RT Journal Article
SR Electronic
T1 SPECS: A non-parameteric method to identify tissue-specific molecular features for unbalanced sample groups
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 656397
DO 10.1101/656397
A1 Everaert, Celine
A1 Volders, Pieter-Jan
A1 Morlion, Annelien
A1 Thas, Olivier
A1 Mestdagh, Pieter
YR 2019
UL http://biorxiv.org/content/early/2019/05/31/656397.abstract
AB To understand biology and differences among various tissues or cell types, one typically searches for molecular features that display characteristic abundance patterns. Several specificity metrics have been introduced to identify tissue-specific molecular features, but these either require an equal number of replicates per tissue or they can’t handle replicates at all. We describe a non-parametric specificity score that is compatible with unequal sample group sizes. To demonstrate its usefulness, the specificity score was calculated on all GTEx samples, detecting known and novel tissue-specific genes. A webtool was developed to browse these results for genes or tissues of interest. An example python implementation of SPECS is available at https://github.ugent.be/ceeverae/SPECs. The precalculated SPECS results on the GTEx data are available through a user-friendly browser at specs.cmgg.be.