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Comparative linkage analysis and visualization of high-density oligonucleotide SNP array data

Igor Leykin12, Ke Hao1, Junsheng Cheng3, Nicole Meyer4, Martin R Pollak5, Richard JH Smith4, Wing Hung Wong6, Carsten Rosenow7* and Cheng Li12*

Author affiliations

1 Department of Biostatistics, Harvard School of Public Health, Boston, MA 02115, USA

2 Department of Biostatistical Science, Dana-Farber Cancer Institute, 44 Binney Street, Boston, MA 02115, USA

3 Department of Computer Science, University of Illinois at Chicago, Chicago, IL 60607, USA

4 Molecular Otolaryngology Research Labs, University of Iowa, Iowa City, IA 52242, USA

5 Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA

6 Department of Statistics, Stanford University, Stanford, CA, 94305, USA

7 Affymetrix Inc., 3380 Central Expressway, Santa Clara, CA 95051, USA

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Citation and License

BMC Genetics 2005, 6:7  doi:10.1186/1471-2156-6-7

Published: 15 February 2005

Abstract

Background

The identification of disease-associated genes using single nucleotide polymorphisms (SNPs) has been increasingly reported. In particular, the Affymetrix Mapping 10 K SNP microarray platform uses one PCR primer to amplify the DNA samples and determine the genotype of more than 10,000 SNPs in the human genome. This provides the opportunity for large scale, rapid and cost-effective genotyping assays for linkage analysis. However, the analysis of such datasets is nontrivial because of the large number of markers, and visualizing the linkage scores in the context of genome maps remains less automated using the current linkage analysis software packages. For example, the haplotyping results are commonly represented in the text format.

Results

Here we report the development of a novel software tool called CompareLinkage for automated formatting of the Affymetrix Mapping 10 K genotype data into the "Linkage" format and the subsequent analysis with multi-point linkage software programs such as Merlin and Allegro. The new software has the ability to visualize the results for all these programs in dChip in the context of genome annotations and cytoband information. In addition we implemented a variant of the Lander-Green algorithm in the dChipLinkage module of dChip software (V1.3) to perform parametric linkage analysis and haplotyping of SNP array data. These functions are integrated with the existing modules of dChip to visualize SNP genotype data together with LOD score curves. We have analyzed three families with recessive and dominant diseases using the new software programs and the comparison results are presented and discussed.

Conclusions

The CompareLinkage and dChipLinkage software packages are freely available. They provide the visualization tools for high-density oligonucleotide SNP array data, as well as the automated functions for formatting SNP array data for the linkage analysis programs Merlin and Allegro and calling these programs for linkage analysis. The results can be visualized in dChip in the context of genes and cytobands. In addition, a variant of the Lander-Green algorithm is provided that allows parametric linkage analysis and haplotyping.