plotClusterBoxPlotsByAppType

Generate boxplot per cluster of the proportion of cells in each celltype

Wires together large collections of single-cell RNA-seq datasets, which allows for both the identification of recurrent cell clusters and the propagation of information between datasets in multi-sample or atlas-scale collections. 'Conos' focuses on the uniform mapping of homologous cell types across heterogeneous sample collections. For instance, users could investigate a collection of dozens of peripheral blood samples from cancer patients combined with dozens of controls, which perhaps includes samples of a related tissue such as lymph nodes. This package interacts with data available through the 'conosPanel' package, which is available in a 'drat' repository. To access this data package, see the instructions at <https://github.com/kharchenkolab/conos>. The size of the 'conosPanel' package is approximately 12 MB.

Evan Biederstedt

conos

Clustering on Network of Samples

Viktor Petukhov

Nikolas Barkas

Peter Kharchenko

Weiliang Qiu

plotClusterBoxPlotsByAppType function

<dl><dt>conos.obj</dt>
<dd>conos object</dd>
<dt>clustering</dt>
<dd>name of the clustering to use (default=NULL)</dd>
<dt>apptypes</dt>
<dd>a factor specifying how to group the samples (default=NULL)</dd>
<dt>return.details</dt>
<dd>boolean If TRUE return a list with the plot and the summary data.frame (default=FALSE)</dd></dl>

Arguments

Generate boxplot per cluster of the proportion of cells in each celltype — plotClusterBoxPlotsByAppType

<dl>

<dt>conos.obj</dt>
<dd>conos object</dd>


<dt>clustering</dt>
<dd>name of the clustering to use (default=NULL)</dd>


<dt>apptypes</dt>
<dd>a factor specifying how to group the samples (default=NULL)</dd>


<dt>return.details</dt>
<dd>boolean If TRUE return a list with the plot and the summary data.frame (default=FALSE)</dd>

</dl>

plotClusterBoxPlotsByAppType: Generate boxplot per cluster of the proportion of cells in each celltype

Description

Usage

Value

Arguments