scRNA.RePACT: scRNA.RePACT optimize speed

In chenweng1991/RePACT: What the Package Does (One Line, Title Case)

scRNA.RePACT optimize speed

Description

This function is to run regression based on the number of PCs, and characteristics of samples.

Usage

scRNA.RePACT(
  OBJ,
  Sample,
  pheno,
  pheno_levels,
  is_continuous = F,
  if_donorWise = F,
  binnumber = 20,
  PCrange = "",
  RePACT_qvalCut = 0.005,
  donorWise_qvalCut = 0.01
)

Arguments

OBJ,	a scRNA-seq Seurat object
Sample,	colnames of donor or sample infomation in [e-mail]
pheno,	the column name of the "characteristics to compare" in [e-mail], e.g. diseaseStatus or BMI or HBA1C
pheno_levels,	specify the levels of pheno column. e.g. c("HT", "T2D"), specify for binary pheno
is_continuous,	if pheno is continous variable. default is F. e.g. diseaseStatus is F, BMI is T
if_donorWise,	if perform donor wise RePACT, default is F
binnumber,	number of bins for cell grouping
RePACT_qvalCut,	qvalue cutoff to determine the significant genes along the disease or other characteristics trajactory, certain cutoff for slope can be further applied
donorWise_qvalCut,	qvalue cutoff to determine the significant genes varying within donors or across donors.
PCrange.	default is "", automatically take top 10 PCs that are significant with phenotype, otherwise specify 10 PCs, e.g. 1:10 or 2:11

Value

The function return a list of objects

Examples

T2D.scRNA.RePACT <- scRNA.RePACT(OBJ=scRNA.OBJ,Sample="Donor", pheno="diseaseStat", is_continuous=F, if_donorWise=F)

chenweng1991/RePACT documentation built on Aug. 28, 2023, 6:28 p.m.