The most informative spacing test effectively discovers biologically relevant outliers or multiple modes in expression.

ABSTRACT:

Summary

Several outlier and subgroup identification statistics (OASIS) have been proposed to discover transcriptomic features with outliers or multiple modes in expression that are indicative of distinct biological processes or subgroups. Here, we borrow ideas from the OASIS methods in the bioinformatics and statistics literature to develop the 'most informative spacing test' (MIST) for unsupervised detection of such transcriptomic features. In an example application involving 14 cases of pediatric acute megakaryoblastic leukemia, MIST more robustly identified features that perfectly discriminate subjects according to gender or the presence of a prognostically relevant fusion-gene than did seven other OASIS methods in the analysis of RNA-seq exon expression, RNA-seq exon junction e

SUBMITTER: Pawlikowska I 

PROVIDER: S-EPMC4068004 | biostudies-literature | 2014 May

REPOSITORIES: biostudies-literature