ArticleNature methods2012
Comparative analysis of algorithms for integration of copy number and expression data.
Article in Nature methods, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
22 citing papers in PubMed.
- A Bayesian-Based Integrative Bioinformatics Analysis Nominates Oncogenic Drivers in Neuroblastoma.Clinical and translational science · 2026Article
- Genome-wide quantification of copy-number aberration impact on gene expression in ovarian high-grade serous carcinoma.BMC cancer · 2024Article
- CiberAMP: AnBiology · 2022Article
- Set-Wise Differential Interaction Between Copy Number Alterations and Gene Expressions of Lower-Grade Glioma Reveals Prognosis-Associated Pathways.Entropy (Basel, Switzerland) · 2020Article
- A comparative study of multi-omics integration tools for cancer driver gene identification and tumour subtyping.Briefings in bioinformatics · 2020Article
- Integration of transcriptome and proteome profiles in glioblastoma: looking for the missing link.BMC molecular biology · 2018Article
- FocalScan: Scanning for altered genes in cancer based on coordinated DNA and RNA change.Nucleic acids research · 2016Article
- Importance of rare gene copy number alterations for personalized tumor characterization and survival analysis.Genome biology · 2016Article
- Practical aspects of NGS-based pathways analysis for personalized cancer science and medicine.Oncotarget · 2016Review
- Liprin-α1 is a regulator of vimentin intermediate filament network in the cancer cell adhesion machinery.Scientific reports · 2016Article
- A survey of best practices for RNA-seq data analysis.Genome biology · 2016Review
- Data integration to prioritize drugs using genomics and curated data.BioData mining · 2016Article
- Efficient exploration of pan-cancer networks by generalized covariance selection and interactive web content.Nucleic acids research · 2015Article
- Computational characterisation of cancer molecular profiles derived using next generation sequencing.Contemporary oncology (Poznan, Poland) · 2015Review
- Genomic DNA Copy Number Aberrations, Histological Diagnosis, Oral Subsite and Aneuploidy in OPMDs/OSCCs.PloS one · 2015Article
- Detection of candidate tumor driver genes using a fully integrated Bayesian approach.Statistics in medicine · 2014Article
- Principles and methods of integrative genomic analyses in cancer.Nature reviews. Cancer · 2014Review
- Integrated exon level expression analysis of driver genes explain their role in colorectal cancer.PloS one · 2014Article
- An integrative characterization of recurrent molecular aberrations in glioblastoma genomes.Nucleic acids research · 2013Article
- Oncodrive-CIS: a method to reveal likely driver genes based on the impact of their copy number changes on expression.PloS one · 2013Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
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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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.