theme</a></span>(<span class="dt">axis.text.x =</span> <span class="kw"><a href="https://ggplot2.tidyverse.org/reference/element.html">element_text</a></span>(<span class="dt">angle =</span> <span class="dv">90</span>, <span class="dt">color =</span> xlab<span class="op">$</span>class_color, <span class="dt">size =</span> <span class="dv">8</span>), <span class="dt">axis.text.y =</span> <span class="kw"><a href="https://ggplot2.tidyverse.org/reference/element.html">element_text</a></span>(<span class="dt">color =</span> ylab<span class="op">$</span>class_color, <span class="dt">size =</span> <span class="dv">8</span>))</a>

-<a class="sourceLine" id="cb21-8" data-line-number="8"></a>

-<a class="sourceLine" id="cb21-9" data-line-number="9">pairs_plt</a></code></pre></div>

+<a class="sourceLine" id="cb21-3" data-line-number="3">feature_tbl =<span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/join.html">left_join</a></span>(<span class="kw"><a href="https://dplyr.tidyverse.org/reference/bind.html">bind_rows</a></span>(pairing_list<span class="op">$</span>idx1_tbl, pairing_list<span class="op">$</span>idx2_tbl), class_colors)</a>

+<a class="sourceLine" id="cb21-4" data-line-number="4"><span class="co">#&gt; Warning in bind_rows_(x, .id): binding factor and character vector,</span></a>

+<a class="sourceLine" id="cb21-5" data-line-number="5"><span class="co">#&gt; coercing into character vector</span></a>

+<a class="sourceLine" id="cb21-6" data-line-number="6"><span class="co">#&gt; Warning in bind_rows_(x, .id): binding character and factor vector,</span></a>

+<a class="sourceLine" id="cb21-7" data-line-number="7"><span class="co">#&gt; coercing into character vector</span></a>

+<a class="sourceLine" id="cb21-8" data-line-number="8"><span class="co">#&gt; Joining, by = "chain"</span></a>

+<a class="sourceLine" id="cb21-9" data-line-number="9"></a>

+<a class="sourceLine" id="cb21-10" data-line-number="10">ylab =<span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/reexports.html">data_frame</a></span>(<span class="dt">representative =</span>  <span class="kw"><a href="https://ggplot2.tidyverse.org/reference/ggplot_build.html">ggplot_build</a></span>(pairs_plt)<span class="op">$</span>layout<span class="op">$</span>panel_params[[<span class="dv">1</span>]]<span class="op">$</span>y.label) <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/join.html">left_join</a></span>(feature_tbl) <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/mutate.html">mutate</a></span>(<span class="dt">class_color =</span> <span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/ifelse">ifelse</a></span>(<span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/NA">is.na</a></span>(class_color), <span class="st">'#E41A1C'</span>, class_color))</a>

+<a class="sourceLine" id="cb21-11" data-line-number="11"><span class="co">#&gt; Warning: `data_frame()` is deprecated, use `tibble()`.</span></a>

+<a class="sourceLine" id="cb21-12" data-line-number="12"><span class="co">#&gt; This warning is displayed once per session.</span></a>

+<a class="sourceLine" id="cb21-13" data-line-number="13"><span class="co">#&gt; Joining, by = "representative"</span></a>

+<a class="sourceLine" id="cb21-14" data-line-number="14"></a>

+<a class="sourceLine" id="cb21-15" data-line-number="15">xlab =<span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/reexports.html">data_frame</a></span>(<span class="dt">representative =</span>  <span class="kw"><a href="https://ggplot2.tidyverse.org/reference/ggplot_build.html">ggplot_build</a></span>(pairs_plt)<span class="op">$</span>layout<span class="op">$</span>panel_params[[<span class="dv">1</span>]]<span class="op">$</span>x.label) <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/join.html">left_join</a></span>(feature_tbl) <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/mutate.html">mutate</a></span>(<span class="dt">class_color =</span> <span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/ifelse">ifelse</a></span>(<span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/NA">is.na</a></span>(class_color), <span class="st">'#E41A1C'</span>, class_color))</a>

+<a class="sourceLine" id="cb21-16" data-line-number="16"><span class="co">#&gt; Joining, by = "representative"</span></a>

