basicSeuratProc

Create and preprocess a Seurat object

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

basicSeuratProc function

<dl><dt>count.matrix</dt>
<dd>gene count matrix</dd>
<dt>vars.to.regress</dt>
<dd>variables to regress with Seurat (default=NULL)</dd>
<dt>verbose</dt>
<dd>boolean Verbose mode (default=TRUE)</dd>
<dt>do.par</dt>
<dd>boolean Use parallel processing for regressing out variables faster (default=TRUE)</dd>
<dt>n.pcs</dt>
<dd>numeric Number of principal components (default=100)</dd>
<dt>cluster</dt>
<dd>boolean Whether to perform clustering (default=TRUE)</dd>
<dt>tsne</dt>
<dd>boolean Whether to construct tSNE embedding (default=TRUE)</dd>
<dt>umap</dt>
<dd>boolean Whether to construct UMAP embedding, works only for Seurat v2.3.1 or higher (default=FALSE)</dd></dl>

Arguments

Create and preprocess a Seurat object — basicSeuratProc

<dl>

<dt>count.matrix</dt>
<dd>gene count matrix</dd>


<dt>vars.to.regress</dt>
<dd>variables to regress with Seurat (default=NULL)</dd>


<dt>verbose</dt>
<dd>boolean Verbose mode (default=TRUE)</dd>


<dt>do.par</dt>
<dd>boolean Use parallel processing for regressing out variables faster (default=TRUE)</dd>


<dt>n.pcs</dt>
<dd>numeric Number of principal components (default=100)</dd>


<dt>cluster</dt>
<dd>boolean Whether to perform clustering (default=TRUE)</dd>


<dt>tsne</dt>
<dd>boolean Whether to construct tSNE embedding (default=TRUE)</dd>


<dt>umap</dt>
<dd>boolean Whether to construct UMAP embedding, works only for Seurat v2.3.1 or higher (default=FALSE)</dd>

</dl>

basicSeuratProc: Create and preprocess a Seurat object

Description

Usage

Value

Arguments