Bioinformatics Advance Access originally published online on February 10, 2004
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Bioinformatics 20(8) © Oxford University Press 2004; all rights reserved.
dChipSNP: significance curve and clustering of SNP-array-based loss-of-heterozygosity data
1 Department of Biostatistics, Harvard School of Public Health, 2 Department of Biostatistical Sciences and 3 Department of Medical Oncology, Dana-Farber Cancer Institute, 4 Department of Medicine, Harvard Medical School, 5 Department of Radiation Oncology, Brigham and Women's Hospital, Boston, MA 02115, USA and 6 Department of Statistics, Harvard University, Cambridge, MA, USA
Received on July 29, 2003; revised on October 6, 2003; accepted on November 18, 2003
Advance Access Publication February 10, 2004
Motivation: Oligonucleotide microarrays allow genotyping of thousands of single-nucleotide polymorphisms (SNPs) in parallel. Recently, this technology has been applied to loss-of-heterozygosity (LOH) analysis of paired normal and tumor samples. However, methods and software for analyzing such data are not fully developed.
Result: Here, we report automated methods for pooling SNP array replicates to make LOH calls, visualizing SNP and LOH data along chromosomes in the context of genes and cytobands, making statistical inference to identify shared LOH regions, clustering samples based on LOH profiles and correlating the clustering results to clinical variables. Application of these methods to prostate and breast cancer datasets generates biologically important results.
Availability: The software module dChipSNP implementing these methods is available at http://biosun1.harvard.edu/complab/dchip/snp/
Supplementary information: The breast cancer data are provided by Andrea L. Richardson, Zhigang C. Wang and James D. Iglehart.
Contact: cli{at}hsph.harvard.edu
* To whom correspondence should be addressed.
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