+<a class="sourceLine" id="cb21-17" data-line-number="17"></a>

+<a class="sourceLine" id="cb21-18" data-line-number="18">pairs_plt =<span class="st"> </span>pairs_plt <span class="op">+</span><span class="st"> </span><span class="kw"><a href="https://ggplot2.tidyverse.org/reference/theme.html">theme</a></span>(<span class="dt">axis.text.x =</span> <span class="kw"><a href="https://ggplot2.tidyverse.org/reference/element.html">element_text</a></span>(<span class="dt">angle =</span> <span class="dv">90</span>, <span class="dt">color =</span> xlab<span class="op">$</span>class_color, <span class="dt">size =</span> <span class="dv">8</span>), <span class="dt">axis.text.y =</span> <span class="kw"><a href="https://ggplot2.tidyverse.org/reference/element.html">element_text</a></span>(<span class="dt">color =</span> ylab<span class="op">$</span>class_color, <span class="dt">size =</span> <span class="dv">8</span>))</a>

+<a class="sourceLine" id="cb21-19" data-line-number="19"></a>

+<a class="sourceLine" id="cb21-20" data-line-number="20">pairs_plt</a></code></pre></div>

+<p><img src="cdr3_clustering_files/figure-html/plot_expanded-1.png" width="700"></p>

 <div id="expanded-clones" class="section level2">

 <h2 class="hasAnchor">

 <a href="#expanded-clones" class="anchor"></a>Expanded clones</h2>

-<div class="sourceCode" id="cb22"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb22-1" data-line-number="1">pairing_list =<span class="st"> </span><span class="kw"><a href="../reference/pairing_tables.html">pairing_tables</a></span>(oligo_clusters_all <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span>(cdr3_representative, dataset, barcode, chain, umis, reads), <span class="dt">cluster_idx =</span> <span class="st">'cdr3_representative'</span>, <span class="dt">cell_identifiers =</span> <span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/c">c</a></span>(<span class="st">'dataset'</span>, <span class="st">'barcode'</span>), <span class="dt">canonicalize_fun =</span> canonicalize_by_prevalence, <span class="dt">table_order =</span> <span class="dv">2</span>, <span class="dt">orphan_level =</span> <span class="dv">1</span>, <span class="dt">min_expansion =</span> <span class="dv">4</span>, <span class="dt">feature_tbl =</span> feature_tbl, <span class="dt">cell_tbl =</span> good_cells, <span class="dt">cluster_whitelist =</span> <span class="kw"><a href="https://dplyr.tidyverse.org/reference/filter.html">filter</a></span>(oligo_clusters, n_cluster<span class="op">&gt;</span><span class="dv">8</span>) <span class="op">%&gt;%</span><span class="st"> </span>dplyr<span class="op">::</span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span>(<span class="dt">cluster_idx.1 =</span> cdr3_representative) <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/unique">unique</a></span>())</a>

-<a class="sourceLine" id="cb22-2" data-line-number="2">pairs_plt =<span class="st"> </span><span class="kw"><a href="https://ggplot2.tidyverse.org/reference/ggplot.html">ggplot</a></span>(pairing_list<span class="op">$</span>cell_tbl, <span class="kw"><a href="https://ggplot2.tidyverse.org/reference/aes.html">aes</a></span>(<span class="dt">x =</span> cluster_idx<span class="fl">.1</span>_fct, <span class="dt">y =</span> cluster_idx<span class="fl">.2</span>_fct, <span class="dt">color =</span> sample, <span class="dt">shape =</span> pop)) <span class="op">+</span><span class="st"> </span><span class="kw"><a href="https://ggplot2.tidyverse.org/reference/geom_jitter.html">geom_jitter</a></span>(<span class="dt">width =</span> <span class="fl">.3</span>, <span class="dt">height =</span> <span class="fl">.3</span>) <span class="op">+</span><span class="st"> </span><span class="kw"><a href="https://ggplot2.tidyverse.org/reference/ggtheme.html">theme_minimal</a></span>()</a>

+<div class="sourceCode" id="cb22"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb22-1" data-line-number="1">pairing_list =<span class="st"> </span><span class="kw"><a href="../reference/pairing_tables.html">pairing_tables</a></span>(oligo_clusters_all <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span>(representative, dataset, barcode, chain, umis, reads), <span class="dt">cluster_idx =</span> <span class="st">'representative'</span>, <span class="dt">cell_identifiers =</span> <span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/c">c</a></span>(<span class="st">'dataset'</span>, <span class="st">'barcode'</span>), <span class="dt">canonicalize_fun =</span> canonicalize_by_prevalence, <span class="dt">table_order =</span> <span class="dv">2</span>, <span class="dt">orphan_level =</span> <span class="dv">1</span>, <span class="dt">min_expansion =</span> <span class="dv">4</span>, <span class="dt">feature_tbl =</span> feature_tbl, <span class="dt">cell_tbl =</span> good_cells, <span class="dt">cluster_whitelist =</span> <span class="kw"><a href="https://dplyr.tidyverse.org/reference/filter.html">filter</a></span>(oligo_clusters, n_cluster<span class="op">&gt;</span><span class="dv">8</span>) <span class="op">%&gt;%</span><span class="st"> </span>dplyr<span class="op">::</span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span>(<span class="dt">cluster_idx.1 =</span> representative) <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/unique">unique</a></span>())</a>

