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TiDEomics

Time-course Differential Expression analysis of omics data

Bioconductor version: 3.24 · Package version: 0.99.5

TiDEomics provides a comprehensive workflow for multi-group time-course omics data analysis, analysing time-dominant, group-dominant, and group-specific temporal effects through pairwise differential expression, variance decomposition, and co-expression module analysis (WGCNA). The package integrates quality control, data processing, functional enrichment, and extensive visualisation. It supports datasets with missing values (e.g., mass spectrometry-based proteomics), and operates on SummarizedExperiment objects to ensure compatibility with the Bioconductor ecosystem.

Installation

if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("TiDEomics")

Details

MaintainerTianen He <tianen.he@ndm.ox.ac.uk>
AuthorTianen He [aut, cre] (ORCID: <https://orcid.org/0000-0001-6864-0723>)
LicenseGPL (>= 2)
URLhttps://github.com/hte123/TiDEomics, https://hte123.github.io/TiDEomics
Bug Reportshttps://github.com/hte123/TiDEomics/issues
Downloads rank66
Source branchdevel
biocViewsDifferentialExpression, GeneExpression, MassSpectrometry, MultipleComparison, Pathways, Proteomics, QualityControl, Software, TimeCourse, Transcriptomics, Visualization

Documentation

Download

Follow the installation instructions to use this package in your R session.

Source packageTiDEomics_0.99.5.tar.gz
Windows binary (x86_64)TiDEomics_0.99.5.zip
macOS binary (arm64)TiDEomics_0.99.5.tgz
macOS binary (x86_64)TiDEomics_0.99.5.tgz
Dependencies

Depends: R (>= 4.5.0)

Imports: circlize, clusterProfiler, ComplexHeatmap, dplyr, enrichplot, ggforce, ggh4x, ggplot2, ggplotify, ggpubr, ggrepel, ggridges, ggsci, limma, lme4, methods, patchwork, pbapply, PCAtools, randtests, scales, SummarizedExperiment, tibble, tidyr, Trendy, umap, WGCNA

Suggests: knitr, rmarkdown, BiocStyle, testthat (>= 3.1.0), plotly, enrichR, org.Hs.eg.db, org.Mm.eg.db, msigdbr, DeeDeeExperiment