README.md

In gefeizhang/ZIAQ: A quantile regression method for differential expression analysis of single-cell RNA-seq data

ZIAQ: A quantile regression method for differential expression analysis of single-cell RNA-seq data

A statistical differential expression analysis method that accounts for both dropout rates and complex scRNA-seq data distributions in the same model

Installation Instructions

You may directly download source file ZIAQ_1.0.tar.gz from github link https://github.com/gefeizhang/ZIAQ/blob/master/ZIAQ_1.0.tar.gz

Or you may use 'devtools' to install it from github

library(devtools)
install_github("gefeizhang/ZIAQ")

It is on the process to submit to 'CRAN', and can be downloaded from 'CRAN' once it is accepted.

Examples

Run ZIAQ for indiviual gene

y = round(100* runif(100))
colDat = data.frame(condition = rep(c(1, 0), e = 50))
res = ziaq_fit(y, colDat = colDat,  formula = ~ condition,
          group = 'condition', probs = c(0.25, 0.5, 0.75),
          log_i = TRUE )

Run ZIAQ for scRNA gene matrix

# simulate gene matrix
ymatrix = matrix(round(100* runif(100*500)), ncol = 100)
rownames(ymatrix) = paste0('gene', 1:500)

# simulate cell conditions
colDat = data.frame(condition = rep(c(1, 0), e = 50))

res = ziaq(ymatrix, colDat, formula = ~ condition,
      group = 'condition', probs = c(0.25, 0.5, 0.75),
      log_i = TRUE, parallel = FALSE, no.core = 1)

Citation

ZIAQ: A quantile regression method for differential expression analysis of single-cell RNA-seq data Wenfei Zhang, Ying Wei, Donghui Zhang, Ethan Y Xu, Bioinformatics, btaa098

gefeizhang/ZIAQ documentation built on Feb. 26, 2020, 6:15 p.m.