SeqMule: Automated pipeline for analysis of human exome/genome sequencing data

Scientific Reports

Volumn 5, Issue , 2015, Pages

  Guo, Yunfei ^a   Ding, Xiaolei ^b   Shen, Yufeng ^c   Lyon, Gholson J ^d,e   Wang, Kai ^a,e  

^a UNIVERSITY OF SOUTHERN CALIFORNIA   (United States)

^b NANJING FORESTRY UNIVERSITY   (China)

^c Och Spine at New York Presbyterian Hospitals   (United States)

^d Simons Center for Quantitative Biology   (United States)

^e Stanley Institute for Cognitive Genomics Cold Spring Harbor Laboratory ^*  (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BIOLOGY; EXOME; GENOMICS; HIGH THROUGHPUT SEQUENCING; HUMAN; HUMAN GENOME; PROCEDURES; REPRODUCIBILITY; SOFTWARE;

COMPUTATIONAL BIOLOGY; EXOME; GENOME, HUMAN; GENOMICS; HIGH-THROUGHPUT NUCLEOTIDE SEQUENCING; HUMANS; REPRODUCIBILITY OF RESULTS; SOFTWARE;

EID: 84942024668     PISSN: None     EISSN: 20452322     Source Type: Journal    
DOI: 10.1038/srep14283     Document Type: Article

References (49)

