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A quantitatively-modeled homozygosity mapping algorithm, qHomozygosityMapping, utilizing whole genome single nucleotide polymorphism genotyping data.

- BMC Bioinformatics (2010)

Bottom Line: 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.Our procedure will accelerate the identification of disease-causing genes using high-density SNP array data.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Respiratory Medicine, Saitama Medical University, 38 Morohongo, Moroyama, Saitama 350-0495, Japan.

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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RHSs obtained for 5 patients with Siiyama-type α1-antitrypsin deficiency and the distribution of the longest AS obtained by a Monte Carlo simulation. (A) - (E) RHSs for each patient. (F) The distribution of the length of the longest AS obtained by a Monte Carlo Simulation. The distribution for 86 HapMap JPT patients is also shown in the right side.
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Figure 4: RHSs obtained for 5 patients with Siiyama-type α1-antitrypsin deficiency and the distribution of the longest AS obtained by a Monte Carlo simulation. (A) - (E) RHSs for each patient. (F) The distribution of the length of the longest AS obtained by a Monte Carlo Simulation. The distribution for 86 HapMap JPT patients is also shown in the right side.

Mentions: We applied the genotyping error correction algorithm to the data for 5 patients with Siiyama-type α1-antitrypsin deficiency [Step (b)], and then obtained RHSs [Step (c)] (Figure 4A-E). All patients had long RHSs, which were likely to be the result of first-cousin marriages.


A quantitatively-modeled homozygosity mapping algorithm, qHomozygosityMapping, utilizing whole genome single nucleotide polymorphism genotyping data.

- BMC Bioinformatics (2010)

RHSs obtained for 5 patients with Siiyama-type α1-antitrypsin deficiency and the distribution of the longest AS obtained by a Monte Carlo simulation. (A) - (E) RHSs for each patient. (F) The distribution of the length of the longest AS obtained by a Monte Carlo Simulation. The distribution for 86 HapMap JPT patients is also shown in the right side.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2957688&req=5

Figure 4: RHSs obtained for 5 patients with Siiyama-type α1-antitrypsin deficiency and the distribution of the longest AS obtained by a Monte Carlo simulation. (A) - (E) RHSs for each patient. (F) The distribution of the length of the longest AS obtained by a Monte Carlo Simulation. The distribution for 86 HapMap JPT patients is also shown in the right side.
Mentions: We applied the genotyping error correction algorithm to the data for 5 patients with Siiyama-type α1-antitrypsin deficiency [Step (b)], and then obtained RHSs [Step (c)] (Figure 4A-E). All patients had long RHSs, which were likely to be the result of first-cousin marriages.

Bottom Line: 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.Our procedure will accelerate the identification of disease-causing genes using high-density SNP array data.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Respiratory Medicine, Saitama Medical University, 38 Morohongo, Moroyama, Saitama 350-0495, Japan.

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.

Show MeSH