+<a class="sourceLine" id="cb22-2" data-line-number="2">pairs_plt =<span class="st"> </span><span class="kw"><a href="https://ggplot2.tidyverse.org/reference/ggplot.html">ggplot</a></span>(pairing_list<span class="op">$</span>cell_tbl, <span class="kw"><a href="https://ggplot2.tidyverse.org/reference/aes.html">aes</a></span>(<span class="dt">x =</span> cluster_idx<span class="fl">.1</span>_fct, <span class="dt">y =</span> cluster_idx<span class="fl">.2</span>_fct, <span class="dt">color =</span> sample, <span class="dt">shape =</span> pop)) <span class="op">+</span><span class="st"> </span><span class="kw"><a href="https://ggplot2.tidyverse.org/reference/geom_jitter.html">geom_jitter</a></span>(<span class="dt">width =</span> <span class="fl">.2</span>, <span class="dt">height =</span> <span class="fl">.2</span>) <span class="op">+</span><span class="st"> </span><span class="kw"><a href="https://ggplot2.tidyverse.org/reference/ggtheme.html">theme_minimal</a></span>() <span class="op">+</span><span class="st"> </span><span class="kw"><a href="https://ggplot2.tidyverse.org/reference/labs.html">xlab</a></span>(<span class="st">'TRB'</span>) <span class="op">+</span><span class="st"> </span><span class="kw"><a href="https://ggplot2.tidyverse.org/reference/labs.html">ylab</a></span>(<span class="st">'TRA'</span>)</a>

 <a class="sourceLine" id="cb22-3" data-line-number="3"></a>

-<a class="sourceLine" id="cb22-4" data-line-number="4">ylab =<span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/reexports.html">data_frame</a></span>(<span class="dt">cdr3_representative =</span>  <span class="kw"><a href="https://ggplot2.tidyverse.org/reference/ggplot_build.html">ggplot_build</a></span>(pairs_plt)<span class="op">$</span>layout<span class="op">$</span>panel_params[[<span class="dv">1</span>]]<span class="op">$</span>y.label) <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/join.html">left_join</a></span>(feature_tbl) <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/mutate.html">mutate</a></span>(<span class="dt">class_color =</span> <span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/ifelse">ifelse</a></span>(<span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/NA">is.na</a></span>(class_color), <span class="st">'#E41A1C'</span>, class_color))</a>

+<a class="sourceLine" id="cb22-4" data-line-number="4">feature_tbl =<span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/join.html">left_join</a></span>(<span class="kw"><a href="https://dplyr.tidyverse.org/reference/bind.html">bind_rows</a></span>(pairing_list<span class="op">$</span>idx1_tbl, pairing_list<span class="op">$</span>idx2_tbl), class_colors)</a>

 <a class="sourceLine" id="cb22-5" data-line-number="5"></a>

-<a class="sourceLine" id="cb22-6" data-line-number="6">xlab =<span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/reexports.html">data_frame</a></span>(<span class="dt">cdr3_representative =</span>  <span class="kw"><a href="https://ggplot2.tidyverse.org/reference/ggplot_build.html">ggplot_build</a></span>(pairs_plt)<span class="op">$</span>layout<span class="op">$</span>panel_params[[<span class="dv">1</span>]]<span class="op">$</span>x.label) <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/join.html">left_join</a></span>(feature_tbl) <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/mutate.html">mutate</a></span>(<span class="dt">class_color =</span> <span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/ifelse">ifelse</a></span>(<span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/NA">is.na</a></span>(class_color), <span class="st">'#E41A1C'</span>, class_color))</a>

+<a class="sourceLine" id="cb22-6" data-line-number="6">ylab =<span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/reexports.html">data_frame</a></span>(<span class="dt">representative =</span>  <span class="kw"><a href="https://ggplot2.tidyverse.org/reference/ggplot_build.html">ggplot_build</a></span>(pairs_plt)<span class="op">$</span>layout<span class="op">$</span>panel_params[[<span class="dv">1</span>]]<span class="op">$</span>y.label) <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/join.html">left_join</a></span>(feature_tbl) <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/mutate.html">mutate</a></span>(<span class="dt">class_color =</span> <span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/ifelse">ifelse</a></span>(<span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/NA">is.na</a></span>(class_color), <span class="st">'#E41A1C'</span>, class_color))</a>

