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 |
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Bioconductor views | Classification Clustering DimensionReduction FeatureExtraction GenePrediction ImmunoOncology Metabolomics Metagenomics Microarray MultipleComparison Proteomics Regression Sequencing Software TimeCourse |
Maintainer | |
License | GPL-3 |
Version | 1.15.11 |
Package repository | View on GitHub |
Installation |
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