Indel variant analysis of short-read sequencing data with Scalpel

Nature Protocols

Volumn 11, Issue 12, 2016, Pages 2529-2548

  Fang, Han ^a,b   Bergmann, Ewa A ^c   Arora, Kanika ^c   Vacic, Vladimir ^c   Zody, Michael C ^c   Iossifov, Ivan ^a   O'rawe, Jason A ^a,b   Wu, Yiyang ^a,b   Jimenez Barron, Laura T ^a,d   Rosenbaum, Julie ^a   Ronemus, Michael ^a   Lee, Yoon Ha ^a   Wang, Zihua ^a   Dikoglu, Esra ^a   Jobanputra, Vaidehi ^a,e   Lyon, Gholson J ^a,b   Wigler, Michael ^a   Schatz, Michael C ^a,f   Narzisi, Giuseppe ^a,c  

^a Simons Center for Quantitative Biology   (United States)

^b STONY BROOK UNIVERSITY   (United States)

^c NEW YORK GENOME CENTER   (United States)

^d INSTITUTO DE CIENCIAS FÍSICAS   (Mexico)

^e Department of Medicine   (United States)

^f Johns Hopkins University   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; AUTISM; CLINICAL PROTOCOL; GENE MAPPING; GENE MUTATION; GENE SEQUENCE; GENETIC ALGORITHM; GENETIC ANALYSIS; GENETIC VARIABILITY; GENOME ANALYSIS; HUMAN GENOME; MEASUREMENT ACCURACY; MUTATIONAL ANALYSIS; PRIORITY JOURNAL; RELIABILITY; SOFTWARE; ALLELE; DNA MUTATIONAL ANALYSIS; GENOMICS; HIGH THROUGHPUT SEQUENCING; HUMAN; INDEL MUTATION; MOLECULAR GENETICS; PROCEDURES; SINGLE NUCLEOTIDE POLYMORPHISM;

ALLELES; DNA MUTATIONAL ANALYSIS; GENOMICS; HIGH-THROUGHPUT NUCLEOTIDE SEQUENCING; HUMANS; INDEL MUTATION; MOLECULAR SEQUENCE ANNOTATION; POLYMORPHISM, SINGLE NUCLEOTIDE;

EID: 84996565284     PISSN: 17542189     EISSN: 17502799     Source Type: Journal    
DOI: 10.1038/nprot.2016.150     Document Type: Article

References (52)

