Comparative and Functional Genomics
Volume 2007 (2007), Article ID 35604, 7 pages
doi:10.1155/2007/35604
Research Article

An Integrated Pipeline of Open Source Software Adapted for Multi-CPU Architectures: Use in the Large-Scale Identification of Single Nucleotide Polymorphisms

B. Jayashree,1 Manindra S. Hanspal,1 Rajgopal Srinivasan,2 R. Vigneshwaran,2 Rajeev K. Varshney,3 N. Spurthi,3 K. Eshwar,3 N. Ramesh,4 S. Chandra,1 and David A. Hoisington3

1Bioinformatics Unit, GT-Biotechnology, International Corps Research Institute for the Semi-Arid Tropics, Patancheru 502324, India
2Advanced Technology Centre, Tata Consultancy Services, Madhapur, Hyderabad 500081, India
3Applied Genomics Laboratory, GT-Biotechnology, International Corps Research Institute for the Semi-Arid Tropics, Patancheru 502324, India
4Novell IDE, Bangalore 560068, India

Received 2 May 2007; Revised 20 July 2007; Accepted 19 October 2007

Academic Editor: Peter Little

Copyright © 2007 B. Jayashree et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. D. G. Wang, J.-B. Fan, and C.-J. Siao, et al., “Large-scale identification, mapping, and genotyping of single-nucleotide polymorphisms in the human genome,” Science, vol. 280, no. 5366, pp. 1077–1082, 1998. View at Publisher · View at Google Scholar
  2. L. Picoult-Newberg, T. E. Ideker, and M. G. Pohl, et al., “Mining SNPs from EST databases,” Genome Research, vol. 9, no. 2, pp. 167–174, 1999.
  3. G. T. Marth, I. Korf, and M. D. Yandell, et al., “A general approach to single-nucleotide polymorphism discovery,” Nature Genetics, vol. 23, no. 4, pp. 452–456, 1999. View at Publisher · View at Google Scholar · View at PubMed
  4. Z. Ning, A. J. Cox, and J. C. Mullikin, “SSAHA: a fast search method for large DNA databases,” Genome Research, vol. 11, no. 10, pp. 1725–1729, 2001. View at Publisher · View at Google Scholar · View at PubMed
  5. J. A. Aerts, B. J. Jungerius, and M. A. M. Groenen, “POSA: perl objects for DNA sequencing data analysis,” BMC Genomics, vol. 5, no. 1, p. 60, 2004. View at Publisher · View at Google Scholar · View at PubMed
  6. F. J. Useche, G. Gao, M. Harafey, and A. Rafalski, “High-throughput identification, database storage and analysis of SNPs in EST sequences,” Genome Informatics, vol. 12, pp. 194–203, 2001.
  7. L. K. Matukumalli, J. J. Grefenstette, D. L. Hyten, I.-Y. Choi, P. B. Cregan, and C. P. Van Tassell, “SNP-PHAGE—high throughput SNP discovery pipeline,” BMC Bioinformatics, vol. 7, p. 468, 2006. View at Publisher · View at Google Scholar · View at PubMed
  8. S. Weckx, J. Del-Favero, and R. Rademakers, et al., “novoSNP, a novel computational tool for sequence variation discovery,” Genome Research, vol. 15, no. 3, pp. 436–442, 2005. View at Publisher · View at Google Scholar · View at PubMed
  9. B. Chevreux, T. Pfisterer, and B. Drescher, et al., “Using the miraEST assembler for reliable and automated mRNA transcript assembly and SNP detection in sequenced ESTs,” Genome Research, vol. 14, no. 6, pp. 1147–1159, 2004.
  10. G. Barker, J. Batley, H. O'Sullivan, K. J. Edwards, and D. Edwards, “Redundancy based detection of sequence polymorphisms in expressed sequence tag data using autoSNP,” Bioinformatics, vol. 19, no. 3, pp. 421–422, 2003.
  11. R. Kota, S. Rudd, and A. Facius, et al., “Snipping polymorphisms from large EST collections in barley (Hordeum vulgare L.),” Molecular Genetics and Genomics, vol. 270, no. 1, pp. 24–33, 2003. View at Publisher · View at Google Scholar · View at PubMed
  12. A. Kalyanaraman, S. Aluru, V. Brendel, and S. Kothari, “Space and time efficient parallel algorithms and software for EST clustering,” IEEE Transactions on Parallel and Distributed Systems, vol. 14, no. 12, pp. 1209–1221, 2003. View at Publisher · View at Google Scholar
  13. X. Huang, J. Wang, S. Aluru, S.-P. Yang, and L. Hillier, “PCAP: a whole-genome assembly program,” Genome Research, vol. 13, no. 9, pp. 2164–2170, 2003.
  14. Z. Zhang, S. Schwartz, L. Wagner, and W. Miller, “A greedy algorithm for aligning DNA sequences,” Journal of Computational Biology, vol. 7, no. 1-2, pp. 203–214, 2000. View at Publisher · View at Google Scholar · View at PubMed
  15. T. Thiel, R. Kota, I. Grosse, N. Stein, and A. Graner, “SNP2CAPS: a SNP and INDEL analysis tool for CAPS marker development,” Nucleic Acids Research, vol. 32, no. 1, p. e5, 2004.
  16. G. Pertea, X. Huang, and F. Liang, et al., “TIGR gene indices clustering tools (TGICL): a software system for fast clustering of large EST datasets,” Bioinformatics, vol. 19, no. 5, pp. 651–652, 2003.
  17. E. S. Mace, H. K. Buhariwalla, and J. H. Crouch, “A high-throughput DNA extraction protocol for tropical molecular breeding programs,” Plant Molecular Biology Reporter, vol. 21, no. 4, pp. 459a–459h, 2003.
  18. E. Bartocci, F. Corradini, E. Merelli, and L. Scortichini, “BioWMS: a web-based workflow management system for bioinformatics,” BMC Bioinformatics, vol. 8, supplement 1, p. S2, 2007.
  19. Q. Lu, P. Hao, and V. Curcin, et al., “KDE bioscience: platform for bioinformatics analysis workflows ,” Journal of Biomedical Informatics, vol. 39, no. 4, pp. 440–450, 2006. View at Publisher · View at Google Scholar · View at PubMed
  20. T. Oinn, M. Addis, and J. Ferris, et al., “Taverna: a tool for the composition and enactment of bioinformatics workflows,” Bioinformatics, vol. 20, no. 17, pp. 3045–3054, 2004. View at Publisher · View at Google Scholar · View at PubMed
  21. S. Hoon, K. K. Ratnapu, and J.-M. Chia, et al., “Biopipe: a flexible framework for protocol-based bioinformatics analysis,” Genome Research, vol. 13, no. 8, pp. 1904–1915, 2003.
  22. B. Schmidt, L. Feng, A. Laud, and Y. Santoso, “Development of distributed bioinformatics applications with GMP,” Concurrency and Computation: Practice & Experience, vol. 16, no. 9, pp. 945–959, 2004.
  23. P. Romano, E. Bartocci, and G. Bertolini, et al., “Biowep: a workflow enactment portal for bioinformatics applications,” BMC Bioinformatics, vol. 8, supplement 1, p. S19, 2007.