estimateWeightEntropyPerCell

Estimate entropy of edge weights per cell according to the specified factor.
Can be used to visualize alignment quality according to this factor.

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

estimateWeightEntropyPerCell function

<dl><dt>con</dt>
<dd>conos object</dd>
<dt>factor.per.cell</dt>
<dd>some factor, which group cells, such as sample or a specific condition</dd></dl>

Arguments

Estimate entropy of edge weights per cell according to the specified factor.
Can be used to visualize alignment quality according to this factor. — estimateWeightEntropyPerCell

<dl>

<dt>con</dt>
<dd>conos object</dd>


<dt>factor.per.cell</dt>
<dd>some factor, which group cells, such as sample or a specific condition</dd>

</dl>

estimateWeightEntropyPerCell: Estimate entropy of edge weights per cell according to the specified factor. Can be used to visualize alignment quality according to this factor.

Description

Usage

Value

Arguments