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  The allele distribution in next-generation sequencing data sets is accurately described as the result of a stochastic branching process

Heinrich, V., Stange, J., Dickhaus, T., Imkeller, P., Kruger, U., Bauer, S., et al. (2012). The allele distribution in next-generation sequencing data sets is accurately described as the result of a stochastic branching process. Nucleic Acids Research (London), 40(6), 2426-2431. doi:10.1093/nar/gkr1073.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-000E-F26A-D Version Permalink: http://hdl.handle.net/11858/00-001M-0000-000E-F26B-B
Genre: Journal Article

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 Creators:
Heinrich, V., Author
Stange, J., Author
Dickhaus, T., Author
Imkeller, P., Author
Kruger, U., Author
Bauer, S., Author
Mundlos, S.1, 2, Author              
Robinson, P. N.1, 2, Author              
Hecht, J.1, 3, Author              
Krawitz, P. M., Author
Affiliations:
1Research Group Development & Disease (Head: Stefan Mundlos), Max Planck Institute for Molecular Genetics, Max Planck Society, Berlin, Germany, ou_1433557              
2Institute for Medical and Human Genetics, Charité Universitätsmedizin Berlin, Berlin, Germany, ou_persistent22              
3Berlin-Brandenburg Center for Regenerative Therapies (BCRT), Charité Universitätsmedizin Berlin, Berlin, Germany, ou_persistent22              

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Free keywords: Alleles Exome Gene Frequency Heterozygote High-Throughput Nucleotide Sequencing Humans Sequence Analysis, DNA Stochastic Processes
 Abstract: With the availability of next-generation sequencing (NGS) technology, it is expected that sequence variants may be called on a genomic scale. Here, we demonstrate that a deeper understanding of the distribution of the variant call frequencies at heterozygous loci in NGS data sets is a prerequisite for sensitive variant detection. We model the crucial steps in an NGS protocol as a stochastic branching process and derive a mathematical framework for the expected distribution of alleles at heterozygous loci before measurement that is sequencing. We confirm our theoretical results by analyzing technical replicates of human exome data and demonstrate that the variance of allele frequencies at heterozygous loci is higher than expected by a simple binomial distribution. Due to this high variance, mutation callers relying on binomial distributed priors are less sensitive for heterozygous variants that deviate strongly from the expected mean frequency. Our results also indicate that error rates can be reduced to a greater degree by technical replicates than by increasing sequencing depth.

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Language(s): eng - English
 Dates: 2012-03
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Method: Peer
 Identifiers: DOI: 10.1093/nar/gkr1073
 Degree: -

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Title: Nucleic Acids Research (London)
  Other : Nucleic Acids Res
Source Genre: Journal
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Publ. Info: Oxford : Oxford University Press
Pages: - Volume / Issue: 40 (6) Sequence Number: - Start / End Page: 2426 - 2431 Identifier: ISSN: 0305-1048
CoNE: https://pure.mpg.de/cone/journals/resource/110992357379342