filter.genes.by.cluster.expression

Filter genes by requiring minimum average expression within at least one of the provided cell clusters

internal

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

filter.genes.by.cluster.expression function

<dl><dt>emat</dt>
<dd>spliced (exonic) count matrix</dd>
<dt>clusters</dt>
<dd>named cell factor defining clusters</dd>
<dt>min.max.cluster.average</dt>
<dd>numeric Required minimum average expression count (no normalization is perfomed) (default=0.1)</dd></dl>

Arguments

Filter genes by requiring minimum average expression within at least one of the provided cell clusters — filter.genes.by.cluster.expression

<dl>

<dt>emat</dt>
<dd>spliced (exonic) count matrix</dd>


<dt>clusters</dt>
<dd>named cell factor defining clusters</dd>


<dt>min.max.cluster.average</dt>
<dd>numeric Required minimum average expression count (no normalization is perfomed) (default=0.1)</dd>

</dl>

filter.genes.by.cluster.expression: Filter genes by requiring minimum average expression within at least one of the provided cell clusters

Description

Usage

Value

Arguments