Skip Navigation



Biostatistics Advance Access published online on June 20, 2006
Biostatistics, doi:10.1093/biostatistics/kxl012
This Article
Right arrow FREE Full Text (PDF) Freely available
Right arrow Supplementary Material
Right arrow Supplementary Material
Right arrow All Versions of this Article:
8/2/323    most recent
kxl012v1
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Right arrowRequest Permissions
Right arrow Disclaimer
Google Scholar
Right arrow Articles by Laframboise, T.
Right arrow Articles by Weir, B. A.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Laframboise, T.
Right arrow Articles by Weir, B. A.
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

© The Author 2006. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oxfordjournals.org
Received January 26, 2006
Revised May 11, 2006
Accepted June 16, 2006

Article

PLASQ: A Generalized Linear Model-Based Procedure to Determine Allelic Dosage in Cancer Cells from SNP Array Data

Thomas Laframboise 1 *, David Harrington 2, and Barbara A. Weir 1

1 Department of Medical Oncology, Dana-Farber Cancer Institute, MA, 02115, USA
2 Department of Biostatistics, Harvard School of Public Health, MA, 02115, USA

* To whom correspondence should be addressed.
Thomas Laframboise, E-mail: tlafram{at}broad.mit.edu


  Abstract

Human cancer is largely driven by the acquisition of mutations. One class of such mutations is copy number polymorphisms, comprised of deviations from the normal diploid two copies of each autosomal chromosome per cell. We describe a probe-level allele-specific quantitation (PLASQ) procedure to determine copy number contributions from each of the parental chromosomes in cancer cells from SNP microarray data. Our approach is based upon a generalized linear model that takes advantage of a novel classification of probes on the array. As a result of this classification, we are able to fit the model to the data using an expectation-maximization algorithm designed for the purpose. We demonstrate a strong model fit to data from a variety of cell types. In normal diploid samples, PLASQ is able to genotype with very high accuracy. Moreover, we are able to provide a generalized genotype in cancer samples (e.g. CCCCT at an amplified SNP). Our approach is illustrated on a variety of lung cancer cell lines and tumors, and a number of events are validated by independent computational and experimental means. An R software package containing the methods is freely available.


Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us    What's this?


This article has been cited by other articles:


Home page
 Nucleic Acids ResHome page
W. Sun, F. A. Wright, Z. Tang, S. H. Nordgard, P. V. Loo, T. Yu, V. N. Kristensen, and C. M. Perou
Integrated study of copy number states and genotype calls using high-density SNP arrays
Nucleic Acids Res., September 1, 2009; 37(16): 5365 - 5377.
[Abstract] [Full Text] [PDF]

Home page
 Nucleic Acids ResHome page
L. Wan, K. Sun, Q. Ding, Y. Cui, M. Li, Y. Wen, R. C. Elston, M. Qian, and W. J Fu
Hybridization modeling of oligonucleotide SNP arrays for accurate DNA copy number estimation
Nucleic Acids Res., September 1, 2009; 37(17): e117 - e117.
[Abstract] [Full Text] [PDF]

Home page
 Nucleic Acids ResHome page
T. LaFramboise
Single nucleotide polymorphism arrays: a decade of biological, computational and technological advances
Nucleic Acids Res., July 1, 2009; (2009) gkp552v1.
[Abstract] [Full Text] [PDF]

Home page
 BioinformaticsHome page
T. LaFramboise, W. Winckler, and R. K. Thomas
A flexible rank-based framework for detecting copy number aberrations from array data
Bioinformatics, March 15, 2009; 25(6): 722 - 728.
[Abstract] [Full Text] [PDF]

Home page
 BioinformaticsHome page
E. Giannoulatou, C. Yau, S. Colella, J. Ragoussis, and C. C. Holmes
GenoSNP: a variational Bayes within-sample SNP genotyping algorithm that does not require a reference population
Bioinformatics, October 1, 2008; 24(19): 2209 - 2214.
[Abstract] [Full Text] [PDF]


Disclaimer: Please note that abstracts for content published before 1996 were created through digital scanning and may therefore not exactly replicate the text of the original print issues. All efforts have been made to ensure accuracy, but the Publisher will not be held responsible for any remaining inaccuracies. If you require any further clarification, please contact our Customer Services Department.