Comparative Analysis of Algorithms for Integration of Copy Number and Expression Data

Overview

Journal Nat Methods

Specialties Biomedical Engineering
Pathology

Date 2012 Feb 14

PMID 22327835

Citations 21

Authors

Riku Louhimo

Tatiana Lepikhova

Outi Monni

Sampsa Hautaniemi

Affiliations

Soon will be listed here.

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/.

Citing Articles

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CiberAMP: An Package to Identify Differential mRNA Expression Linked to Somatic Copy Number Variations in Cancer Datasets.

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A comparative study of multi-omics integration tools for cancer driver gene identification and tumour subtyping.

Sathyanarayanan A, Gupta R, Thompson E, Nyholt D, Bauer D, Nagaraj S Brief Bioinform. 2019; 21(6):1920-1936.

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