The most informative spacing test effectively discovers biologically relevant outliers or multiple modes in expression
| Autor: | Iwona Pawlikowska, Stan Pounds, Tanja A. Gruber, Zhifa Liu, Gang Wu, Michael N. Edmonson, Jinghui Zhang |
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| Rok vydání: | 2014 |
| Předmět: |
Adult
Male Statistics and Probability Biometry Gene Expression Computational biology Biology Biochemistry Exon Humans Child Molecular Biology Genetics Models Genetic Sequence Analysis RNA Exons Multiple modes Original Papers Expression (mathematics) Pediatric Acute Megakaryoblastic Leukemia Computer Science Applications Leukemia Myeloid Acute Computational Mathematics R package Computational Theory and Mathematics Expression data Outlier Female Identification (biology) |
| Zdroj: | Bioinformatics. 30:1400-1408 |
| ISSN: | 1367-4811 1367-4803 |
| Popis: | 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 expression and micorarray exon expression data. MIST was also effective at identifying features related to gender or molecular subtype in an example application involving 157 adult cases of acute myeloid leukemia. Availability: MIST will be freely available in the OASIS R package at http://www.stjuderesearch.org/site/depts/biostats Contact: stanley.pounds@stjude.org Supplementary information: Supplementary data are available at Bioinformatics online. |
| Databáze: | OpenAIRE |
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