METCC: METric learning for Confounder Control Making distance matter in high dimensional biological analysis

7 Dec 2018Kabir ManghnaniAdam DrakeNathan WanImran Haque

High-dimensional data acquired from biological experiments such as next generation sequencing are subject to a number of confounding effects. These effects include both technical effects, such as variation across batches from instrument noise or sample processing, or institution-specific differences in sample acquisition and physical handling, as well as biological effects arising from true but irrelevant differences in the biology of each sample, such as age biases in diseases... (read more)

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