Journal
NUCLEIC ACIDS RESEARCH
Volume 44, Issue D1, Pages D567-D573Publisher
OXFORD UNIV PRESS
DOI: 10.1093/nar/gkv1228
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Funding
- European Union 7th Framework Programme [602273]
- Metakids Foundation
- Centre for Systems Biology and Bioenergetics [CSBR09/013V]
- European Union's FP7 large scale integrated network Gencodys [HEALTH-241995]
- SYSCILIA [241955]
- Centre for Systems Biology and Bioenergetics
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We have developed the Weighted Gene Expression Tool and database (WeGET, http://weget.cmbi.umcn.nl) for the prediction of new genes of a molecular system by correlated gene expression. WeGET utilizes a compendium of 465 human and 560 murine gene expression datasets that have been collected from multiple tissues under a wide range of experimental conditions. It exploits this abundance of expression data by assigning a high weight to datasets in which the known genes of a molecular system are harmoniously up-and down-regulated. WeGET ranks new candidate genes by calculating their weighted co-expression with that system. A weighted rank is calculated for human genes and their mouse orthologs. Then, an integrated gene rank and p-value is computed using a rank-order statistic. We applied our method to predict novel genes that have a high degree of co-expression with Gene Ontology terms and pathways from KEGG and Reactome. For each query set we provide a list of predicted novel genes, computed weights for transcription datasets used and cell and tissue types that contributed to the final predictions. The performance for each query set is assessed by 10-fold cross-validation. Finally, users can use the WeGET to predict novel genes that coexpress with a custom query set.
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