timeOmics: Time-Course Multi-Omics data integration

timeOmics is a generic data-driven framework to integrate multi-Omics longitudinal data measured on the same biological samples and select key temporal features with strong associations within the same sample group. The main steps of timeOmics are: 1. Plaform and time-specific normalization and filtering steps; 2. Modelling each biological into one time expression profile; 3. Clustering features with the same expression profile over time; 4. Post-hoc validation step.

Package details

AuthorAntoine Bodein [aut, cre], Olivier Chapleur [aut], Kim-Anh Le Cao [aut], Arnaud Droit [aut]
Bioconductor views Classification Clustering DimensionReduction FeatureExtraction GenePrediction ImmunoOncology Metabolomics Metagenomics Microarray MultipleComparison Proteomics Regression Sequencing Software TimeCourse
MaintainerAntoine Bodein <antoine.bodein.1@ulaval.ca>
Package repositoryView on Bioconductor
Installation Install the latest version of this package by entering the following in R:
if (!requireNamespace("BiocManager", quietly = TRUE))


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timeOmics documentation built on Nov. 8, 2020, 10:58 p.m.