mcell_cgraph_norm_gcor: Computing gene-gene correlation normaized over a similarity...

In tanaylab/metacell: Meta cell analysis for single cell RNA-seq data

Computing gene-gene correlation normaized over a similarity graph

Description

This is generating a randomized umi matrix by substituting each umi call (per cell and gene) with a umi call from the same gene on a cell that is connected to the original cell in a given similarity graph. If the similarity graph is based on some specific features that express a specific process (e.g. cell cycle), this can help in normalizing this effect and retaining correlation that are independent of it.

Usage

mcell_cgraph_norm_gcor(cgraph_id, mat_id, K = -1, min_gtot = 1000)

Arguments

cgraph_id	id of the cell graph to be used for normalization
mat_id	the matrix with umis to be analyzed
K	the maxium number of edges to consider per cell in normalization. This can be smaller than the K used in cgraph_id, to provide tighter control
min_gtot	minimal number of umis to consider when computing gene-gene correlaitons

Value

a list with two entries. gcor - is the gene correlation matrix of the downsampled matrix. r_gcor - is the correlation of the randomized umi matrix

tanaylab/metacell documentation built on Jan. 29, 2025, 1:34 a.m.