Dindel: Accurate indel calls from short-read data
- Cornelis A. Albers1,2,5,
- Gerton Lunter3,
- Daniel G. MacArthur1,
- Gilean McVean4,
- Willem H. Ouwehand1,2 and
- Richard Durbin1
- 1Wellcome Trust Sanger Institute, Hinxton, Cambridgeshire CB10 1HH, United Kingdom;
- 2Department of Haematology, University of Cambridge and National Health Service Blood and Transplant, Cambridge CB2 1TN, United Kingdom;
- 3Wellcome Trust Centre for Human Genetics, Oxford OX3 7BN, United Kingdom;
- 4Department of Statistics, University of Oxford, Oxford OX1 3TG, United Kingdom
Abstract
Small insertions and deletions (indels) are a common and functionally important type of sequence polymorphism. Most of the focus of studies of sequence variation is on single nucleotide variants (SNVs) and large structural variants. In principle, high-throughput sequencing studies should allow identification of indels just as SNVs. However, inference of indels from next-generation sequence data is challenging, and so far methods for identifying indels lag behind methods for calling SNVs in terms of sensitivity and specificity. We propose a Bayesian method to call indels from short-read sequence data in individuals and populations by realigning reads to candidate haplotypes that represent alternative sequence to the reference. The candidate haplotypes are formed by combining candidate indels and SNVs identified by the read mapper, while allowing for known sequence variants or candidates from other methods to be included. In our probabilistic realignment model we account for base-calling errors, mapping errors, and also, importantly, for increased sequencing error indel rates in long homopolymer runs. We show that our method is sensitive and achieves low false discovery rates on simulated and real data sets, although challenges remain. The algorithm is implemented in the program Dindel, which has been used in the 1000 Genomes Project call sets.
Footnotes
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↵5 Corresponding author.
E-mail caa{at}sanger.ac.uk; fax 44-1223-49-6802.
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[Supplemental material is available for this article. The sequence data from this study have been submitted to the European Nucleotide Archive (http://www.ebi.ac.uk/ena/) under accession no. ERA014258. The program Dindel can be freely downloaded from http://www.sanger.ac.uk/resources/software/dindel/.]
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Article published online before print. Article and publication date are at http://www.genome.org/cgi/doi/10.1101/gr.112326.110.
- Received July 1, 2010.
- Accepted October 6, 2010.
- Copyright © 2011 by Cold Spring Harbor Laboratory Press
Freely available online through the Genome Research Open Access option.