 <a class="sourceLine" id="cb22-7" data-line-number="7"></a>

-<a class="sourceLine" id="cb22-8" data-line-number="8">pairs_plt =<span class="st"> </span>pairs_plt <span class="op">+</span><span class="st"> </span><span class="kw"><a href="https://ggplot2.tidyverse.org/reference/theme.html">theme</a></span>(<span class="dt">axis.text.x =</span> <span class="kw"><a href="https://ggplot2.tidyverse.org/reference/element.html">element_text</a></span>(<span class="dt">angle =</span> <span class="dv">90</span>, <span class="dt">color =</span> xlab<span class="op">$</span>class_color, <span class="dt">size =</span> <span class="dv">8</span>), <span class="dt">axis.text.y =</span> <span class="kw"><a href="https://ggplot2.tidyverse.org/reference/element.html">element_text</a></span>(<span class="dt">color =</span> ylab<span class="op">$</span>class_color, <span class="dt">size =</span> <span class="dv">8</span>))</a>

+<a class="sourceLine" id="cb22-8" data-line-number="8">xlab =<span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/reexports.html">data_frame</a></span>(<span class="dt">representative =</span>  <span class="kw"><a href="https://ggplot2.tidyverse.org/reference/ggplot_build.html">ggplot_build</a></span>(pairs_plt)<span class="op">$</span>layout<span class="op">$</span>panel_params[[<span class="dv">1</span>]]<span class="op">$</span>x.label) <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/join.html">left_join</a></span>(feature_tbl) <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/mutate.html">mutate</a></span>(<span class="dt">class_color =</span> <span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/ifelse">ifelse</a></span>(<span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/NA">is.na</a></span>(class_color), <span class="st">'#E41A1C'</span>, class_color))</a>

 <a class="sourceLine" id="cb22-9" data-line-number="9"></a>

-<a class="sourceLine" id="cb22-10" data-line-number="10">pairs_plt</a></code></pre></div>

+<a class="sourceLine" id="cb22-10" data-line-number="10">pairs_plt =<span class="st"> </span>pairs_plt <span class="op">+</span><span class="st"> </span><span class="kw"><a href="https://ggplot2.tidyverse.org/reference/theme.html">theme</a></span>(<span class="dt">axis.text.x =</span> <span class="kw"><a href="https://ggplot2.tidyverse.org/reference/element.html">element_text</a></span>(<span class="dt">angle =</span> <span class="dv">90</span>, <span class="dt">color =</span> xlab<span class="op">$</span>class_color, <span class="dt">size =</span> <span class="dv">8</span>), <span class="dt">axis.text.y =</span> <span class="kw"><a href="https://ggplot2.tidyverse.org/reference/element.html">element_text</a></span>(<span class="dt">color =</span> ylab<span class="op">$</span>class_color, <span class="dt">size =</span> <span class="dv">8</span>))</a>

+<a class="sourceLine" id="cb22-11" data-line-number="11"></a>

+<a class="sourceLine" id="cb22-12" data-line-number="12">pairs_plt</a></code></pre></div>

 </div>

 </div>

 <div id="length-of-cdr3" class="section level1">

@@ -368,7 +387,7 @@

 <a class="sourceLine" id="cb24-12" data-line-number="12"><span class="co">#&gt; coercing into character vector</span></a>

 <a class="sourceLine" id="cb24-13" data-line-number="13"><span class="kw"><a href="https://ggplot2.tidyverse.org/reference/ggplot.html">ggplot</a></span>(cdr_len <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/filter.html">filter</a></span>(group <span class="op">==</span><span class="st"> 'fixed'</span>, term <span class="op">!=</span><span class="st"> '(Intercept)'</span>), <span class="kw"><a href="https://ggplot2.tidyverse.org/reference/aes.html">aes</a></span>(<span class="dt">x =</span> <span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/interaction">interaction</a></span>(chain, term), <span class="dt">y =</span> estimate, <span class="dt">ymin =</span> conf.low, <span class="dt">ymax =</span> conf.high)) <span class="op">+</span><span class="st"> </span><span class="kw"><a href="https://ggplot2.tidyverse.org/reference/geom_linerange.html">geom_pointrange</a></span>() <span class="op">+</span><span class="st"> </span><span class="kw"><a href="https://ggplot2.tidyverse.org/reference/ggtheme.html">theme_minimal</a></span>() <span class="op">+</span><span class="st"> </span><span class="kw"><a href="https://ggplot2.tidyverse.org/reference/coord_flip.html">coord_flip</a></span>() <span class="op">+</span><span class="st"> </span><span class="kw"><a href="https://ggplot2.tidyverse.org/reference/labs.html">ylab</a></span>(<span class="st">'Length(CDR3 Nt)'</span>) <span class="op">+</span><span class="st"> </span><span class="kw"><a href="https://ggplot2.tidyverse.org/reference/labs.html">xlab</a></span>(<span class="st">'Term/Chain'</span>)</a></code></pre></div>

