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🚨 Warning: This package is no longer maintained through this repo 🚨

For the current version please see myles-lewis/glmmSeq.

Lifecycle: Maturing License: MIT CRAN status Hits GitHub issues GitHub tag Downloads Travis

glmmSeq

This R package is designed to model gene expression with a general linear mixed model (GLMM). This allows us to include random effects as well as fixed effects. For the purpose of the package we use the glmer function from the lme4 package which fits a GLMM.

This package focuses in particular on changes in genes expression between different response or treatment groups over time.

Loading the package

From CRAN

install.packages("glmmSeq")

From Github

devtools::install_github("KatrionaGoldmann/glmmSeq")

Locally

You can also download the source directory and load the functions individually:

functions = list.files("./R", full.names = TRUE)
invisible(lapply(functions, source))

But you will need to load in the additional libraries then:

# Install CRAN packages
invisible(lapply(c("MASS", "car", "ggplot2", "ggpubr", "lme4", 
                   "lmerTest", "methods", "parallel", "plotly", 
                   "pbapply", "pbmcapply"),
                 function(p){
                   if(! p %in% rownames(installed.packages())) {
                     install.packages(p)
                   }
                   library(p, character.only=TRUE)
                 }))

# Install BioConductor packages
if (!requireNamespace("BiocManager", quietly = TRUE))
  install.packages("BiocManager")
invisible(lapply(c("qvalue"), function(p){
  if(! p %in% rownames(installed.packages())) BiocManager::install(p)
  library(p, character.only=TRUE)
}))

Example script

For examples see the vignette.

Reference

glmmSeq was developed by the bioinformatics team at the Experimental Medicine & Rheumatology department and Centre for Translational Bioinformatics at Queen Mary University London.

If you use this package please cite as:

citation("glmmSeq")

## To cite package ‘glmmSeq’ in publications use:
##
##  Myles Lewis, Katriona Goldmann, Elisabetta Sciacca, Cankut Cubuk and Anna Surace (2021). 
##  glmmSeq: General Linear Mixed Models for Gene-level Differential Expression. 
##  R package version 0.5.4. https://github.com/KatrionaGoldmann/glmmSeq
##
## A BibTeX entry for LaTeX users is
##
##  @Manual{,
##    title = {glmmSeq: General Linear Mixed Models for Gene-level Differential Expression},
##    author = {Myles Lewis and Katriona Goldmann and Elisabetta Sciacca and Cankut Cubuk and Anna Surace},
##    year = {2022},
##    note = {R package version 0.5.4},
##    url = {https://github.com/KatrionaGoldmann/glmmSeq},
##  }