Align human interactome with phenome to identify causative genes and networks underlying disease families
Identifieur interne : 000C13 ( Main/Exploration ); précédent : 000C12; suivant : 000C14Align human interactome with phenome to identify causative genes and networks underlying disease families
Auteurs : Xuebing Wu [République populaire de Chine] ; Qifang Liu [République populaire de Chine] ; Rui JiangSource :
- Bioinformatics [ 1367-4803 ] ; 2009-01-01.
Abstract
Motivation: Understanding the complexity in gene–phenotype relationship is vital for revealing the genetic basis of common diseases. Recent studies on the basis of human interactome and phenome not only uncovers prevalent phenotypic overlap and genetic overlap between diseases, but also reveals a modular organization of the genetic landscape of human diseases, providing new opportunities to reduce the complexity in dissecting the gene–phenotype association. Results: We provide systematic and quantitative evidence that phenotypic overlap implies genetic overlap. With these results, we perform the first heterogeneous alignment of human interactome and phenome via a network alignment technique and identify 39 disease families with corresponding causative gene networks. Finally, we propose AlignPI, an alignment-based framework to predict disease genes, and identify plausible candidates for 70 diseases. Our method scales well to the whole genome, as demonstrated by prioritizing 6154 genes across 37 chromosome regions for Crohn's disease (CD). Results are consistent with a recent meta-analysis of genome-wide association studies for CD. Availability: Bi-modules and disease gene predictions are freely available at the URL http://bioinfo.au.tsinghua.edu.cn/alignpi/ Contact: ruijiang@tsinghua.edu.cn Supplementary information: Supplementary data are available at Bioinformatics online.
Url:
DOI: 10.1093/bioinformatics/btn593
Affiliations:
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Recent studies on the basis of human interactome and phenome not only uncovers prevalent phenotypic overlap and genetic overlap between diseases, but also reveals a modular organization of the genetic landscape of human diseases, providing new opportunities to reduce the complexity in dissecting the gene–phenotype association. Results: We provide systematic and quantitative evidence that phenotypic overlap implies genetic overlap. With these results, we perform the first heterogeneous alignment of human interactome and phenome via a network alignment technique and identify 39 disease families with corresponding causative gene networks. Finally, we propose AlignPI, an alignment-based framework to predict disease genes, and identify plausible candidates for 70 diseases. Our method scales well to the whole genome, as demonstrated by prioritizing 6154 genes across 37 chromosome regions for Crohn's disease (CD). Results are consistent with a recent meta-analysis of genome-wide association studies for CD. Availability: Bi-modules and disease gene predictions are freely available at the URL http://bioinfo.au.tsinghua.edu.cn/alignpi/ Contact: ruijiang@tsinghua.edu.cn Supplementary information: Supplementary data are available at Bioinformatics online.</div></front></TEI><affiliations><list><country><li>République populaire de Chine</li></country><settlement><li>Pékin</li></settlement></list><tree><noCountry><name sortKey="Jiang, Rui" sort="Jiang, Rui" uniqKey="Jiang R" first="Rui" last="Jiang">Rui Jiang</name></noCountry><country name="République populaire de Chine"><noRegion><name sortKey="Wu, Xuebing" sort="Wu, Xuebing" uniqKey="Wu X" first="Xuebing" last="Wu">Xuebing Wu</name></noRegion><name sortKey="Liu, Qifang" sort="Liu, Qifang" uniqKey="Liu Q" first="Qifang" last="Liu">Qifang Liu</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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