Abstract
Copy number variations (CNVs) are abundant in the human genome. They have been associated with complex traits in genome-wide association studies (GWAS) and expected to continue playing an important role in identifying the etiology of disease phenotypes. As a result of current high throughput whole-genome single-nucleotide polymorphism (SNP) arrays, we currently have datasets that simultaneously have integer copy numbers in CNV regions as well as SNP genotypes. At the same time, haplotypes that have been shown to offer advantages over genotypes in identifying disease traits even though available for SNP genotypes are largely not available for CNV/SNP data due to insufficient computational tools. We introduce a new framework for inferring haplotypes in CNV/SNP data using a sequential Monte Carlo sampling scheme ‘Tree-Based Deterministic Sampling CNV’ (TDSCNV). We compare our method with polyHap(v2.0), the only currently available software able to perform inference in CNV/SNP genotypes, on datasets of varying number of markers. We have found that both algorithms show similar accuracy but TDSCNV is an order of magnitude faster while scaling linearly with the number of markers and number of individuals and thus could be the method of choice for haplotype inference in such datasets. Our method is implemented in the TDSCNV package which is available for download at http://www.ee.columbia.edu/~anastas/tdscnv.
Highlights
Copy number variations (CNVs) are a form of a structural genomic variation referring to duplications and deletions of DNA segments larger than 1 kilobase in size
CNVs are abundant in the human genome, and it is estimated that they can occupy as much as 4% to 6%
CNVs have been associated with complex traits unexplained by recent genome wide association studies (GWAS) [2] and are believed to make a substantial contribution in uncovering the mechanisms and etiology of disease phenotypes that result from complex patterns of inheritance [2,4]
Summary
Copy number variations (CNVs) are a form of a structural genomic variation referring to duplications and deletions of DNA segments larger than 1 kilobase in size. Large-scale genome-wide studies have shed light in many aspects and characteristics of CNVs providing unique insights into the origins, mechanisms, formation, and population genetics of CNVs [1,2,3]. CNVs have been associated with complex traits unexplained by recent genome wide association studies (GWAS) [2] and are believed to make a substantial contribution in uncovering the mechanisms and etiology of disease phenotypes that result from complex patterns of inheritance [2,4]. There is currently simultaneously information on the integer copy number (CN) genotypes along a CNV region and on SNPs outside these regions, in which we will refer in the following as CNV-SNP genotypes
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: EURASIP Journal on Bioinformatics and Systems Biology
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
