Literature DB >> 19819885

Inferring relative proportions of DNA variants from sequencing electropherograms.

I M Carr1, J I Robinson, R Dimitriou, A F Markham, A W Morgan, D T Bonthron.   

Abstract

MOTIVATION: Determination of the relative copy number of single-nucleotide sequence variants (SNVs) within a DNA sample is a frequent experimental goal. Various methods can be applied to this problem, although hybridization-based approaches tend to suffer from high-setup cost and poor adaptability, while others (such as pyrosequencing) may not be accessible to all laboratories. The potential to extract relative copy number information from standard dye-terminator electropherograms has been little explored, yet this technology is cheap and widely accessible. Since several biologically important loci have paralogous copies that interfere with genotyping, and which may also display copy number variation (CNV), there are many situations in which determination of the relative copy number of SNVs is desirable.
RESULTS: We have developed a desktop application, QSVanalyzer, which allows high-throughput quantification of the proportions of DNA sequences containing SNVs. In reconstruction experiments, QSVanalyzer accurately estimated the known relative proportions of SNVs. By analyzing a large panel of genomic DNA samples, we demonstrate the ability of the software to analyze not only common biallelic SNVs, but also SNVs within a locus at which gene conversion between four genomic paralogs operates, and within another that is subject to CNV.
AVAILABILITY AND IMPLEMENTATION: QSVanalyzer is freely available at http://dna.leeds.ac.uk/qsv/. It requires the Microsoft .NET framework version 2.0, which can be installed on all Microsoft operating systems from Windows 98 onwards. CONTACT: msjimc@leeds.ac.uk SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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Substances:

Year:  2009        PMID: 19819885     DOI: 10.1093/bioinformatics/btp583

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


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