 <p><img src="cdr3_clustering_files/figure-html/cdr3_len-1.png" width="288"></p>

-<p>As was suggested by the histogram, there doesn’t seem to be an obvious <code>pop</code> effect.</p>

+<p>We end up with a convergence warning. This is not a suprise, because the <code>samples</code> aren’t actually replicates – they are just subsamples drawn for illustrative purposes. The Balbc mice have .5 fewer nucleotides per contig, on average, and this is not significant.</p>

 </div>

   </div>

@@ -381,6 +400,8 @@

       <li><a href="#chain-pairings">Chain pairings</a></li>

       <li><a href="#cluster-cdr3-protein-sequences">Cluster CDR3 protein sequences</a></li>

       <li><a href="#cluster-cdr3-dna-sequences">Cluster CDR3 DNA sequences</a></li>

+      <li><a href="#cluster-by-v-j-identity">Cluster by V-J identity</a></li>

+      <li><a href="#some-simple-phylogenetic-relationship">Some simple phylogenetic relationship</a></li>

       <li><a href="#oligo-clusters">Oligo clusters</a></li>

       <li><a href="#formal-testing-for-frequency-differences">Formal testing for frequency differences</a></li>

       <li>

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@@ -25,7 +25,7 @@

 <![endif]-->

 </head>

 <body>

-    <div class="container template-home">

+    <div class="container template-article">

       <header><div class="navbar navbar-default navbar-fixed-top" role="navigation">

   <div class="container">

     <div class="navbar-header">

@@ -85,7 +85,12 @@

       </header><div class="row">

-  <div class="contents col-md-9">

+  <div class="col-md-9 contents">

+    

+

+    

+    

+<!-- README.md is generated from README.Rmd. Please edit that file -->

 <div id="cellarepertorium" class="section level1">

 <div class="page-header"><h1 class="hasAnchor">

 <a href="#cellarepertorium" class="anchor"></a>CellaRepertorium</h1></div>

@@ -94,16 +99,17 @@

 <h2 class="hasAnchor">

 <a href="#installation" class="anchor"></a>Installation</h2>

 <pre><code><a href="https://www.rdocumentation.org/packages/devtools/topics/reexports">devtools::install_github('amcdavid/CellaRepertorium')</a></code></pre>

-<p>Requires R&gt;=3.5.</p>

+<p>Requires R &gt;= 3.5.</p>

 </div>

 <div id="data-requirements-and-package-structure" class="section level2">

 <h2 class="hasAnchor">

 <a href="#data-requirements-and-package-structure" class="anchor"></a>Data requirements and package structure</h2>

-<p>The fundamental unit is the <strong>contig</strong>, which is a section of contiguously stitched reads from a single <strong>cell</strong>. Each contig belongs to one (and only one) cell, however, cells generate multiple contigs. Contigs can also belong to a <strong>cluster</strong>. Because of these two many-to-one mappings, these data can be thought as a series of ragged arrays. The links between them mean they are relational data.</p>

-<p>[A schematic of contigs and cells should go here]</p>

-<p>A <code>ContigCellDB</code> object wraps each of these objects as a sequence of three <code>data.frame</code>s (well, <code>tibble</code>s, actually). <code>ContigCellDB</code> also tracks columns (keys) that unique identify each row in each of these tables. The <code>contig_tbl</code> is the <code>tibble</code> containing <strong>contigs</strong>, the <code>cell_tbl</code> contains the <strong>cells</strong>, and the <code>cluster_tbl</code> contains the <strong>clusters</strong>. The <code>contig_pk</code>, <code>cell_pk</code> and <code>cluster_pk</code> identify the columns that identify a contig, cell and cluster, respectively, and must be unique in each of the respective tables. The tables are kept in sync so that subsetting the contigs will subset the cells, and clusters, and vice-versa.</p>

