Predictive Classification of IBS-subtype: Performance of a 250-gene RNA expression panel vs. Complete Blood Count (CBC) profiles under a Random Forest model
Abstract:In this experiment, an R-script was developed to select the best performing machine learning (ML) predictive classification algorithm for IBS subtype, and compare the performance of two datasets from the same clinical cohort: 1) The Complete Blood Count (CBC) results, and 2) A 250 gene Nanostring expression panel run on RNA from the Buffy Coat fraction. This publicly available data was compiled from open-source repositories and previously published supplementary data. Column labels were reformatted according… Show more
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