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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("myles-lewis/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/myles-lewis/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/myles-lewis/glmmSeq},
##  }

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Version

Install

install.packages('glmmSeq')

Monthly Downloads

342

Version

0.5.5

License

MIT + file LICENSE

Issues

Pull Requests

Stars

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Maintainer

Myles Lewis

Last Published

October 8th, 2022

Functions in glmmSeq (0.5.5)

tpm

TPM count data from PEAC
modelPlot

Mixed model effects plot
summary.lmmSeq

Summarise a 'glmmSeq'/'lmmSeq' object
lmmSeq

Linear mixed models for data matrix
metadata

Minimal metadata from PEAC
glmmQvals

Glmm Sequencing qvalues
GlmmSeq-class

An S4 class to define the glmmSeq output
glmmSeq

GLMM with negative binomial distribution for sequencing count data
glmmRefit

Refit mixed effects model
lmmSeq-class

An S4 class to define the lmmSeq output
ggmodelPlot

Mixed model effects plot using ggplot2
fcPlot

Plotly or ggplot fold change plots
maPlot

MA plots