Linear Models for Microarray and Omics Data
Data analysis, linear models and differential expression for omics data.
Gordon Smyth [cre,aut], Yifang Hu [ctb], Matthew Ritchie [ctb], Jeremy Silver [ctb], James Wettenhall [ctb], Davis McCarthy [ctb], Di Wu [ctb], Wei Shi [ctb], Belinda Phipson [ctb], Aaron Lun [ctb], Natalie Thorne [ctb], Alicia Oshlack [ctb], Carolyn de Graaf [ctb], Yunshun Chen [ctb], Goknur Giner [ctb], Mette Langaas [ctb], Egil Ferkingstad [ctb], Marcus Davy [ctb], Francois Pepin [ctb], Dongseok Choi [ctb], Charity Law [ctb], Mengbo Li [ctb], Lizhong Chen [ctb]
grDevices, graphics, stats, utils, methods, statmod
BiasedUrn, ellipse, gplots, knitr, locfit, MASS, splines,
affy, AnnotationDbi, Biobase, BiocStyle, GO.db, illuminaio,
org.Hs.eg.db, vsn
ExonArray, GeneExpression, Transcription,
AlternativeSplicing, DifferentialExpression,
DifferentialSplicing, GeneSetEnrichment, DataImport, Bayesian,
Clustering, Regression, TimeCourse, Microarray, MicroRNAArray,
mRNAMicroarray, OneChannel, ProprietaryPlatforms, TwoChannel,
Sequencing, RNASeq, BatchEffect, MultipleComparison,
Normalization, Preprocessing, QualityControl,
BiomedicalInformatics, CellBiology, Cheminformatics,
Epigenetics, FunctionalGenomics, Genetics, ImmunoOncology,
Metabolomics, Proteomics, SystemsBiology, Transcriptomics