Network tuned multiple rank aggregation and applications to gene ranking

Wenhui Wang, Xianghong Jasmine Zhou, Zhenqiu Liu, Fengzhu Sun

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

With the development of various high throughput technologies and analysis methods, researchers can study different aspects of a biological phenomenon simultaneously or one aspect repeatedly with different experimental techniques and analysis methods. The output from each study is a rank list of components of interest. Aggregation of the rank lists of components, such as proteins, genes and single nucleotide variants (SNV), produced by these experiments has been proven to be helpful in both filtering the noise and bringing forth a more complete understanding of the biological problems. Current available rank aggregation methods do not consider the network information that has been observed to provide vital contributions in many data integration studies. We developed network tuned rank aggregation methods incorporating network information and demonstrated its superior performance over aggregation methods without network information. The methods are tested on predicting the Gene Ontology function of yeast proteins. We validate the methods using combinations of three gene expression data sets and three protein interaction networks as well as an integrated network by combining the three networks. Results show that the aggregated rank lists are more meaningful if protein interaction network is incorporated. Among the methods compared, CGI_RRA and CGI_Endeavour, which integrate rank lists with networks using CGI [1] followed by rank aggregation using either robust rank aggregation (RRA) [2] or Endeavour [3] perform the best. Finally, we use the methods to locate target genes of transcription factors.

Original languageEnglish (US)
Article numberS6
JournalBMC Bioinformatics
Volume16
Issue number1
DOIs
StatePublished - Jan 21 2015

Fingerprint

Rank Aggregation
Ranking
Agglomeration
Genes
Gene
Information Services
Protein Interaction Maps
Proteins
Protein Interaction Networks
Aggregation
Transcription factors
Fungal Proteins
Data integration
Protein
Nucleotides
Biological Phenomena
Gene expression
Gene Ontology
Ontology
Data Integration

All Science Journal Classification (ASJC) codes

  • Structural Biology
  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Applied Mathematics

Cite this

Wang, Wenhui ; Zhou, Xianghong Jasmine ; Liu, Zhenqiu ; Sun, Fengzhu. / Network tuned multiple rank aggregation and applications to gene ranking. In: BMC Bioinformatics. 2015 ; Vol. 16, No. 1.
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Network tuned multiple rank aggregation and applications to gene ranking. / Wang, Wenhui; Zhou, Xianghong Jasmine; Liu, Zhenqiu; Sun, Fengzhu.

In: BMC Bioinformatics, Vol. 16, No. 1, S6, 21.01.2015.

Research output: Contribution to journalArticle

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