-<p>[A schematic showing table relations should go here]</p>

-<p>Of course, each of these tables can contain many other columns that will serve as covariates for various analysis, such as the CDR3 sequence, or the identity of the V, D and J regions. Various derived quantities that describe cells and clusters can also be calculated, and added to these tables, such as the medoid of a cluster.</p>

+<p>The fundamental unit this package operates on is the <strong>contig</strong>, which is a section of contiguously stitched reads from a single <strong>cell</strong>. Each contig belongs to one (and only one) cell, however, cells generate multiple contigs.</p>

+<p><img src="../../../../Box%20Sync/research/scRNAseq/CellaRepertorium/vignettes/figure/contig_schematic.png"><!-- --></p>

+<p>Contigs can also belong to a <strong>cluster</strong>. Because of these two many-to-one mappings, these data can be thought as a series of ragged arrays. The links between them mean they are relational data. A <code>ContigCellDB</code> object wraps each of these objects as a sequence of three <code>data.frames</code> (well, <code>tibbles</code>, actually). <code>ContigCellDB</code> also tracks columns (the primary keys) that unique identify each row in each of these tables. The <code>contig_tbl</code> is the <code>tibble</code> containing <strong>contigs</strong>, the <code>cell_tbl</code> contains the <strong>cells</strong>, and the <code>cluster_tbl</code> contains the <strong>clusters</strong>.</p>

+<p>The <code>contig_pk</code>, <code>cell_pk</code> and <code>cluster_pk</code> identify the columns that identify a contig, cell and cluster, respectively. These will serve as foreign keys that link the three tables together. The tables are kept in sync so that subsetting the contigs will subset the cells, and clusters, and vice-versa.</p>

+<p><img src="../../../../Box%20Sync/research/scRNAseq/CellaRepertorium/vignettes/figure/table_schematic.png"><!-- --></p>

+<p>Of course, each of these tables can contain many other columns that will serve as covariates for various analyses, such as the CDR3 sequence, or the identity of the V, D and J regions. Various derived quantities that describe cells and clusters can also be calculated, and added to these tables, such as the medoid of a cluster – a contig that minimizes the average distance to all other clusters.</p>

 </div>

 <div id="functions" class="section level2">

 <h2 class="hasAnchor">

@@ -111,11 +117,13 @@

 <p>[a screencap of something interesting?]</p>

 <ul>

 <li>

-<code>cdhit</code>: An R interface to CDhit, which was originally ported by Thomas Lin Pedersen.</li>

+<code>cdhit_ccdb</code>: An R interface to CDhit, which was originally ported by Thomas Lin Pedersen.</li>

 <li>

-<code>fine_cluster</code>: clustering CDR3 by edit distances (possibly using empirical amino acid substitution matrices)</li>

+<code>fine_clustering</code>: clustering CDR3 by edit distances (possibly using empirical amino acid substitution matrices)</li>

 <li>

 <code>cluster_permute_test</code>: permutation tests of cluster statistics</li>

+<li>

+<code>pairing_tables</code>: Generate pairings of contigs within each cell in a way that they can be plotted</li>

 </ul>

 </div>

 </div>

@@ -145,9 +153,11 @@

 </ul>

 </div>

-  </div>

+      </div>

+

 </div>

+

       <footer><div class="copyright">

   <p>Developed by Andrew McDavid, Yu Gu.</p>

 </div>

new file mode 100644

@@ -0,0 +1,229 @@

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+<meta property="og:title" content="Find a canonical contig to represent a cell — canonicalize_cell" />

+

+<meta property="og:description" content="Using filtering in `...` and sorting in `tie_break_keys` and `order` find a

+single, canonical contig to represent each cell

+Fields in `contig_fields` will be copied over to the `cell_tbl`." />

+<meta name="twitter:card" content="summary" />

+

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+        <a class="navbar-link" href="../index.html">CellaRepertorium</a>

+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">0.3.1</span>

+      </span>

+    </div>

+

+    <div id="navbar" class="navbar-collapse collapse">

+      <ul class="nav navbar-nav">

+        <li>

+  <a href="../index.html">

+    <span class="fa fa-home fa-lg"></span>

+     

+  </a>

+</li>

+<li>

+  <a href="../reference/index.html">Reference</a>

+</li>

+<li class="dropdown">

+  <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false">

+    Articles

+     

+    <span class="caret"></span>

+  </a>

+  <ul class="dropdown-menu" role="menu">

+    <li>

+      <a href="../articles/cdr3_clustering.html">Clustering repertoire via CDR3 sequences</a>

+    </li>

+    <li>

+      <a href="../articles/mouse_tcell_qc.html">Quality control and Exploration of UMI-based repertoire data</a>

