Journal article
Coex-Rank: An approach incorporating co-expression information for combined analysis of microarray data
Journal of integrative bioinformatics, Vol.9(1), pp.32-43
03/01/2012
DOI: 10.1515/jib-2012-208
PMCID: PMC3482100
PMID: 22842118
Abstract
Microarrays have been widely used to study differential gene expression at the genomic level. They can also provide genome-wide co-expression information. Biologically related datasets from independent studies are publicly available, which requires robust combined approaches for integration and validation. Previously, meta-analysis has been adopted to solve this problem.
As an alternative to meta-analysis, for microarray data with high similarity in biological experimental design, a more direct combined approach is possible. Gene-level normalization across datasets is motivated by the different scale and distribution of data due to separate origins. However, there has been limited discussion about this point in the past. Here we describe a combined approach for microarray analysis, including gene-level normalization and Coex-Rank approach. After normalization, a linear modeling process is used to identify lists of differentially expressed genes. The Coex-Rank approach incorporates co-expression information into a rank-aggregation procedure. We applied this computational approach to our data, which illustrated an improvement in statistical power and a complementary advantage of the Coex-Rank approach from a biological perspective.
Our combined approach for microarray data analysis (Coex-rank) is based on normalization, which is naturally driven. The Coex-rank process not only takes advantage of merging the power of multiple methods regarding normalization but also assists in the discovery of functional clusters of genes.
Details
- Title: Subtitle
- Coex-Rank: An approach incorporating co-expression information for combined analysis of microarray data
- Creators
- Jinlu Cai - Albert Einstein College of MedicineHenry L Keen - University of IowaCurt D Sigmund - University of IowaThomas L Casavant - University of Iowa
- Resource Type
- Journal article
- Publication Details
- Journal of integrative bioinformatics, Vol.9(1), pp.32-43
- DOI
- 10.1515/jib-2012-208
- PMID
- 22842118
- PMCID
- PMC3482100
- NLM abbreviation
- J Integr Bioinform
- ISSN
- 1613-4516
- eISSN
- 1613-4516
- Publisher
- De Gruyter
- Number of pages
- 12
- Language
- English
- Date published
- 03/01/2012
- Academic Unit
- Roy J. Carver Department of Biomedical Engineering; Electrical and Computer Engineering; Molecular Physiology and Biophysics; Neuroscience and Pharmacology; Iowa Institute of Human Genetics
- Record Identifier
- 9984196972302771
Metrics
13 Record Views