Skip to main content
SpringerLink
Log in

Variant Calling From Next Generation Sequence Data

  • Protocol
  • First Online:
Statistical Genomics

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1418))

Abstract

The use of next generation nucleotide sequencing to discover and genotype small sequence variants has led to numerous insights into the molecular causes of various diseases. This chapter describes the use of freely available software to align next generation sequencing reads to a reference and then to use the resulting alignments to call, annotate, view, and filter small sequence variants. The suggested variant calling workflow includes read alignment with novoalign, the removal of polymerase chain reaction duplicate sequences with samtools or bamUtils, and the detection of variants with Freebayes or bam2mpg software. ANNOVAR is then used to annotate the predicted variants using gene models, population frequencies, and predicted mutation severity, producing variant files which can be viewed and filtered with the variant display tool VarSifter.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Protocol
USD 49.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 89.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 119.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 129.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. International Human Genome Sequencing Consortium (2001) Initial sequencing and analysis of the human genome. Nature 409(6822):860. http://dx.doi.org/10.1038/35057062

  2. Bentley DR, Balasubramanian S, Swerdlow HP, Smith GP, Milton J, Brown CG, Hall KP, Evers DJ, Barnes CL, Bignell HR, Boutell JM, Bryant J, Carter RJ, Keira Cheetham R, Cox AJ, Ellis DJ, Flatbush MR, Gormley NA, Humphray SJ, Irving LJ, Karbelashvili MS, Kirk SM, Li H, Liu X, Maisinger KS, Murray LJ, Obradovic B, Ost T, Parkinson ML, Pratt MR, Rasolonjatovo IMJ, Reed MT, Rigatti R, Rodighiero C, Ross MT, Sabot A, Sankar SV, Scally A, Schroth GP, Smith ME, Smith VP, Spiridou A, Torrance PE, Tzonev SS, Vermaas EH, Walter K, Wu X, Zhang L, Alam MD, Anastasi C, Aniebo IC, Bailey DMD, Bancarz IR, Banerjee S, Barbour SG, Baybayan PA, Benoit VA, Benson KF, Bevis C, Black PJ, Boodhun A, Brennan JS, Bridgham JA, Brown RC, Brown AA, Buermann DH, Bundu AA, Burrows JC, Carter NP, Castillo N, Chiara M, Catenazzi E, Chang S, Neil Cooley R, Crake NR, Dada OO, Diakoumakos KD, Dominguez-Fernandez B, Earnshaw DJ, Egbujor UC, Elmore DW, Etchin SS, Ewan MR, Fedurco M, Fraser LJ, Fuentes Fajardo KV, Scott Furey W, George D, Gietzen KJ, Goddard CP, Golda GS, Granieri PA, Green DE, Gustafson DL, Hansen NF, Harnish K, Haudenschild CD, Heyer NI, Hims MM, Ho JT, Horgan AM, Hoschler K, Hurwitz S, Ivanov DV, Johnson MQ, JamesT, Huw Jones TA, Kang GD, Kerelska TH, Kersey AD, Khrebtukova I, Kindwall AP, Kingsbury Z, Kokko-Gonzales PI, Kumar A, Laurent MA, Lawley CT, Lee SE, Lee X, Liao AK, Loch JA, Lok M, Luo S, Mammen RM, Martin JW, McCauley PG, McNitt P, Mehta P, Moon KW, Mullens JW, Newington T, Ning Z, Ling Ng B, Novo SM, O’Neill MJ, Osborne MA, Osnowski A, Ostadan O, Paraschos LL, Pickering L, Pike AC, Pike AC, Chris Pinkard D, Pliskin DP, Podhasky J, Quijano VJ, Raczy C, Rae VH, Rawlings SR, Chiva Rodriguez A, Roe PM, Rogers J, Rogert Bacigalupo MC, Romanov N, Romieu A, Roth RK, Rourke NJ, Ruediger ST, Rusman E, Sanches-Kuiper RM, Schenker MR, Seoane JM, Shaw RJ, Shiver MK, Short SW, Sizto NL, Sluis JP, Smith MA, Ernest Sohna Sohna J, Spence EJ, Stevens K, Sutton N, Szajkowski L, Tregidgo CL, Turcatti G, Vandevondele S, Verhovsky Y, Virk SM, Wakelin S, Walcott GC, Wang J, Worsley GJ, Yan J, Yau L, Zuerlein M, Rogers J, Mullikin JC, Hurles ME, McCooke NJ, West JS, Oaks FL, Lundberg PL, Klenerman D, Durbin R, Smith AJ (2008) Accurate whole human genome sequencing using reversible terminator chemistry. Nature 456(7218):53. doi:10. 1038/nature07517

