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Autozygosity mapping with exome sequence data.
- Source :
-
Human mutation [Hum Mutat] 2013 Jan; Vol. 34 (1), pp. 50-6. Date of Electronic Publication: 2012 Oct 22. - Publication Year :
- 2013
-
Abstract
- Autozygosity mapping is a powerful method for the identification of recessively inherited disease genes using small inbred families. Typically, microarray SNP genotype data are first used to identify autozygous regions as extended runs of homozygous genotypes. Next, candidate disease loci are found by defining regions that are autozygous in all affected patients. Finally, the disease gene is identified by sequencing the genes within the candidate disease loci. However, with the advent of massively parallel sequencing, it is now possible to sample or to completely sequence an individual's genome, or, more commonly, exome. This opens up the possibility of concurrently defining autozygous regions and identifying possibly deleterious sequence variants, using data from a single sequencing experiment. Consequently, we have developed a set of computer programs that identify autozygous regions using exome sequence data. These programs derive their genotyping data either by the ab initio detection of all sequence variants or by the assessment of 0.53 million known polymorphic positions within each exome dataset. Using genotype data derived solely from exome sequence data, it was possible to identify the majority of autozygous regions found by microarray SNP genotype data.<br /> (© 2012 Wiley Periodicals, Inc.)
- Subjects :
- Chromosome Mapping methods
Consanguinity
Genetic Predisposition to Disease genetics
Genotype
Genotyping Techniques methods
Humans
Pedigree
Polymorphism, Single Nucleotide
Reproducibility of Results
Software
Computational Biology methods
Exome genetics
Genes, Recessive genetics
Genome, Human genetics
Sequence Analysis, DNA methods
Subjects
Details
- Language :
- English
- ISSN :
- 1098-1004
- Volume :
- 34
- Issue :
- 1
- Database :
- MEDLINE
- Journal :
- Human mutation
- Publication Type :
- Academic Journal
- Accession number :
- 23090942
- Full Text :
- https://doi.org/10.1002/humu.22220