Skip to main content

Detecting Medium and Large Insertions and Deletions with transIndel

  • Protocol
  • First Online:
Variant Calling

Part of the book series: Methods in Molecular Biology ((MIMB,volume 2493))

Abstract

Insertions and deletions (indels) are primarily detected from DNA sequencing (DNA-seq) data, but their transcriptional consequences remain unexplored due to challenges in distinguishing medium- and large-sized indels from RNA splicing events in RNA-seq data. We introduce transIndel, a splice-aware algorithm that parses the chimeric alignments predicted by a short read aligner and reconstructs the mid-sized insertions and large deletions based on the linear alignments of split reads from DNA-seq or RNA-seq data. Here, we describe the method and provide a tutorial on the installation and application of transIndel.

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

Access this chapter

Protocol
USD 49.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 249.99
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. Shlien A, Raine K, Fuligni F, Arnold R, Nik-Zainal S, Dronov S, Mamanova L, Rosic A, Ju YS, Cooke SL, Ramakrishna M, Papaemmanuil E, Davies HR, Tarpey PS, Van Loo P, Wedge DC, Jones DR, Martin S, Marshall J, Anderson E, Hardy C, Icgc Breast Cancer Working Group OBCRC, Barbashina V, Aparicio SA, Sauer T, Garred O, Vincent-Salomon A, Mariani O, Boyault S, Fatima A, Langerod A, Borg A, Thomas G, Richardson AL, Borresen-Dale AL, Polyak K, Stratton MR, Campbell PJ (2016) Direct transcriptional consequences of somatic mutation in breast cancer. Cell Rep 16(7):2032–2046. https://doi.org/10.1016/j.celrep.2016.07.028

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Radenbaugh AJ, Ma S, Ewing A, Stuart JM, Collisson EA, Zhu J, Haussler D (2014) RADIA: RNA and DNA integrated analysis for somatic mutation detection. PLoS One 9(11):e111516. https://doi.org/10.1371/journal.pone.0111516

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. O’Brien TD, Jia P, Xia J, Saxena U, Jin H, Vuong H, Kim P, Wang Q, Aryee MJ, Mino-Kenudson M, Engelman JA, Le LP, Iafrate AJ, Heist RS, Pao W, Zhao Z (2015) Inconsistency and features of single nucleotide variants detected in whole exome sequencing versus transcriptome sequencing: a case study in lung cancer. Methods 83:118–127. https://doi.org/10.1016/j.ymeth.2015.04.016

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Wilkerson MD, Cabanski CR, Sun W, Hoadley KA, Walter V, Mose LE, Troester MA, Hammerman PS, Parker JS, Perou CM, Hayes DN (2014) Integrated RNA and DNA sequencing improves mutation detection in low purity tumors. Nucleic Acids Res 42(13):e107. https://doi.org/10.1093/nar/gku489

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. McPherson A, Wu C, Hajirasouliha I, Hormozdiari F, Hach F, Lapuk A, Volik S, Shah S, Collins C, Sahinalp SC (2011) Comrad: detection of expressed rearrangements by integrated analysis of RNA-Seq and low coverage genome sequence data. Bioinformatics 27(11):1481–1488. https://doi.org/10.1093/bioinformatics/btr184

    Article  CAS  PubMed  Google Scholar 

  6. Piskol R, Ramaswami G, Li JB (2013) Reliable identification of genomic variants from RNA-seq data. Am J Hum Genet 93(4):641–651. https://doi.org/10.1016/j.ajhg.2013.08.008

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Zhang J, White NM, Schmidt HK, Fulton RS, Tomlinson C, Warren WC, Wilson RK, Maher CA (2016) INTEGRATE: gene fusion discovery using whole genome and transcriptome data. Genome Res 26(1):108–118. https://doi.org/10.1101/gr.186114.114

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Sun Z, Bhagwate A, Prodduturi N, Yang P, Kocher JA (2017) Indel detection from RNA-seq data: tool evaluation and strategies for accurate detection of actionable mutations. Brief Bioinform 18(6):973–983. https://doi.org/10.1093/bib/bbw069

    Article  CAS  PubMed  Google Scholar 

  9. Wajnberg G, Passetti F (2016) Using high-throughput sequencing transcriptome data for INDEL detection: challenges for cancer drug discovery. Expert Opin Drug Discov 11(3):257–268. https://doi.org/10.1517/17460441.2016.1143813

    Article  CAS  PubMed  Google Scholar 

  10. Yang R, Van Etten JL, Dehm SM (2018) Indel detection from DNA and RNA sequencing data with transIndel. BMC Genomics 19(1). https://doi.org/10.1186/s12864-018-4671-4

