Multivariate methods for multiomics data analysis
Due to recent technological advancements, multi-omics has emerged as a trending approach to gain deeper insights into molecular mechanisms. Multi-omics approach involves integrating information from various level of central dogma of biology such as Genomics, Transcriptomics, Proteomics, Epigenetics and Metabolomics. Multi-omics has seen it's tremendous application in oncology. Since the information obtained at individual omics layer are highly heterogeneous, it is a challenging task to integrate them and derive useful information. This course aim at introducing you to various multivariate, clustering and integrative methods such as PCA, MDS, PLS, PLSDA, KC, HC, NMF etc., that are widely used in multi-omics data integration.
Course Contents
Data integrity check methods
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Multiomics Clustering
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Multiple co inertia analysis (MCIA) for multiomics data integration
Duration
- Online training.
- 15-20 hr depending upon the speed
- Flexible timings as per your conveniences.
Extra Benefits
- Course certificate will be provided
- Course materials will be provided
- Post training, if you need any help in writing codes for solving any of your research problem, assistance and guidance will be provided.
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