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


BACKGROUND
MIST will be freely available in the OASIS R package at http://www.stjuderesearch.org/site/depts/biostats


BACKGROUND
stanley.pounds@stjude.org


BACKGROUND
Supplementary data are available at Bioinformatics online.
Departments of Biostatistics, St. Jude Children's Research Hospital, Memphis, TN, USA, Institue of Mathematics, University of Silesia, Katowice, Poland, Department of Computational Biology and Department of Oncology, St. Jude Children's Research Hospital, Memphis, TN, USA.
Iwona
I
Pawlikowska
Gang
G
Wu
Michael
M
Edmonson
Zhifa
Z
Liu
Tanja
T
Gruber
Jinghui
J
Zhang
Stan
S
Pounds
D000328:Adult; D001699:Biometry; D002648:Child; D005091:Exons; D005260:Female; D015870:Gene Expression; D006801:Humans; D015470:Leukemia, Myeloid, Acute / Q000235:genetics; D008297:Male; D008957:Models, Genetic; D017423:Sequence Analysis, RNA / Q000379:methods*