TY - JOUR
T1 - PathwaySplice
T2 - An R package for unbiased pathway analysis of alternative splicing in RNA-Seq data
AU - Yan, Aimin
AU - Ban, Yuguang
AU - Gao, Zhen
AU - Chen, Xi
AU - Wang, Lily
N1 - Funding Information:
This work was supported partially by NIH/NCI R01 CA158472, NIH/NCI R01 CA200987 and NIH/NCI U24 CA210954.
PY - 2018/9/15
Y1 - 2018/9/15
N2 - Pathway analysis of alternative splicing would be biased without accounting for the different number of exons or junctions associated with each gene, because genes with higher number of exons or junctions are more likely to be included in the ‘significant’ gene list in alternative splicing. We present PathwaySplice, an R package that (i) Performs pathway analysis that explicitly adjusts for the number of exons or junctions associated with each gene; (ii) visualizes selection bias due to different number of exons or junctions for each gene and formally tests for presence of bias using logistic regression; (iii) supports gene sets based on the Gene Ontology terms, as well as more broadly defined gene sets (e.g. MSigDB) or user defined gene sets; (iv) identifies the significant genes driving pathway significance and (v) organizes significant pathways with an enrichment map, where pathways with large number of overlapping genes are grouped together in a network graph.
AB - Pathway analysis of alternative splicing would be biased without accounting for the different number of exons or junctions associated with each gene, because genes with higher number of exons or junctions are more likely to be included in the ‘significant’ gene list in alternative splicing. We present PathwaySplice, an R package that (i) Performs pathway analysis that explicitly adjusts for the number of exons or junctions associated with each gene; (ii) visualizes selection bias due to different number of exons or junctions for each gene and formally tests for presence of bias using logistic regression; (iii) supports gene sets based on the Gene Ontology terms, as well as more broadly defined gene sets (e.g. MSigDB) or user defined gene sets; (iv) identifies the significant genes driving pathway significance and (v) organizes significant pathways with an enrichment map, where pathways with large number of overlapping genes are grouped together in a network graph.
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U2 - 10.1093/bioinformatics/bty317
DO - 10.1093/bioinformatics/bty317
M3 - Article
C2 - 29688305
AN - SCOPUS:85055670349
VL - 34
SP - 3220
EP - 3222
JO - Bioinformatics (Oxford, England)
JF - Bioinformatics (Oxford, England)
SN - 1367-4803
IS - 18
ER -