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Fig. 1 | BMC Bioinformatics

Fig. 1

From: PROMO: an interactive tool for analyzing clinically-labeled multi-omic cancer datasets

Fig. 1

PROMO’s subtype discovery workflow – From data import to subtype classifier. This figure outlines the complete workflow by which PROMO can be used for identifying and characterizing clinically distinct cancer subtypes: (1) Importing genomic data together with clinical information in one of several available formats. (2) Preprocessing the data and preparing it for downstream analysis. (3) Verifying the integrity of the data, characterizing its distribution and exploring dataset properties with respect to the available clinical labels. (4) Employing clustering algorithms partition both samples and features (genes) into groups. (5) Applying enrichment tests to identify clinically significant sample subtypes and groups of co-regulated genes. and to characterize their function. (6) Statistical tests identify features that distinguish between different sample subtypes as well as survival related features. (7) Decision tree classifiers can be generated for formulating a set of rules by which a new sample can be classified

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