+    </li>

+  </ul>

+</li>

+      </ul>

+      

+      <ul class="nav navbar-nav navbar-right">

+        <li>

+  <a href="https://github.com/amcdavid/CellaRepertorium">

+    <span class="fa fa-github fa-lg"></span>

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+

+      

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+

+<div class="row">

+  <div class="col-md-9 contents">

+    <div class="page-header">

+    <h1>Find a canonical contig to represent a cell</h1>

+    <small class="dont-index">Source: <a href='https://github.com/amcdavid/CellaRepertorium/blob/master/R/pairing-methods.R'><code>R/pairing-methods.R</code></a></small>

+    <div class="hidden name"><code>canonicalize_cell.Rd</code></div>

+    </div>

+

+    <div class="ref-description">

+    

+    <p>Using filtering in `...` and sorting in `tie_break_keys` and `order` find a

+single, canonical contig to represent each cell

+Fields in `contig_fields` will be copied over to the `cell_tbl`.</p>

+    

+    </div>

+

+    <pre class="usage"><span class='fu'>canonicalize_cell</span>(<span class='no'>ccdb</span>, <span class='no'>contig_filter_args</span>, <span class='kw'>tie_break_keys</span> <span class='kw'>=</span> <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/c'>c</a></span>(<span class='st'>"umis"</span>,

+  <span class='st'>"reads"</span>), <span class='kw'>contig_fields</span> <span class='kw'>=</span> <span class='no'>tie_break_keys</span>, <span class='kw'>order</span> <span class='kw'>=</span> <span class='fl'>1</span>)</pre>

+    

+    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>

+    <table class="ref-arguments">

+    <colgroup><col class="name" /><col class="desc" /></colgroup>

+    <tr>

+      <th>ccdb</th>

+      <td><p>`ContigCellDB`</p></td>

+    </tr>

+    <tr>

+      <th>contig_filter_args</th>

+      <td><p>an expression passed to dplyr::filter.  Unlike `filter`, multiple criteria must be `&amp;` together, rather than using commas to separate.

+that act on `ccdb$contig_tbl``</p></td>

+    </tr>

+    <tr>

+      <th>tie_break_keys</th>

+      <td><p>(optional) `character` naming fields in `contig_tbl`

+that are used sort the contig table in descending order.

+Used to break ties if `contig_filter_args` does not return a unique contig

+for each cluster</p></td>

+    </tr>

+    <tr>

+      <th>contig_fields</th>

+      <td><p>Optional fields from `contig_tbl` that will be copied into

+the `cluster_tbl` from the canonical contig.</p></td>

+    </tr>

+    <tr>

+      <th>order</th>

+      <td><p>The rank order of the contig, based on `tie_break_keys`

+to return</p></td>

+    </tr>

+    </table>

+    

+    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>

+

+    <p>`ContigCellDB` with additional fields in `cell_tbl`</p>

+    

+    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>

+

+    <div class='dont-index'><p>canonicalize_cluster</p></div>

+    

+

+    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>

+    <pre class="examples"><div class='input'><span class='co'># Report beta chain with highest umi-count, breaking ties with reads</span>

+<span class='no'>beta</span> <span class='kw'>=</span> <span class='fu'>canonicalize_cell</span>(<span class='no'>ccdb_ex</span>, <span class='no'>chain</span> <span class='kw'>==</span> <span class='st'>'TRB'</span>,

+<span class='kw'>tie_break_keys</span> <span class='kw'>=</span> <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/c'>c</a></span>(<span class='st'>'umis'</span>, <span class='st'>'reads'</span>),

+<span class='kw'>contig_fields</span> <span class='kw'>=</span> <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/c'>c</a></span>(<span class='st'>'umis'</span>, <span class='st'>'reads'</span>, <span class='st'>'chain'</span>, <span class='st'>'v_gene'</span>, <span class='st'>'d_gene'</span>, <span class='st'>'j_gene'</span>))

+<span class='fu'><a href='https://www.rdocumentation.org/packages/utils/topics/head'>head</a></span>(<span class='no'>beta</span>$<span class='no'>cell_tbl</span>)</div><div class='output co'>#&gt; <span style='color: #555555;'># A tibble: 6 x 9</span><span>

+#&gt; </span><span style='color: #555555;'># Groups:   pop, sample, barcode [6]</span><span>

