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data/GSE37382
01-medulloblastoma_data_prep.Rmd
01-medulloblastoma_data_prep.nb.html
02-medulloblastoma_clustering.Rmd
02-medulloblastoma_clustering.nb.html
03-medulloblastoma_PLIER.Rmd
03-medulloblastoma_PLIER.nb.html
04-medulloblastoma_LV_differences.Rmd
04-medulloblastoma_LV_differences.nb.html
05-machine_learning_exercise.Rmd
README.md

README.md

Machine Learning Training Module

This CCDL-designed module involves the analysis of primary medulloblastoma sample gene expression data from Northcott, et al. Nature. 2012 using some machine learning methods. It is designed to be taught in approximately 1.5 hours. It depends on knowledge gained in the intro to R module and analyses are performed within a Docker container. It covers conversion between different gene identifiers, hierarchical clustering, consensus clustering, and obtaining correlated patterns of expression in data or latent variables (LVs) through the implementation of PLIER (Pathway-Level Information Extractor). The notebooks that comprise this module are:

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