coherentFraction: Calculate coherent fraction for feature expression program.

In NMikolajewicz/scMiko: scRNAseq analysis functions. Developed using Seurat framework.

Calculate coherent fraction for feature expression program.

Description

Calculate fraction of genes that are correlated with feature expression program. Performed on a per-cluster basis ("seurat_clusters" in 'object' meta data).

Usage

coherentFraction(
  object,
  score.matrix,
  genelist,
  method = c("pearson", "spearman"),
  assay = DefaultAssay(object),
  slot = "data",
  subsample.cluster.n = 500,
  nworkers = 1,
  verbose = T
)

Arguments

object	Seurat Object.
score.matrix	matrix of feature expression program. Can be computed using 'AddModuleScores', 'AddSModuleScores', 'mikoScore', among others.
method	Correlation method: "pearson" or "spearman". Default is "pearson".
assay	Name of assay to use.
slot	Use expression data from this slot in 'object'.
subsample.cluster.n	number of cells to subsample within each cluster ("seurat_clusters" in 'object' meta data). Default is 500.
nworkers	Number of workers for parallel implementation. Default is 1.
verbose	Print progress. Default is TRUE.
geneset	gene set list used for obtaining 'score.matrix' (e.g., gene set provided as input into 'mikoScore' or 'AddSModuleScores').

Value

data.frame containing cluster-level coherent fractions.

Author(s)

Nicholas Mikolajewicz

See Also

AddSModuleScore for standardized module scoring, mikoScore for miko scoring

Examples

so.query <-  AddSModuleScore(object = so.query, features = gene.list)

raw.mat <- so.query@misc[["raw_score"]]
colnames(raw.mat) <- gsub("raw_", "", colnames(raw.mat))
df.cscore <- coherentFraction(object = so.query, score.matrix =raw.mat, nworkers = 20,
                              genelist = gene.list, assay = DefaultAssay(so.query), slot = "data", subsample.cluster.n = 500)

NMikolajewicz/scMiko documentation built on June 28, 2023, 1:41 p.m.