estimateWeightEntropyPerCell

<p>some factor, which group cells, such as sample or a specific condition</p>

factor.per.cell

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

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

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

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

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

Arguments

Value