{ "_id": "6a1af3331d7bb097a09f82a9", "Package": "timeOmics", "Title": "Time-Course Multi-Omics data integration", "Version": "1.25.0", "Authors@R": "c(person(\"Antoine\",\"Bodein\", role = c(\"aut\", \"cre\"), email = \"antoine.bodein.1@ulaval.ca\"),\nperson(\"Olivier\", \"Chapleur\", role = c(\"aut\")),\nperson(\"Kim-Anh\", \"Le Cao\", role = c(\"aut\")),\nperson(\"Arnaud\", \"Droit\", role = c(\"aut\")))", "Description": "timeOmics is a generic data-driven framework to integrate\nmulti-Omics longitudinal data measured on the same biological\nsamples and select key temporal features with strong\nassociations within the same sample group. The main steps of\ntimeOmics are: 1. Plaform and time-specific normalization and\nfiltering steps; 2. Modelling each biological into one time\nexpression profile; 3. Clustering features with the same\nexpression profile over time; 4. 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