Learn R Programming

QuasiSeq (version 1.0-11-0)

Analyzing RNA Sequencing Count Tables Using Quasi-Likelihood

Description

Identify differentially expressed genes in RNA-seq count data using quasi-Poisson or quasi-negative binomial models with 'QL', 'QLShrink' and 'QLSpline' methods described by Lund, Nettleton, McCarthy, and Smyth (2012) . Report bias-reduced estimates of log fold changes.

Copy Link

Version

Install

install.packages('QuasiSeq')

Monthly Downloads

108

Version

1.0-11-0

License

GPL (>= 2)

Maintainer

Steve Lund

Last Published

August 15th, 2022

Functions in QuasiSeq (1.0-11-0)

fbrNBglm

Firth-Type Bias-Reduced Negative Binomial Log-Linear Model
QL.fit

Fit quasi-likelihood models to matrix of RNA-seq expression count data
negbin

Negative Binomial Family
glmSolvers

Generalized linear model (glm) solvers
mockRNASeqData

A Simulated RNA-Seq Data Set
coef.glm

Coefficient and Bias From Generalized Linear Model Fit
QL.results

Obtain p-values and q-values using results from QL.fit
nlSolvers

Nonlinear equation solvers
NBDev

Fit a negative binomial GLM for given design matrix
PoisDev

Compute Poisson deviances (up to a constant) for given design matrix