    Google Scholar 

  3. The 1000 Genomes Project Consortium (2012) An integrated map of genetic variation from 1,092 human genomes. Nature 491(7422):56. http://dx.doi.org/10.1038/nature11632

  4. Hoadley KA, Yau C, Wolf DM, Cherniack AD, Tamborero D, Ng S, Leiserson MD, Niu B, McLellan MD, Uzunangelov V, Zhang J, Kandoth C, Akbani R, Shen H, Omberg L, Chu A, Margolin AA, van’t Veer LJ, N. Lopez-Bigas, Laird PW, Raphael BJ, Ding L, Robertson AG, Byers LA, Mills GB, Weinstein JN, Waes CV, Chen Z, Collisson EA, Benz CC, Perou CM, Stuart JM (2014) Multiplatform analysis of 12 cancer types reveals molecular classification within and across tissues of origin. Cell 158(4):929. doi:http://dx.doi.org/10.1016/j.cell.2014.06.049. http://www.sciencedirect.com/science/article/pii/S0092867414008769

    Google Scholar 

  5. Nielsen R, Paul JS, Albrechtsen A, Song YS (2011) Genotype and SNP calling from next-generation sequencing data. Nat Rev Genet 12(6):443. doi:10.1038/nrg2986

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Li H, Durbin R (2010) Fast and accurate long-read alignment with Burrows-Wheeler transform. Bioinformatics 26(5):589. doi:10.1093/bioinformatics/btp698

    Article  PubMed  PubMed Central  Google Scholar 

  7. Langmead B, Trapnell C, Pop M, Salzberg SL (2009) Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biol 10(3):R25. doi:10.1186/gb-2009-10-3-r25

    Article  PubMed  PubMed Central  Google Scholar 

  8. Li R, Yu C, Li Y, Lam TW, Yiu SM, Kristiansen K, Wang J (2009) SOAPZ: an improved ultrafast tool for shot real alignment. Bioinformatics 25(15):1966. doi:10.1093/bioinformatics/btp336

    Article  CAS  PubMed  Google Scholar 

  9. Smith TF, Waterman MS (1981) Identification of common molecular subsequences. J Mol Biol 147(1):195

    Article  CAS  PubMed  Google Scholar 

  10. Needleman SB, Wunsch CD (1970) A general method applicable to the search for similarities in the amino acid sequence of two proteins. J Mol Biol 48(3):443

    Article  CAS  PubMed  Google Scholar 

  11. Garrison E, Marth G (2012) Haplotype-based variant detection from short-read sequencing. arXiv:1207.3907V2 [q-bio.GN]. http://arxiv.org/abs/1207.3907

    Google Scholar 

  12. Teer JK, Bonnycastle LL, Chines PS, Hansen NF, Aoyama N, Swift AJ, Abaan HO, Albert TJ, Margulies EH, Green ED, Collins FS, Mullikin JC, Biesecker LG (2010) Systematic comparison of three genomic enrichment methods for massively parallel DNA sequencing. Genome Res 20(10):1420. doi:10.1101/gr.106716.110

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Ewing B, Green P (1998) Base-calling of automated sequencer traces using phred. II. Error probabilities. Genome Res 8(3):186

