iDESC: iDESC: main function for DE analysis using zero-inflated...

In yl883/iDESC: iDESC: Identifying differential expression in single-cell RNA sequencing data with multiple subjects

iDESC: main function for DE analysis using zero-inflated negative binomial mixed model

Description

iDESC: main function for DE analysis using zero-inflated negative binomial mixed model

Usage

iDESC(
  mat,
  meta,
  subject_var,
  group_var,
  norm_opt = c("SeqDepth", "SizeFactor", "User", "None"),
  user_sf = NULL,
  sub_cell_filtering = 5,
  gene_sub_filtering = 0,
  gene_cell_filtering = 0.05,
  ncell_filtering = 1,
  span = 0.05
)

Arguments

mat	Count matrix
meta	Data frame including information for cells
subject_var	The name of subject information in meta
group_var	The name of group/disease information for DE analysis in meta
norm_opt	Option for normalizing factors
user_sf	Option for user-specific normalizing factors
sub_cell_filtering	Filtering on cells within each subject
gene_sub_filtering	Filtering on genes based on expression in each subject
gene_cell_filtering	Filtering on genes based on expression across all cells
ncell_filtering	Filtering on cells based on the number of genes expressed
span	smoothing parameter for LOESS curve

Value

A result table contains parameter estimation

Examples

library(iDESC)
data(IPF_example)
mat=IPF_example$mat
meta=IPF_example$meta
sequencing_depth=IPF_example$meta$sequencing_depth
result=iDESC(mat,meta,subject_var="subject",group_var="disease",norm_opt="User",user_sf = sequencing_depth,span = 0.7)

yl883/iDESC documentation built on Aug. 2, 2022, 1:21 a.m.