+#>    umis reads chain v_gene d_gene j_gene  pop   sample barcode           

+#&gt;   </span><span style='color: #555555;font-style: italic;'>&lt;dbl&gt;</span><span> </span><span style='color: #555555;font-style: italic;'>&lt;dbl&gt;</span><span> </span><span style='color: #555555;font-style: italic;'>&lt;chr&gt;</span><span> </span><span style='color: #555555;font-style: italic;'>&lt;chr&gt;</span><span>  </span><span style='color: #555555;font-style: italic;'>&lt;chr&gt;</span><span>  </span><span style='color: #555555;font-style: italic;'>&lt;chr&gt;</span><span>   </span><span style='color: #555555;font-style: italic;'>&lt;chr&gt;</span><span> </span><span style='color: #555555;font-style: italic;'>&lt;chr&gt;</span><span>  </span><span style='color: #555555;font-style: italic;'>&lt;chr&gt;</span><span>             

+#&gt; </span><span style='color: #555555;'>1</span><span>     6 </span><span style='text-decoration: underline;'>37</span><span>898 TRB   TRBV31 None   TRBJ1-5 b6    4      AAAGTAGTCGCGCCAA-1

+#&gt; </span><span style='color: #555555;'>2</span><span>    </span><span style='color: #BB0000;'>NA</span><span>    </span><span style='color: #BB0000;'>NA</span><span> </span><span style='color: #BB0000;'>NA</span><span>    </span><span style='color: #BB0000;'>NA</span><span>     </span><span style='color: #BB0000;'>NA</span><span>     </span><span style='color: #BB0000;'>NA</span><span>      b6    4      AACCATGCATTTGCCC-1

+#&gt; </span><span style='color: #555555;'>3</span><span>     6 </span><span style='text-decoration: underline;'>33</span><span>548 TRB   TRBV5  TRBD2  TRBJ2-2 b6    4      AACTGGTGTCTGATCA-1

+#&gt; </span><span style='color: #555555;'>4</span><span>     6 </span><span style='text-decoration: underline;'>26</span><span>928 TRB   TRBV4  TRBD2  TRBJ2-4 b6    4      AAGCCGCAGTAAGTAC-1

+#&gt; </span><span style='color: #555555;'>5</span><span>     4 </span><span style='text-decoration: underline;'>18</span><span>435 TRB   TRBV1  None   TRBJ2-4 b6    4      AAGTCTGGTTCAACCA-1

+#&gt; </span><span style='color: #555555;'>6</span><span>     9 </span><span style='text-decoration: underline;'>46</span><span>156 TRB   TRBV5  TRBD2  TRBJ2-7 b6    4      ACACCAAAGTCCAGGA-1</div><div class='input'>

+<span class='co'># Only adds fields to `cell_tbl`</span>

+<span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/stopifnot'>stopifnot</a></span>(<span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/all.equal'>all.equal</a></span>(<span class='no'>beta</span>$<span class='no'>cell_tbl</span>[<span class='no'>ccdb_ex</span>$<span class='no'>cell_pk</span>],

+<span class='no'>ccdb_ex</span>$<span class='no'>cell_tbl</span>[<span class='no'>ccdb_ex</span>$<span class='no'>cell_pk</span>]))

+

+<span class='co'>#Report cdr3 with highest UMI count, but only when &gt; 5 UMIs support it</span>

+<span class='no'>umi5</span> <span class='kw'>=</span> <span class='fu'>canonicalize_cell</span>(<span class='no'>ccdb_ex</span>, <span class='no'>umis</span> <span class='kw'>&gt;</span> <span class='fl'>5</span>,

+<span class='kw'>tie_break_keys</span> <span class='kw'>=</span> <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/c'>c</a></span>(<span class='st'>'umis'</span>, <span class='st'>'reads'</span>), <span class='kw'>contig_fields</span> <span class='kw'>=</span> <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/c'>c</a></span>(<span class='st'>'umis'</span>, <span class='st'>'cdr3'</span>))

+<span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/stopifnot'>stopifnot</a></span>(<span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/all'>all</a></span>(<span class='no'>umi5</span>$<span class='no'>cell_tbl</span>$<span class='no'>umis</span> <span class='kw'>&gt;</span> <span class='fl'>5</span>, <span class='kw'>na.rm</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>))</div></span></pre>

+  </div>

+  <div class="col-md-3 hidden-xs hidden-sm" id="sidebar">

+    <h2>Contents</h2>

+    <ul class="nav nav-pills nav-stacked">

+      <li><a href="#arguments">Arguments</a></li>

+      

+      <li><a href="#value">Value</a></li>

+

+      <li><a href="#see-also">See also</a></li>

+      

+      <li><a href="#examples">Examples</a></li>

+    </ul>

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