Unknown

Dataset Information

0

OrthoClust: an orthology-based network framework for clustering data across multiple species.


ABSTRACT: Increasingly, high-dimensional genomics data are becoming available for many organisms.Here, we develop OrthoClust for simultaneously clustering data across multiple species. OrthoClust is a computational framework that integrates the co-association networks of individual species by utilizing the orthology relationships of genes between species. It outputs optimized modules that are fundamentally cross-species, which can either be conserved or species-specific. We demonstrate the application of OrthoClust using the RNA-Seq expression profiles of Caenorhabditis elegans and Drosophila melanogaster from the modENCODE consortium. A potential application of cross-species modules is to infer putative analogous functions of uncharacterized elements like non-coding RNAs based on guilt-by-association.

SUBMITTER: Yan KK 

PROVIDER: S-EPMC4289247 | biostudies-literature | 2014 Aug

REPOSITORIES: biostudies-literature

altmetric image

Publications

OrthoClust: an orthology-based network framework for clustering data across multiple species.

Yan Koon-Kiu KK   Wang Daifeng D   Rozowsky Joel J   Zheng Henry H   Cheng Chao C   Gerstein Mark M  

Genome biology 20140828 8


Increasingly, high-dimensional genomics data are becoming available for many organisms.Here, we develop OrthoClust for simultaneously clustering data across multiple species. OrthoClust is a computational framework that integrates the co-association networks of individual species by utilizing the orthology relationships of genes between species. It outputs optimized modules that are fundamentally cross-species, which can either be conserved or species-specific. We demonstrate the application of  ...[more]

Similar Datasets

| S-EPMC7078030 | biostudies-literature
| S-EPMC4642618 | biostudies-literature
2022-10-31 | GSE186566 | GEO
| S-EPMC5428484 | biostudies-literature
| S-EPMC6221474 | biostudies-literature
| S-EPMC4045337 | biostudies-literature
| S-EPMC10830981 | biostudies-literature
| S-EPMC4138177 | biostudies-literature
2016-01-12 | E-GEOD-76705 | biostudies-arrayexpress
2016-01-12 | GSE76705 | GEO