CRAN/E | glmmSeq

glmmSeq

General Linear Mixed Models for Gene-Level Differential Expression

Installation

About

Using mixed effects models to analyse longitudinal gene expression can highlight differences between sample groups over time. The most widely used differential gene expression tools are unable to fit linear mixed effect models, and are less optimal for analysing longitudinal data. This package provides negative binomial and Gaussian mixed effects models to fit gene expression and other biological data across repeated samples. This is particularly useful for investigating changes in RNA-Sequencing gene expression between groups of individuals over time, as described in: Rivellese, F., Surace, A. E., Goldmann, K., Sciacca, E., Cubuk, C., Giorli, G., ... Lewis, M. J., & Pitzalis, C. (2022) Nature medicine doi:10.1038/s41591-022-01789-0.

myles-lewis.github.io/glmmSeq/
github.com/myles-lewis/glmmSeq
Bug report File report

Key Metrics

Version 0.5.5
R ≥ 3.6.0
Published 2022-10-08 165 days ago
Needs compilation? no
License MIT
License File
CRAN checks glmmSeq results
Language en-gb

Downloads

Last 24 hours 13 -65%
Last 7 days 99 +15%
Last 30 days 298 +2%
Last 90 days 820 -25%
Last 365 days 3.695 -11%

Maintainer

Maintainer

Myles Lewis

myles.lewis@qmul.ac.uk

Authors

Myles Lewis

aut / cre

Katriona Goldmann

aut

Elisabetta Sciacca

aut

Cankut Cubuk

ctb

Anna Surace

ctb

Material

README
NEWS
Reference manual
Package source

Vignettes

glmmSeq

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

glmmSeq archive

Depends

R ≥ 3.6.0

Imports

MASS
car
stats
ggplot2
ggpubr
glmmTMB
graphics
lme4
lmerTest
methods
plotly
qvalue
pbapply
pbmcapply

Suggests

knitr
rmarkdown
kableExtra
DESeq2
edgeR
emmeans