Journal article
Integrative prescreening in analysis of multiple cancer genomic studies
BMC bioinformatics, Vol.13(1), pp.168-168
07/16/2012
DOI: 10.1186/1471-2105-13-168
PMCID: PMC3436748
PMID: 22799431
Abstract
Background: In high throughput cancer genomic studies, results from the analysis of single datasets often suffer from a lack of reproducibility because of small sample sizes. Integrative analysis can effectively pool and analyze multiple datasets and provides a cost effective way to improve reproducibility. In integrative analysis, simultaneously analyzing all genes profiled may incur high computational cost. A computationally affordable remedy is prescreening, which fits marginal models, can be conducted in a parallel manner, and has low computational cost.Results: An integrative prescreening approach is developed for the analysis of multiple cancer genomic datasets. Simulation shows that the proposed integrative prescreening has better performance than alternatives, particularly including prescreening with individual datasets, an intensity approach and meta-analysis. We also analyze multiple microarray gene profiling studies on liver and pancreatic cancers using the proposed approach.Conclusions: The proposed integrative prescreening provides an effective way to reduce the dimensionality in cancer genomic studies. It can be coupled with existing analysis methods to identify cancer markers. © 2012 Song et al.; licensee BioMed Central Ltd.
Details
- Title: Subtitle
- Integrative prescreening in analysis of multiple cancer genomic studies
- Creators
- Rui Song - Colorado State UniversityJian Huang - University of IowaShuangge Ma - Yale University
- Resource Type
- Journal article
- Publication Details
- BMC bioinformatics, Vol.13(1), pp.168-168
- DOI
- 10.1186/1471-2105-13-168
- PMID
- 22799431
- PMCID
- PMC3436748
- NLM abbreviation
- BMC Bioinformatics
- ISSN
- 1471-2105
- eISSN
- 1471-2105
- Publisher
- BioMed Central
- Language
- English
- Date published
- 07/16/2012
- Academic Unit
- Statistics and Actuarial Science
- Record Identifier
- 9984257734202771
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