ArticleBMC bioinformatics2010
A quantitatively-modeled homozygosity mapping algorithm, qHomozygosityMapping, utilizing whole genome single nucleotide polymorphism genotyping data.
Article in BMC bioinformatics, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- A novel rearrangement of occludin causes brain calcification and renal dysfunction.Human genetics · 2013Article
- A clinical evaluation tool for SNP arrays, especially for autosomal recessive conditions in offspring of consanguineous parents.Genetics in medicine : official journal of the American College of Medical Genetics · 2013Article
- Article
- InCoB2010 - 9th International Conference on Bioinformatics at Tokyo, Japan, September 26-28, 2010.BMC bioinformatics · 2010Article
- Pitfall of identifying a disease locus by using low-resolution SNP arrays.Journal of molecular and genetic medicine : an international journal of biomedical research · 2010Article
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Authors and funding
11 authors.
Funding
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Abstract
Homozygosity mapping is a powerful procedure that is capable of detecting recessive disease-causing genes in a few patients from families with a history of inbreeding. We report here a homozygosity mapping algorithm for high-density single nucleotide polymorphism arrays that is able to (i) correct genotyping errors, (ii) search for autozygous segments genome-wide through regions with runs of homozygous SNPs, (iii) check the validity of the inbreeding history, and (iv) calculate the probability of the disease-causing gene being located in the regions identified. The genotyping error correction restored an average of 94.2% of the total length of all regions with run of homozygous SNPs, and 99.9% of the total length of them that were longer than 2 cM. At the end of the analysis, we would know the probability that regions identified contain a disease-causing gene, and we would be able to determine how much effort should be devoted to scrutinizing the regions. We confirmed the power of this algorithm using 6 patients with Siiyama-type α1-antitrypsin deficiency, a rare autosomal recessive disease in Japan. Our procedure will accelerate the identification of disease-causing genes using high-density SNP array data.
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