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Sequence Alignment technology

Sequence Alignment technology. Chengwei Lei Fang Yuan Saleh Tamim. Goal. Save time “PASS : a Program to Align Short Sequences Davide Campagna et al . Bioinformatics (2009 )” Save money

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Sequence Alignment technology

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  1. Sequence Alignment technology Chengwei Lei Fang Yuan SalehTamim

  2. Goal • Save time “PASS: a Program to Align Short SequencesDavideCampagna et al. Bioinformatics (2009)” • Save money “Optimal pooling for genome re-sequencing with ultra-high-throughput short-read technologies, ImanHajirasouliha, Bioinformatics (2008) ”

  3. Keywords in both paper • Reference sequence: A long Genomic sequence. • Short reads: Input short strings. e.g. ATGCGTAC

  4. Save time – PASS program • PASS, a new algorithm to align short DNA sequences allowing gaps and mismatches. • The performance of the program is very striking both for sensitivity and speed. For instance, gap alignment is achieved hundreds of times faster than BLAST and several times faster than SOAP, especially when gaps are allowed.

  5. PASS Program to Align Short Sequences Performs gapped and ungapped alignment onto a reference sequence Seed words (11 and 12 bases) Short reads (7 and 8 bases) PST - calculated with the Needleman and Wunsch algorithm supplied with PASS Handles data generated by Solexa, SOLiD or 454 technologies

  6. Approach/Algorithm

  7. Analysis and Results • Comparison of PASS with SOAP • PASS has better sensitivity with words of 11 and runs at least 10 times faster

  8. Save money - Optimal pooling method • A set of experiments using the Solexa technology, based on bacterial artificial chromosome (BAC) clones, and address an experimental design problem. • Basic idea: More than one BAC per lane in order to maximize the throughput of the Solexa technology, hence minimize its cost.

  9. Inputs Reference sequences Input strings (short reads)

  10. Normal pooling method • One other hurdle in designing a globally optimal experiment is the rapid proliferation of number of possible configurations. For instance, if we would like to pool m=150 BACs into 15 groups of size=10, we would need to consider Infeasible to search all these configurations Optimal Pooling method

  11. Optimal Pooling method Reference sequence Input strings (short reads)

  12. Optimal Pooling method Reference sequences Input strings (short reads)

  13. Optimal Pooling method Reference sequences Input strings (short reads) Pool

  14. Problem • How to separate the groups of short reads?

  15. Optimal Pooling method Reference sequence Input strings (short reads) Pool

  16. Two cases

  17. Result

  18. Conclusion • Program for Save time “PASS: a Program to Align Short SequencesDavideCampagna et al. Bioinformatics (2009)” • Algorithm for Save money “Optimal pooling for genome re-sequencing with ultra-high-throughput short-read technologies, ImanHajirasouliha, Bioinformatics (2008) ”

  19. Q & A

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