  11. Li H (2013) Aligning sequence reads, clone sequences and assembly contigs with BWA-MEM.arXiv:1303.3997

    Google Scholar 

  12. Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N, Marth G, Abecasis G, Durbin R, Genome Project Data Processing S (2009) The sequence alignment/map format and SAMtools. Bioinformatics 25(16):2078–2079. https://doi.org/10.1093/bioinformatics/btp352

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Anders S, Pyl PT, Huber W (2015) HTSeq--a Python framework to work with high-throughput sequencing data. Bioinformatics 31(2):166–169. https://doi.org/10.1093/bioinformatics/btu638

    Article  CAS  PubMed  Google Scholar 

  14. Kent WJ, Sugnet CW, Furey TS, Roskin KM, Pringle TH, Zahler AM, Haussler D (2002) The human genome browser at UCSC. Genome Res 12(6):996–1006. https://doi.org/10.1101/gr.229102

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Frankish A, Diekhans M, Ferreira AM, Johnson R, Jungreis I, Loveland J, Mudge JM, Sisu C, Wright J, Armstrong J, Barnes I, Berry A, Bignell A, Carbonell Sala S, Chrast J, Cunningham F, Di Domenico T, Donaldson S, Fiddes IT, Garcia Giron C, Gonzalez JM, Grego T, Hardy M, Hourlier T, Hunt T, Izuogu OG, Lagarde J, Martin FJ, Martinez L, Mohanan S, Muir P, Navarro FCP, Parker A, Pei B, Pozo F, Ruffier M, Schmitt BM, Stapleton E, Suner MM, Sycheva I, Uszczynska-Ratajczak B, Xu J, Yates A, Zerbino D, Zhang Y, Aken B, Choudhary JS, Gerstein M, Guigo R, Hubbard TJP, Kellis M, Paten B, Reymond A, Tress ML, Flicek P (2019) GENCODE reference annotation for the human and mouse genomes. Nucleic Acids Res 47(D1):D766–D773. https://doi.org/10.1093/nar/gky955

    Article  CAS  PubMed  Google Scholar 

  16. Danecek P, Auton A, Abecasis G, Albers CA, Banks E, De Pristo MA, Handsaker RE, Lunter G, Marth GT, Sherry ST, McVean G, Durbin R, Genomes Project Analysis G (2011) The variant call format and VCFtools. Bioinformatics 27(15):2156–2158. https://doi.org/10.1093/bioinformatics/btr330

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Barretina J, Caponigro G, Stransky N, Venkatesan K, Margolin AA, Kim S, Wilson CJ, Lehar J, Kryukov GV, Sonkin D, Reddy A, Liu M, Murray L, Berger MF, Monahan JE, Morais P, Meltzer J, Korejwa A, Jane-Valbuena J, Mapa FA, Thibault J, Bric-Furlong E, Raman P, Shipway A, Engels IH, Cheng J, Yu GK, Yu J, Aspesi P Jr, de Silva M, Jagtap K, Jones MD, Wang L, Hatton C, Palescandolo E, Gupta S, Mahan S, Sougnez C, Onofrio RC, Liefeld T, MacConaill L, Winckler W, Reich M, Li N, Mesirov JP, Gabriel SB, Getz G, Ardlie K, Chan V, Myer VE, Weber BL, Porter J, Warmuth M, Finan P, Harris JL, Meyerson M, Golub TR, Morrissey MP, Sellers WR, Schlegel R, Garraway LA (2012) The cancer cell line encyclopedia enables predictive modelling of anticancer drug sensitivity. Nature 483(7391):603–607. https://doi.org/10.1038/nature11003

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Leinonen R, Sugawara H, Shumway M, International Nucleotide Sequence Database C (2011) The sequence read archive. Nucleic Acids Res 39(Database issue):D19–D21. https://doi.org/10.1093/nar/gkq1019

    Article  CAS  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Rendong Yang .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2022 The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature

About this protocol

Check for updates. Verify currency and authenticity via CrossMark

Cite this protocol

Wang, TY., Yang, R. (2022). Detecting Medium and Large Insertions and Deletions with transIndel. In: Ng, C., Piscuoglio, S. (eds) Variant Calling. Methods in Molecular Biology, vol 2493. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-2293-3_5

Download citation

  • DOI: https://doi.org/10.1007/978-1-0716-2293-3_5

  • Published:

  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-0716-2292-6

  • Online ISBN: 978-1-0716-2293-3

  • eBook Packages: Springer Protocols

Publish with us

Policies and ethics