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

Louhimo, Riku; Lepikhova, Tatiana; Monni, Outi; Hautaniemi, Sampsa

doi:10.1038/nmeth.1893

Cited by 31Genomic variations and chromosomal abnormalitiesCancer Genomics and DiagnosticsGene expression and cancer classification

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

Louhimo, Riku, Lepikhova, Tatiana, Monni, Outi, Hautaniemi, Sampsa·2012·Nature Methods

DOI 10.1038/nmeth.1893

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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/.

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The combination of RNA-seq and re-sequencing can be used both to remove false positives when inferring fusion genes and to analyze copy number alterations.
“Moreover, the combination of RNA-seq and re-sequencing can be used both to remove false positives when inferring fusion genes [88] and to analyze copy number alterations [137].”
From A survey of best practices for RNA-seq data analysis (2016) · cites this paper as [137]

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Authors: Louhimo, R., Lepikhova, T., Monni, O., & Hautaniemi, S.
Affiliations: University of Helsinki (FI)
Corresponding author: Hautaniemi, Sampsa
ORCID: Monni, Outi
Hautaniemi, Sampsa
Venue: Nature Methods
Publisher: Springer Science and Business Media LLC
Published: 2012-02-12
Volume: 9
Issue: 4
Pages: 351-355
ISSN: 1548-7091 (ISSN-L)
1548-7105
DOI: 10.1038/nmeth.1893
OpenAlex: W1973978516
Cited by: 30
References: 73
Citations by year: 2026: 1 · 2024: 1 · 2022: 1 · 2020: 1 · 2019: 1 · 2018: 3 · 2017: 2 · 2016: 6 · 2015: 3 · 2014: 6 · 2013: 4 · 2012: 1
FWCI: 2.69
Type: journal article
Language: en
Open access: closed
Licence: www.springer.com/tdm (tdm)
Locations: Nature Methods (publishedVersion)
PubMed (publishedVersion)
Topics: Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genomic variations and chromosomal abnormalities
Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer Genomics and Diagnostics
Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene expression and cancer classification
Keywords: copy number variation, gene expression, data integration, driver genes, chromosomal instability, tumor progression, algorithm comparison, head and neck squamous cell carcinoma, lung squamous cell carcinoma, cancer cell lines, sensitivity and specificity, sample size
MeSH terms: Algorithms, Carcinoma, Squamous Cell, Head and Neck Neoplasms, Humans, Lung Neoplasms, Neoplasms, Software, Statistics as Topic, Gene Expression Regulation, Neoplastic, Gene Dosage, Computational Biology, Cell Line, Tumor, Transcriptome

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

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