ArticleBioinformatics (Oxford, England)2013
Precise inference of copy number alterations in tumor samples from SNP arrays.
Article in Bioinformatics (Oxford, England), 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
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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
10 citing papers in PubMed, 1 synthesis or guideline pooled it, 15 citations in OpenAlex.
- Fully exploiting SNP arrays: a systematic review on the tools to extract underlying genomic structure.Briefings in bioinformatics · 2022Pooled it
- Review
- Nuclear envelope, chromatin organizers, histones, and DNA: The many achilles heels exploited across cancers.Frontiers in cell and developmental biology · 2022Review
- Early Breast Cancer Evolution by Autosomal Broad Copy Number Alterations.International journal of genomics · 2022Article
- Identification of recurrent noncoding mutations in B-cell lymphoma using capture Hi-C.Blood advances · 2019Article
- CloneCNA: detecting subclonal somatic copy number alterations in heterogeneous tumor samples from whole-exome sequencing data.BMC bioinformatics · 2016Article
- An integrated analysis tool for analyzing hybridization intensities and genotypes using new-generation population-optimized human arrays.BMC genomics · 2016Article
- Detection of gene copy number alterations in DCIS and invasive breast cancer by QM-FISH.American journal of translational research · 2016Article
- TAFFYS: An Integrated Tool for Comprehensive Analysis of Genomic Aberrations in Tumor Samples.PloS one · 2015Article
- Somatic mosaicism in the human genome.Genes · 2014Review
Corrections and comments
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
motivationThe accurate detection of copy number alterations (CNAs) in human genomes is important for understanding susceptibility to cancer and mechanisms of tumor progression. CNA detection in tumors from single nucleotide polymorphism (SNP) genotyping arrays is a challenging problem due to phenomena such as aneuploidy, stromal contamination, genomic waves and intra-tumor heterogeneity, issues that leading methods do not optimally address.
resultsHere we introduce methods and software (PennCNV-tumor) for fast and accurate CNA detection using signal intensity data from SNP genotyping arrays. We estimate stromal contamination by applying a maximum likelihood approach over multiple discrete genomic intervals. By conditioning on signal intensity across the genome, our method accounts for both aneuploidy and genomic waves. Finally, our method uses a hidden Markov model to integrate multiple sources of information, including total and allele-specific signal intensity at each SNP, as well as physical maps to make posterior inferences of CNAs. Using real data from cancer cell-lines and patient tumors, we demonstrate substantial improvements in accuracy and computational efficiency compared with existing methods.
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Registered trials
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.