get_pseudobulk_logCPM_exprs: get_pseudobulk_logCPM_exprs

In saeyslab/muscatWrapper: Wrapper functions around muscat for differential expression analysis of multi-sample multi-condition scRNAseq datasets

get_pseudobulk_logCPM_exprs

Description

get_pseudobulk_logCPM_exprs Calculate the 'library-size' normalized pseudbulk counts per sample for each gene - returned values are similar to logCPM.

Usage

get_pseudobulk_logCPM_exprs(sce, sample_id, celltype_id, group_id, covariates = NA, assay_oi_pb = "counts", fun_oi_pb = "sum")

Arguments

sce	SingleCellExperiment object of the scRNAseq data of interest.
sample_id	Name of the meta data column that indicates from which sample/patient a cell comes from (in sce)
celltype_id	Name of the column in the meta data of sce that indicates the cell type of a cell.
group_id	Name of the meta data column that indicates from which group/condition a cell comes from (in sce)
covariates	NA if no covariates should be corrected for. If there should be corrected for covariates, this argument should be the name(s) of the columns in the meta data that indicate the covariate(s).
assay_oi_pb	Indicates which information of the assay of interest should be used (counts, scaled data,...). Default: "counts". See 'muscat::aggregateData'.
fun_oi_pb	Indicates way of doing the pseudobulking. Default: "sum". See 'muscat::aggregateData'.

Value

Data frame with logCPM-like values of the library-size corrected pseudobulked counts ('pb_sample') per gene per sample. pb_sample = log2( ((pb_raw/effective_library_size) \* 1000000) + 1). effective_library_size = lib.size \* norm.factors (through edgeR::calcNormFactors).

Examples

## Not run: 
library(dplyr)
sample_id = "tumor"
group_id = "pEMT"
celltype_id = "celltype"
pseudobulk_logCPM_exprs = get_pseudobulk_logCPM_exprs(sce = sce, sample_id = sample_id, celltype_id =  celltype_id, group_id = group_id)

## End(Not run)

saeyslab/muscatWrapper documentation built on March 11, 2023, 6:14 p.m.