ArticleProceedings of the National Academy of Sciences of the United States of America2004
A versatile statistical analysis algorithm to detect genome copy number variation.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2004. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
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Who cites it
27 citing papers in PubMed.
- Chromothripsis-like chromosomal rearrangements induced by ionizing radiation using proton microbeam irradiation system.Oncotarget · 2016Article
- Copy number variation signature to predict human ancestry.BMC bioinformatics · 2012Article
- Parsimonious higher-order hidden Markov models for improved array-CGH analysis with applications to Arabidopsis thaliana.PLoS computational biology · 2012Article
- Efficient algorithms for tandem copy number variation reconstruction in repeat-rich regions.Bioinformatics (Oxford, England) · 2011Article
- Estimation of parent specific DNA copy number in tumors using high-density genotyping arrays.PLoS computational biology · 2011Article
- Bayesian Frequentist hybrid Model wth Application to the Analysis of Gene Copy Number Changes.Journal of applied statistics · 2011Article
- Model-integrated estimation of normal tissue contamination for cancer SNP allelic copy number data.Cancer informatics · 2011Article
- Detection and reconstruction of tandemly organized de novo copy number variations.BMC bioinformatics · 2010Article
- Detecting simultaneous changepoints in multiple sequences.Biometrika · 2010Article
- A bayesian analysis for identifying DNA copy number variations using a compound poisson process.EURASIP journal on bioinformatics & systems biology · 2010Article
- On the frequency of copy number variants.Bioinformatics (Oxford, England) · 2008Article
- Gene copy number analysis for family data using semiparametric copula model.Bioinformatics and biology insights · 2008Article
- Array CGH data modeling and smoothing in Stationary Wavelet Packet Transform domain.BMC genomics · 2008Article
- Copy number variant analysis of human embryonic stem cells.Stem cells (Dayton, Ohio) · 2008Article
- An improved method for detecting and delineating genomic regions with altered gene expression in cancer.Genome biology · 2008Article
- Getting started in tiling microarray analysis.PLoS computational biology · 2007Review
- Overlay tool for aCGHViewer: an analysis module built for aCGHViewer used to perform comparisons of data derived from different microarray platforms.Cancer informatics · 2007Article
- Flexible and accurate detection of genomic copy-number changes from aCGH.PLoS computational biology · 2007Article
- A forward-backward fragment assembling algorithm for the identification of genomic amplification and deletion breakpoints using high-density single nucleotide polymorphism (SNP) array.BMC bioinformatics · 2007Article
- Exploiting noise in array CGH data to improve detection of DNA copy number change.Nucleic acids research · 2007Article
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6 authors.
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No grant is acknowledged in the PubMed record.
Abstract
We have developed a versatile statistical analysis algorithm for the detection of genomic aberrations in human cancer cell lines. The algorithm analyzes genomic data obtained from a variety of array technologies, such as oligonucleotide array, bacterial artificial chromosome array, or array-based comparative genomic hybridization, that operate by hybridizing with genomic material obtained from cancer and normal cells and allow detection of regions of the genome with altered copy number. The number of probes (i.e., resolution), the amount of uncharacterized noise per probe, and the severity of chromosomal aberrations per chromosomal region may vary with the underlying technology, biological sample, and sample preparation. Constrained by these uncertainties, our algorithm aims at robustness by using a priorless maximum a posteriori estimator and at efficiency by a dynamic programming implementation. We illustrate these characteristics of our algorithm by applying it to data obtained from representational oligonucleotide microarray analysis and array-based comparative genomic hybridization technology as well as to synthetic data obtained from an artificial model whose properties can be varied computationally. The algorithm can combine data from multiple sources and thus facilitate the discovery of genes and markers important in cancer, as well as the discovery of loci important in inherited genetic disease.
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