bhagwataditya/importomics: Unified statistal Modeling of Omics Data

This package unifies access to Statistal Modeling of Omics Data. Across linear modeling engines (lm, lme, lmer, limma, and wilcoxon). Across coding systems (treatment, difference, deviation, etc). Across model formulae (with/without intercept, random effect, interaction or nesting). Across omics platforms (microarray, rnaseq, msproteomics, affinity proteomics, metabolomics). Across projection methods (pca, pls, sma, lda, spls, opls). It provides a fast enrichment analysis implementation. And an intuitive contrastogram visualisation to summarize contrast effects in complex designs.

Getting started

Package details

Bioconductor views DataImport DifferentialExpression DimensionReduction GeneExpression GeneSetEnrichment MassSpectrometry Metabolomics Microarray Preprocessing PrincipalComponent Proteomics RNASeq Regression Software Transcription Transcriptomics
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
bhagwataditya/importomics documentation built on May 11, 2024, 5:24 a.m.