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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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Connections between AS, RHS, false negative, type A false positive, and type B false positive values. (A) In a family with a consanguineous marriage, a loop is formed in the pedigree (bold lines). A chromosomal segment that is separately inherited through both sides of the arc becomes homozygous in an offspring and forms an autozygous segment. (B) (i) a chromosomal region with 2 ASs (dark gray boxes). (ii) An RHS is a region whose genetic length greater than the cutoff value. (iii) Relationship of an RHS and an AS. ASs are shown by dark gray boxes, and RHSs are shown by light gray boxes. Three types of errors are defined: false negative, type A false positive, and type B false positive. (C) Principle used for the genotyping error correction. If a homozygous SNP in an RHS is mistyped and becomes heterozygous, it is likely to have a greater distance (i.e. x + y) from the adjacent heterozygous SNPs than a heterozygous SNP that exists in another part of the autosomes. Therefore, heterozygous SNPs with a large x +y are likely to be mistyped.
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Figure 1: Connections between AS, RHS, false negative, type A false positive, and type B false positive values. (A) In a family with a consanguineous marriage, a loop is formed in the pedigree (bold lines). A chromosomal segment that is separately inherited through both sides of the arc becomes homozygous in an offspring and forms an autozygous segment. (B) (i) a chromosomal region with 2 ASs (dark gray boxes). (ii) An RHS is a region whose genetic length greater than the cutoff value. (iii) Relationship of an RHS and an AS. ASs are shown by dark gray boxes, and RHSs are shown by light gray boxes. Three types of errors are defined: false negative, type A false positive, and type B false positive. (C) Principle used for the genotyping error correction. If a homozygous SNP in an RHS is mistyped and becomes heterozygous, it is likely to have a greater distance (i.e. x + y) from the adjacent heterozygous SNPs than a heterozygous SNP that exists in another part of the autosomes. Therefore, heterozygous SNPs with a large x +y are likely to be mistyped.

Mentions: The average number, the average length, and the maximal length of the ASs derived from a common ancestor were calculated for a range of m + n values (Figure 1A) using a Monte Carlo simulation. The trial was repeated until we observed 100,000 events in which at least 1 AS appeared in the autosomal region.


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

- BMC Bioinformatics (2010)

Connections between AS, RHS, false negative, type A false positive, and type B false positive values. (A) In a family with a consanguineous marriage, a loop is formed in the pedigree (bold lines). A chromosomal segment that is separately inherited through both sides of the arc becomes homozygous in an offspring and forms an autozygous segment. (B) (i) a chromosomal region with 2 ASs (dark gray boxes). (ii) An RHS is a region whose genetic length greater than the cutoff value. (iii) Relationship of an RHS and an AS. ASs are shown by dark gray boxes, and RHSs are shown by light gray boxes. Three types of errors are defined: false negative, type A false positive, and type B false positive. (C) Principle used for the genotyping error correction. If a homozygous SNP in an RHS is mistyped and becomes heterozygous, it is likely to have a greater distance (i.e. x + y) from the adjacent heterozygous SNPs than a heterozygous SNP that exists in another part of the autosomes. Therefore, heterozygous SNPs with a large x +y are likely to be mistyped.
© Copyright Policy - open-access
Related In: Results  -  Collection

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

Figure 1: Connections between AS, RHS, false negative, type A false positive, and type B false positive values. (A) In a family with a consanguineous marriage, a loop is formed in the pedigree (bold lines). A chromosomal segment that is separately inherited through both sides of the arc becomes homozygous in an offspring and forms an autozygous segment. (B) (i) a chromosomal region with 2 ASs (dark gray boxes). (ii) An RHS is a region whose genetic length greater than the cutoff value. (iii) Relationship of an RHS and an AS. ASs are shown by dark gray boxes, and RHSs are shown by light gray boxes. Three types of errors are defined: false negative, type A false positive, and type B false positive. (C) Principle used for the genotyping error correction. If a homozygous SNP in an RHS is mistyped and becomes heterozygous, it is likely to have a greater distance (i.e. x + y) from the adjacent heterozygous SNPs than a heterozygous SNP that exists in another part of the autosomes. Therefore, heterozygous SNPs with a large x +y are likely to be mistyped.
Mentions: The average number, the average length, and the maximal length of the ASs derived from a common ancestor were calculated for a range of m + n values (Figure 1A) using a Monte Carlo simulation. The trial was repeated until we observed 100,000 events in which at least 1 AS appeared in the autosomal region.

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