1. Collins, F.S., & Varmus, H. A new initiative on precision medicine. N. Engl. J. Med. 372, 793-795 (2015
2. Highnam, G., et al. An analytical framework for optimizing variant discovery from personal genomes. Nat. Commun. 6, 6275 (2015
3. Watson, J.D., Baker, T.A., Gann, A., Levine, M., & Losick, R. Molecular Biology of the Gene 7th edn. (Cold Spring Harbor Laboratory Press, (2013
4. Nik-Zainal, S., et al. Mutational processes molding the genomes of 21 breast cancers. Cell 149, 979-993 (2012
5. Zaidi, S., et al. De novo mutations in histone-modifying genes in congenital heart disease. Nature 498, 220-223 (2013
6. Iossifov, I., et al. De novo gene disruptions in children on the autistic spectrum. Neuron 74, 285-299 (2012
7. Iossifov, I., et al. The contribution of de novo coding mutations to autism spectrum disorder. Nature 515, 216-221 (2014
8. Gupta, R.S. Protein phylogenies and signature sequences: a reappraisal of evolutionary relationships among archaebacteria, eubacteria, and eukaryotes. Microbiol. Mol. Biol. Rev. 62, 1435-1491 (1998
9. Tian, D., et al. Single-nucleotide mutation rate increases close to insertions/deletions in eukaryotes. Nature 455, 105-108 (2008
10. MacArthur, D.G., et al. A systematic survey of loss-of-function variants in human protein-coding genes. Science 335, 823-828 (2012
11. Fukuoka, S., et al. Loss of function of a proline-containing protein confers durable disease resistance in rice. Science 325, 998-1001 (2009
12. Denver, D.R., et al. High mutation rate and predominance of insertions in the Caenorhabditis elegans nuclear genome. Nature 430, 679-682 (2004
13. Montgomery, S.B., et al. The origin, evolution, and functional impact of short insertion-deletion variants identified in 179 human genomes. Genome Res. 23, 749-761 (2013
14. Mullaney, J.M., et al. Small insertions and deletions (INDELs) in human genomes. Hum. Mol. Genet. 19, R131-R136 (2010
15. Jiang, Y., Turinsky, A.L., & Brudno, M. The missing indels: an estimate of indel variation in a human genome and analysis of factors that impede detection. Nucleic Acids Res. 43, 7217-7228 (2015
16. Narzisi, G., et al. Accurate de novo and transmitted indel detection in exome-capture data using microassembly. Nat. Methods 11, 1033-1036 (2014
17. Narzisi, G., & Schatz, M.C. The challenge of small-scale repeats for indel discovery. Front. Bioeng. Biotechnol. 3, 8 (2015
18. Fang, H., et al. Reducing INDEL calling errors in whole genome and exome sequencing data. Genome Med. 6, 89 (2014
19. DePristo, M.A., et al. A framework for variation discovery and genotyping using next-generation DNA sequencing data. Nat. Genet. 43, 491-498 (2011
20. Albers, C.A., et al. Dindel: accurate indel calls from short-read data. Genome Res. 21, 961-973 (2011
21. Li, H., et al. The Sequence Alignment/Map format and SAMtools. Bioinformatics 25, 2078-2079 (2009
22. Ye, K., et al. Pindel: a pattern growth approach to detect break points of large deletions and medium sized insertions from paired-end short reads. Bioinformatics 25, 2865-2871 (2009
23. Karakoc, E., et al. Detection of structural variants and indels within exome data. Nat. Methods 9, 176-178 (2012
24. Iqbal, Z., et al. De novo assembly and genotyping of variants using colored de Bruijn graphs. Nat. Genet. 44, 226-232 (2012
25. Van der Auwera, G.A., et al. From FastQ data to high confidence variant calls: the Genome Analysis Toolkit best practices pipeline. Curr. Protoc. Bioinformatics 11, 11 10 1-11 10 33 (2013
26. Li, S., et al. SOAPindel: efficient identification of indels from short paired reads. Genome Res. 23, 195-200 (2013
27. Pabinger, S., et al. A survey of tools for variant analysis of next-generation genome sequencing data. Brief Bioinform. 15, 256-278 (2014
28. Rimmer, A., et al. Integrating mapping-, assembly- and haplotype-based approaches for calling variants in clinical sequencing applications. Nat. Genet. 46, 912-918 (2014
29. Mose, L.E., et al. ABRA: improved coding indel detection via assembly-based realignment. Bioinformatics 30, 2813-2815 (2014
30. Chen, K., et al. TIGRA: a targeted iterative graph routing assembler for breakpoint assembly. Genome Res. 24310-24317 (2014
31. Weisenfeld, N.I., et al. Comprehensive variation discovery in single human genomes. Nat. Genet. 46, 1350-1355 (2014
32. Leggett, R.M., et al. Identifying and classifying trait linked polymorphisms in non-reference species by walking coloured de Bruijn graphs. PLoS One 8, e60058 (2013
33. Chen, X., et al. Manta: rapid detection of structural variants and indels for germline and cancer sequencing applications. Bioinformatics 32, 1220-1222 (2016
34. Yang, R., et al. ScanIndel: a hybrid framework for indel detection via gapped alignment, split reads and de novo assembly. Genome Med. 7, 127 (2015
35. Highnam, G., et al. Accurate human microsatellite genotypes from high-throughput resequencing data using informed error profiles. Nucleic Acids Res. 41, e32 (2013
36. Gymrek, M., et al. lobSTR: A short tandem repeat profiler for personal genomes. Genome Res. 22, 1154-1162 (2012
37. Ye, K., et al. Systematic discovery of complex insertions and deletions in human cancers. Nat. Med. 22, 97-104 (2016
38. Gnerre, S., et al. High-quality draft assemblies of mammalian genomes from massively parallel sequence data. Proc. Natl. Acad. Sci. USA 108, 1513-1518 (2011
39. Berlin, K., et al. Assembling large genomes with single-molecule sequencing and locality-sensitive hashing. Nat. Biotechnol. 33, 623-630 (2015
40. Paila, U., et al. GEMINI: integrative exploration of genetic variation and genome annotations. PLoS Comput. Biol. 9, e1003153 (2013
41. Brannon, A.R., et al. Comparative sequencing analysis reveals high genomic concordance between matched primary and metastatic colorectal cancer lesions. Genome Biol. 15, 454 (2014
42. Eberle, M.A., et al. A reference dataset of 5.4 million phased human variants validated by genetic inheritance from sequencing a three-generation 17-member pedigree. (bioRxiv http: //dx.doi.org/10.1101/055541 (2016
43. Li, H. Aligning sequence reads, clone sequences and assembly contigs with BWA-MEM. ArXiv e-prints 1303, 3997 (2013
44. Quinlan, A.R., & Hall, I.M. BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics 26, 841-842 (2010
45. Wang, K., Li, M., & Hakonarson, H. ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data. Nucleic Acids Res. 38, e164 (2010
46. Robinson, J.T., et al. Integrative genomics viewer. Nat. Biotechnol. 29, 24-26 (2011
47. Genomes Project, C., et al. A map of human genome variation from population-scale sequencing. Nature 467, 1061-1073 (2010
48. Tan, A., Abecasis, G.R., & Kang, H.M. Unified representation of genetic variants. Bioinformatics 31, 2202-2204 (2015
49. Van der Auwera, G.A., et al. From FastQ data to high confidence variant calls: the Genome Analysis Toolkit best practices pipeline. Curr. Protoc. Bioinformatics 43, 11 10 1-11 10 33 (2013
50. Cingolani, P., et al. A program for annotating and predicting the effects of single nucleotide polymorphisms, SnpEff: SNPs in the genome of Drosophila melanogaster strain w1118; iso-2; iso-3. Fly (Austin) 6, 80-92 (2012
51. McLaren, W., et al. Deriving the consequences of genomic variants with the Ensembl API and SNP Effect Predictor. Bioinformatics 26, 2069-2070 (2010
52. McCarthy, D.J., et al. Choice of transcripts and software has a large effect on variant annotation. Genome Med. 6, 26 (2014