    Article  CAS  PubMed  Google Scholar 

  14. Van der Auwera GA, Carneiro MO, Hartl C, Poplin R, Del Angel G, A. Levy-Moonshine, Jordan T, Shakir K, Roazen D, Thibault J, Banks E, Garimella KV, Altshuler D, Gabriel S, DePristo MA (2013) From FastQ data to high confidence variant calls: the Genome Analysis Toolkit best practices pipeline. Curr Protoc Bioinformatics 11(1110):11.10.1. doi:10.1002/0471250953. bi1110s43

    Google Scholar 

  15. Li H (2014) Toward better understanding of artifacts in variant calling from high-coverage samples. Bioinformatics 30(20):2843. doi:10.1093/bioinformatics/ btu356

    Article  PubMed  PubMed Central  Google Scholar 

  16. Goecks J, Nekrutenko A, Taylor J (2010) Galaxy: a comprehensive approach for supporting accessible, reproducible, and transparent computational research in the life sciences. Genome Biol 11(8):R86. doi:10.1186/gb-2010-11-8-r86

    Article  PubMed  PubMed Central  Google Scholar 

  17. Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N, Marth G, Abecasis G, Durbin R (2009) The Sequence Alignment/map format and SAM tools. Bioinformatics 25(16):2078. doi:10.1093/ bioinformatics/btp352

    Article  PubMed  PubMed Central  Google Scholar 

  18. Danecek P, Auton A, Abecasis G, Albers CA, Banks E, DePristo MA, Handsaker RE, Lunter G, Marth GT, Sherry ST, McVean G, Durbin R (2011) The variant call format and VCF tools. Bioinformatics 27(15):2156. doi:10.1093/bioinformatics/btr330

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Wang K, Li M, Hakonarson H (2010) ANNOVAR: functional annotation of genetic variants from high-through put sequencing data. Nucleic Acids Res 38(16):e164. doi:10.1093/nar/gkq603

    Article  PubMed  PubMed Central  Google Scholar 

  20. Teer JK, Green ED, Mullikin JC, Biesecker LG (2012) Var Sifter: visualizing and analyzing exome-scale sequence variation data on a desktop computer. Bioinformatics 28(4):599. doi:10.1093/bioinformatics/btr711

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Karolchik D, Hinrichs AS, Furey TS, Roskin KM, Sugnet CW, Haussler D, Kent WJ (2004) The USSC Table Browser data retrieval tool. Nucleic Acids Res 32(Database issue):D493. doi:10. 1093/nar/gkh103

    Google Scholar 

  22. Stenson PD, Mort M, Ball EV, Shaw K, Phillips A, Cooper DN (2014) The Human Gene Mutation Database: building a comprehensive mutation repository for clinical and molecular genetics, diagnostic testing and personalized genomic medicine. Hum Genet 133(1):1. doi:10.1007/s00439-013-1358-4

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgments

Artwork for Fig. 1 was provided by DXYN Studios. This work was supported by the Intramural Research Program of the National Human Genome Research Institute, National Institutes of Health. The content is solely the responsibility of the author and does not necessarily represent the official views of the National Human Genome Research Institute or the National Institutes of Health.

Author information

Authors and Affiliations

  1. National Human Genome Research Institute, Rockville, MD, USA

    Nancy F. Hansen

Authors
  1. Nancy F. Hansen
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Ohio State University, Biomed Informatics, College of Medicine, Columbus, Ohio, USA

    Ewy Mathé

  2. National Cancer Institute, National Institutes of Health, Columbia, Maryland, USA

    Sean Davis

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer Science+Business Media New York

About this protocol

Cite this protocol

Hansen, N.F. (2016). Variant Calling From Next Generation Sequence Data. In: Mathé, E., Davis, S. (eds) Statistical Genomics. Methods in Molecular Biology, vol 1418. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-3578-9_11

Download citation

  • DOI: https://doi.org/10.1007/978-1-4939-3578-9_11

  • Published:

  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-3576-5

  • Online ISBN: 978-1-4939-3578-9

  • eBook Packages: Springer Protocols

Publish with us

Policies and ethics

Search

Navigation