1 / 18

Genome analysis

Genome analysis. Lecture 11: literature discussion. Papers. Consensus sequences improve PSI-BLAST through mimicking profile-profile alignments Dariusz Przybylski and Burkhard Rost Nucleic Acids Research 2007

luka
Download Presentation

Genome analysis

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Genome analysis Lecture 11: literature discussion

  2. Papers • Consensus sequences improve PSI-BLAST through mimicking profile-profile alignmentsDariusz Przybylski and Burkhard RostNucleic Acids Research 2007 • Heads or Tails: A Simple Reliability Check for Multiple Sequence AlisngmentsGiddy Landan and Dan GraurMolecular Biology and Evolution 2007

  3. 1st paper

  4. BLAST and PSI-BLAST • BLAST is a sequence-sequence method:Sequence (query) –Sequence (nr database) • PSI-BLAST is a profile-sequence method:RUN 1: just like normal BLASTRUN 2: Profile (query) –Sequence (nr database)

  5. Accuracy vs. Speedthe usual dilemma … Sequence – Sequence Profile – Sequence Profile – Profile ACCURACY SPEED

  6. Profile A C D . . Y Consensus sequences - 1 • “1-D semplification of the sequence profile” • Compromise between accuracy and speed

  7. Consensus sequences - 2 • How can we display consensus sequences? • Replace the complete sequence by the consensus sequence (100%) • Replace only local parts by consensus segments(top 50% & low 50%) • Tests on: • Sequence – Consensus • Consensus – Consensus • Profile – Consensus

  8. Method

  9. Evaluation of results • Ability to identify functionally related proteins • Correctly align them based on structural alignments • Function is more conserved than Structure

  10. Functional evaluation: SCOP classes folds superfamilies families

  11. Structural evaluation: 3D model quality • Making the model: simply copy coordinates • Test model quality through LGA superposition (query model with query structure) • ‘Golden standard’: structural alignment of known structure of query & template with MAMMOTH  MAGFWIL MLGKSLL query template

  12. Final sets for alignment test • Set 1: most related, non-trivial pairs(no. = 1647) • Set 2: more difficult, most diverged(no. = 5551)

  13. Results functional analysis

  14. Results structural analysis

  15. 2nd paper

  16. There are quite some multiple alignment methods .... PRALINE ... but what about accuracy?

  17. Benchmarking: usual on structural alignments. • There are several alignment benchmarks, such as BAliBASE, HOMSTRAD or SABMARK • But they can only tell us the alignment quality on their predefined sets • Alignment methods need to define quality and consistency criteria.

  18. Heads-or-Tails method ?

More Related