1. Rabbani, B., Mahdieh, N., Hosomichi, K., Nakaoka, H. & Inoue, I. Next-generation sequencing: impact of exome sequencing in characterizing Mendelian disorders. J Hum Genet 57, 621-632 (2012).
2. Bamshad, M. J. et al. Exome sequencing as a tool for Mendelian disease gene discovery. Nat Rev Genet 12, 745-755 (2011).
3. Meyerson, M., Gabriel, S. & Getz, G. Advances in understanding cancer genomes through second-generation sequencing. Nat Rev Genet 11, 685-696 (2010).
4. Mardis, E. R. The impact of next-generation sequencing technology on genetics. Trends in genetics: TIG 24, 133-141 (2008).
5. Morozova, O. & Marra, M. A. Applications of next-generation sequencing technologies in functional genomics. Genomics 92, 255-264 (2008).
6. Genomes Project, C. et al. A map of human genome variation from population-scale sequencing. Nature 467, 1061-1073 (2010).
7. Lam, H. Y. et al. Performance comparison of whole-genome sequencing platforms. Nat Biotechnol 30, 78-82 (2012).
8. O'Rawe, J. et al. Low concordance of multiple variant-calling pipelines: practical implications for exome and genome sequencing. Genome Med 5, 28 (2013).
9. Ruffalo, M., LaFramboise, T. & Koyuturk, M. Comparative analysis of algorithms for next-generation sequencing read alignment. Bioinformatics 27, 2790-2796 (2011).
10. Hull, D. et al. Taverna: a tool for building and running workflows of services. Nucleic Acids Res 34, W729-732 (2006).
11. Reich, M. et al. GenePattern 2.0. Nat Genet 38, 500-501 (2006).
12. Abouelhoda, M., Issa, S. A. & Ghanem, M. Tavaxy: integrating Taverna and Galaxy workflows with cloud computing support. BMC Bioinformatics 13, 77 (2012).
13. Goecks, J., Nekrutenko, A., Taylor, J. & Galaxy, T. Galaxy: a comprehensive approach for supporting accessible, reproducible, and transparent computational research in the life sciences. Genome Biol 11, R86 (2010).
14. Pabinger, S. et al. A survey of tools for variant analysis of next-generation genome sequencing data. Brief Bioinform 15, 256-278 (2014).
15. Gentleman, R. C. et al. Bioconductor: open software development for computational biology and bioinformatics. Genome Biol 5, R80 (2004).
16. Stajich, J. E. et al. The Bioperl toolkit: Perl modules for the life sciences. Genome Res 12, 1611-1618 (2002).
17. Chang, X. & Wang, K. wANNOVAR: annotating genetic variants for personal genomes via the web. Journal of medical genetics 49, 433-436 (2012).
18. Krampis, K. et al. Cloud BioLinux: pre-configured and on-demand bioinformatics computing for the genomics community. BMC Bioinformatics 13, 42 (2012).
19. Nocq, J., Celton, M., Gendron, P., Lemieux, S. & Wilhelm, B. T. Harnessing virtual machines to simplify next-generation DNA sequencing analysis. Bioinformatics 29, 2075-2083 (2013).
20. Angiuoli, S. V. et al. CloVR: a virtual machine for automated and portable sequence analysis from the desktop using cloud computing. BMC Bioinformatics 12, 356 (2011).
21. Li, H. & Durbin, R. Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics 25, 1754-1760 (2009).
22. Langmead, B., Trapnell, C., Pop, M. & Salzberg, S. L. Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biol 10, R25 (2009).
23. Langmead, B. & Salzberg, S. L. Fast gapped-read alignment with Bowtie 2. Nat Methods 9, 357-359 (2012).
24. Li, R. et al. SOAP2: an improved ultrafast tool for short read alignment. Bioinformatics 25, 1966-1967 (2009).
25. Zaharia, M. et al. Faster and More Accurate Sequence Alignment with SNAP. ArXiv e-prints 1111, 5572, doi: 2011arXiv1111.5572Z (2011).
26. McKenna, A. et al. The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res 20, 1297-1303 (2010).
27. Li, H. et al. The Sequence Alignment/Map format and SAMtools. Bioinformatics 25, 2078-2079 (2009).
28. Koboldt, D. C. et al. VarScan 2: somatic mutation and copy number alteration discovery in cancer by exome sequencing. Genome Res 22, 568-576 (2012).
29. Li, R. et al. SNP detection for massively parallel whole-genome resequencing. Genome Res 19, 1124-1132 (2009).
30. Danecek, P. et al. The variant call format and VCFtools. Bioinformatics 27, 2156-2158 (2011).
31. R. Pandya, W. B. et al. SNAP: fast, accurate sequence alignment enabling biological applications. ASHG meeting 2014, San Diego (2014).
32. Wang, K., Li, M. & Hakonarson, H. ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data. Nucleic Acids Res 38, e164 (2010).
33. Wang, W., Wei, Z., Lam, T. W. & Wang, J. Next generation sequencing has lower sequence coverage and poorer SNP-detection capability in the regulatory regions. Scientific reports 1, 55 (2011).
34. Purcell, S. et al. PLINK: a tool set for whole-genome association and population-based linkage analyses. American journal of human genetics 81, 559-575 (2007).
35. Utsunomiya, Y. T. et al. mendelFix: a Perl script for checking Mendelian errors in high density SNP data of trio designs. arXiv:1306.2243 (2013).
36. Chen, H. VennDiagram: Generate high-resolution Venn and Euler plots. CRAN (2011).
37. Altshuler, D. M. et al. An integrated map of genetic variation from 1,092 human genomes. Nature 491, 56-65 (2012).
38. Lyon, G. J. et al. Exome sequencing and unrelated findings in the context of complex disease research: ethical and clinical implications. Discovery medicine 12, 41 (2011).
39. Genomes Project, C. et al. An integrated map of genetic variation from 1,092 human genomes. Nature 491, 56-65 (2012).
40. Li, B. et al. A likelihood-based framework for variant calling and de novo mutation detection in families. PLoS genetics 8, e1002944 (2012).
41. Ramu, A. et al. DeNovoGear: de novo indel and point mutation discovery and phasing. Nat Methods 10, 985-987 (2013).
42. Peng, G. et al. Rare variant detection using family-based sequencing analysis. Proc Natl Acad Sci USA 110, 3985-3990 (2013).
43. Nielsen, R., Korneliussen, T., Albrechtsen, A., Li, Y. & Wang, J. SNP calling, genotype calling, and sample allele frequency estimation from New-Generation Sequencing data. PLoS One 7, e37558 (2012).
44. Afgan, E. et al. Galaxy CloudMan: delivering cloud compute clusters. BMC Bioinformatics 11 Suppl 12, S4 (2010).
45. Lam, H. Y. et al. Detecting and annotating genetic variations using the HugeSeq pipeline. Nat Biotechnol 30, 226-229 (2012).
46. Blanca, J. M., Pascual, L., Ziarsolo, P., Nuez, F. & Canizares, J. ngs-backbone: a pipeline for read cleaning, mapping and SNP calling using next generation sequence. BMC Genomics 12, 285 (2011).
47. Shi, L. et al. Genotype-first inverted question mark approaches on a curious case of idiopathic progressive cognitive decline. BMC medical genomics 7, 66 (2014).
48. Jia, H., Guo, Y., Zhao, W. & Wang, K. Long-range PCR in next-generation sequencing: comparison of six enzymes and evaluation on the MiSeq sequencer. Scientific reports 4, 5737 (2014).
49. Zhang, X. et al. Exome sequencing on malignant meningiomas identified mutations in neurofibromatosis type 2 (NF2) and meningioma 1 (MN1) genes. Discov Med 18, 301-311 (2014).