Identification of indels in next-generation sequencing data

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• 作者：Aakrosh Ratan (1) (3)
  Thomas L Olson (2)
  Thomas P Loughran Jr (2)
  Webb Miller (1)
  
  1. Center for Comparative Genomics and Bioinformatics ; Pennsylvania State University ; 506 ; Wartik Laboratory ; University Park ; PA ; 16802 ; USA
  3. Department of Public Health Sciences and Center for Public Health Genomics ; University of Virginia ; Charlottesville ; VA ; 22908 ; USA
  2. Department of Medicine ; Hematology and Oncology ; and the University of Virginia Cancer Center ; University of Virginia ; Charlottesville ; VA ; 22908 ; USA
  
• 关键词：Indels ; Variants ; Sequencing analysis
• 刊名：BMC Bioinformatics
• 出版年：2015
• 出版时间：December 2015
• 年：2015
• 卷：16
• 期：1
• 全文大小：879 KB
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• 刊物主题：Bioinformatics; Microarrays; Computational Biology/Bioinformatics; Computer Appl. in Life Sciences; Combinatorial Libraries; Algorithms;
• 出版者：BioMed Central
• ISSN：1471-2105

文摘

Background The discovery and mapping of genomic variants is an essential step in most analysis done using sequencing reads. There are a number of mature software packages and associated pipelines that can identify single nucleotide polymorphisms (SNPs) with a high degree of concordance. However, the same cannot be said for tools that are used to identify the other types of variants. Indels represent the second most frequent class of variants in the human genome, after single nucleotide polymorphisms. The reliable detection of indels is still a challenging problem, especially for variants that are longer than a few bases. Results We have developed a set of algorithms and heuristics collectively called indelMINER to identify indels from whole genome resequencing datasets using paired-end reads. indelMINER uses a split-read approach to identify the precise breakpoints for indels of size less than a user specified threshold, and supplements that with a paired-end approach to identify larger variants that are frequently missed with the split-read approach. We use simulated and real datasets to show that an implementation of the algorithm performs favorably when compared to several existing tools. Conclusions indelMINER can be used effectively to identify indels in whole-genome resequencing projects. The output is provided in the VCF format along with additional information about the variant, including information about its presence or absence in another sample. The source code and documentation for indelMINER can be freely downloaded from www.bx.psu.edu/miller_lab/indelMINER.tar.gz.