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PMID: 22327835 Published · epublish English Comparative Study Journal Article Research Support, Non-U.S. Gov't

Comparative analysis of algorithms for integration of copy number and expression data.

Nature methods ·Vol. 9 ·No. 4 ·2012-02-12 ·Pages 351-5

Louhimo R, Lepikhova T, Monni O, Hautaniemi S

Abstract

Chromosomal instability is a hallmark of cancer, and genes that display abnormal expression in aberrant chromosomal regions are likely to be key players in tumor progression. Identifying such driver genes reliably requires computational methods that can integrate genome-scale data from several sources. We compared the performance of ten algorithms that integrate copy-number and transcriptomics data from 15 head and neck squamous cell carcinoma cell lines, 129 lung squamous cell carcinoma primary tumors and simulated data. Our results revealed clear differences between the methods in terms of sensitivity and specificity as well as in their performance in small and large sample sizes. Results of the comparison are available at http://csbi.ltdk.helsinki.fi/cn2gealgo/.

MeSH Terms
Algorithms Carcinoma, Squamous Cell/genetics Cell Line, Tumor Computational Biology Gene Dosage/genetics Gene Expression Regulation, Neoplastic/genetics Head and Neck Neoplasms/genetics Humans Lung Neoplasms/genetics Neoplasms/genetics Software Statistics as Topic Transcriptome/genetics
Authors & Affiliations
4 authors, click to expand affiliations / ORCID
Louhimo Riku
Research Programs Unit, Genome-Scale Biology and Institute of Biomedicine, Biochemistry and Developmental Biology, Faculty of Medicine, University of Helsinki, Helsinki, Finland.
Lepikhova Tatiana
Monni Outi
Hautaniemi Sampsa
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Article Info
Journal
Nature methods
Abbr.
Nat Methods
ISSN
1548-7105
DOI
10.1038/nmeth.1893
Published
2012-02-12
Epub
2012-00-12
Pages
351-5
Language
English
Region
United States
NLM ID
101215604
Subset
IM
External Links
PubMed source DOI: 10.1038/nmeth.1893 View journal details
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