CGHweb: a Tool for Comparing DNA Copy Number Segmentations from Multiple Algorithms

Overview

Journal Bioinformatics

Publisher Oxford University Press

Specialty Biology

Date 2008 Feb 26

PMID 18296463

Citations 27

Authors

Weil Lai

Vidhu Choudhary

Peter J Park

Affiliations

Soon will be listed here.

Abstract

Unlabelled: Accurate estimation of DNA copy numbers from array comparative genomic hybridization (CGH) data is important for characterizing the cancer genome. An important part of this process is the segmentation of the log-ratios between the sample and control DNA along the chromosome into regions of different copy numbers. However, multiple algorithms are available in the literature for this procedure and the results can vary substantially among these. Thus, a visualization tool that can display the segmented profiles from a number of methods can be helpful to the biologist or the clinician to ascertain that a feature of interest did not arise as an artifact of the algorithm. Such a tool also allows the methodologist to easily contrast his method against others. We developed a web-based tool that applies a number of popular algorithms to a single array CGH profile entered by the user. It generates a heatmap panel of the segmented profiles for each method as well as a consensus profile. The clickable heatmap can be moved along the chromosome and zoomed in or out. It also displays the time that each algorithm took and provides numerical values of the segmented profiles for download. The web interface calls algorithms written in the statistical language R. We encourage developers of new algorithms to submit their routines to be incorporated into the website.

Availability: http://compbio.med.harvard.edu/CGHweb.

Citing Articles

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Bhanuprakash V, Chhotaray S, Pruthviraj D, Rawat C, Karthikeyan A, Panigrahi M Vet World. 2018; 11(4):535-541.

PMID: 29805222 PMC: 5960796. DOI: 10.14202/vetworld.2018.535-541.

Repeat associated mechanisms of genome evolution and function revealed by the and genomes.

Thybert D, Roller M, Navarro F, Fiddes I, Streeter I, Feig C Genome Res. 2018; 28(4):448-459.

PMID: 29563166 PMC: 5880236. DOI: 10.1101/gr.234096.117.

Evidence for feasibility of fetal trophoblastic cell-based noninvasive prenatal testing.

Breman A, Chow J, URen L, Normand E, Qdaisat S, Zhao L Prenat Diagn. 2016; 36(11):1009-1019.

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Inferring expressed genes by whole-genome sequencing of plasma DNA.

Ulz P, Thallinger G, Auer M, Graf R, Kashofer K, Jahn S Nat Genet. 2016; 48(10):1273-8.

PMID: 27571261 DOI: 10.1038/ng.3648.

Whole-genome plasma sequencing reveals focal amplifications as a driving force in metastatic prostate cancer.

Ulz P, Belic J, Graf R, Auer M, Lafer I, Fischereder K Nat Commun. 2016; 7:12008.

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