Bioconductor Code: timeOmics (original) (raw)

[\](https://travis-ci.com/abodein/timeOmics) [\](https://codecov.io/gh/abodein/timeOmics) [\](https://www.gnu.org/licenses/gpl-3.0) # timeOmics ***timeOmics*** is a generic data-driven framework to integrate multi-Omics longitudinal data (**A.**) 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: * a pre-processing step (**B.**) Normalize and filter low-expressed features, except those not varying over time, * a modelling step (**C.**) Capture inter-individual variability in biological/technical replicates and accommodate heterogeneous experimental designs, * a clustering step (**D.**) Group features with the same expression profile over time. Feature selection step can also be used to identify a signature per cluster, * a post-hoc validation step (**E.**) Ensure clustering quality. ***timeOmics*** can be applied on both single-Omic or multi-Omics experimental design. * If you came to this page thanks to our article and you wish to access its example scripts please follow this link .* ## Installation ### Latest `GitHub` Version Install the devtools package in R, then load it and install the latest stable version of `timeOmics` from `GitHub` ```r ## install devtools if not installed if (!requireNamespace("devtools", quietly = TRUE)) install.packages("devtools") ## install timeOmics devtools::install_github("abodein/timeOmics") ``` ## Citing *Bodein A, Chapleur O, Droit A and Lê Cao K-A (2019) A Generic Multivariate Framework for the Integration of Microbiome Longitudinal Studies With Other Data Types. Front. Genet. 10:963. doi:10.3389/fgene.2019.00963* ## Maintainer Antoine Bodein (antoine.bodein.1@ulaval.ca) ## Bugs/Feature requests If you have any bugs or feature requests, [let us know](https://github.com/abodein/timeOmics\_BioC/issues). Thanks!