Display options
Cite
Pope BJ, Nguyen-Dumont T, Hammet F, et al. ROVER variant caller: read-pair overlap considerate variant-calling software applied to PCR-based massively parallel sequencing datasets. Source Code Biol Med. 2014;9(1):3doi: 10.1186/1751-0473-9-3.
Pope, B. J., Nguyen-Dumont, T., Hammet, F., & Park, D. J. (2014). ROVER variant caller: read-pair overlap considerate variant-calling software applied to PCR-based massively parallel sequencing datasets. Source code for biology and medicine, 9(1), 3. https://doi.org/10.1186/1751-0473-9-3
Pope, Bernard J, et al. "ROVER variant caller: read-pair overlap considerate variant-calling software applied to PCR-based massively parallel sequencing datasets." Source code for biology and medicine vol. 9,1 (2014): 3. doi: https://doi.org/10.1186/1751-0473-9-3
Pope BJ, Nguyen-Dumont T, Hammet F, Park DJ. ROVER variant caller: read-pair overlap considerate variant-calling software applied to PCR-based massively parallel sequencing datasets. Source Code Biol Med. 2014 Jan 24;9(1):3. doi: 10.1186/1751-0473-9-3. PMID: 24461215; PMCID: PMC3904415.
Copy Download .nbib Format: NLM
Share it on

Source Code Biol Med. 2014 Jan 24;9(1):3. doi: 10.1186/1751-0473-9-3.

ROVER variant caller: read-pair overlap considerate variant-calling software applied to PCR-based massively parallel sequencing datasets.

Source code for biology and medicine

Bernard J Pope, Tú Nguyen-Dumont, Fleur Hammet, Daniel J Park

Affiliations

  1. Genetic Epidemiology Laboratory, Department of Pathology, Medical Building, The University of Melbourne, Melbourne, Victoria 3010, Australia. [email protected].

PMID: 24461215 PMCID: PMC3904415 DOI: 10.1186/1751-0473-9-3

Abstract

BACKGROUND: We recently described Hi-Plex, a highly multiplexed PCR-based target-enrichment system for massively parallel sequencing (MPS), which allows the uniform definition of library size so that subsequent paired-end sequencing can achieve complete overlap of read pairs. Variant calling from Hi-Plex-derived datasets can thus rely on the identification of variants appearing in both reads of read-pairs, permitting stringent filtering of sequencing chemistry-induced errors. These principles underly ROVER software (derived from Read Overlap PCR-MPS variant caller), which we have recently used to report the screening for genetic mutations in the breast cancer predisposition gene PALB2. Here, we describe the algorithms underlying ROVER and its usage.

RESULTS: ROVER enables users to quickly and accurately identify genetic variants from PCR-targeted, overlapping paired-end MPS datasets. The open-source availability of the software and threshold tailorability enables broad access for a range of PCR-MPS users.

METHODS: ROVER is implemented in Python and runs on all popular POSIX-like operating systems (Linux, OS X). The software accepts a tab-delimited text file listing the coordinates of the target-specific primers used for targeted enrichment based on a specified genome-build. It also accepts aligned sequence files resulting from mapping to the same genome-build. ROVER identifies the amplicon a given read-pair represents and removes the primer sequences by using the mapping co-ordinates and primer co-ordinates. It considers overlapping read-pairs with respect to primer-intervening sequence. Only when a variant is observed in both reads of a read-pair does the signal contribute to a tally of read-pairs containing or not containing the variant. A user-defined threshold informs the minimum number of, and proportion of, read-pairs a variant must be observed in for a 'call' to be made. ROVER also reports the depth of coverage across amplicons to facilitate the identification of any regions that may require further screening.

CONCLUSIONS: ROVER can facilitate rapid and accurate genetic variant calling for a broad range of PCR-MPS users.

References

  1. Hugo J. 2011 Dec;5(1-4):1-12 - PubMed
  2. Trends Genet. 2008 Mar;24(3):133-41 - PubMed
  3. BMC Med Genomics. 2013 Nov 08;6:48 - PubMed
  4. Nucleic Acids Res. 2010 Sep;38(16):e164 - PubMed
  5. Bioinformatics. 2009 Aug 15;25(16):2078-9 - PubMed
  6. Bioinformatics. 2010 Mar 15;26(6):841-2 - PubMed
  7. Biotechniques. 2013 Aug;55(2):69-74 - PubMed
  8. Clin Biochem Rev. 2011 Nov;32(4):177-95 - PubMed
  9. Anal Biochem. 2013 Nov 15;442(2):127-9 - PubMed
  10. Hum Mutat. 2010 Apr;31(4):484-91 - PubMed
  11. BMC Bioinformatics. 2013 Feb 25;14:65 - PubMed

Publication Types