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Genomic sequence alignment in elasticsearch
- 1. GoingOrganic Genomic sequence alignment in elasticsearch Tuesday, August 13, 13
- 2. GoingOrganic A story of a side project gone horribly wrong Tuesday, August 13, 13
- 3. you are human. hopefully ^ Tuesday, August 13, 13
- 4. you have lots of these 60s ribosomal protein Tuesday, August 13, 13
- 5. this is a bacteria. ʘ‿ʘ hey Tuesday, August 13, 13
- 6. he has a bunch of these too 50s ribosomal protein Tuesday, August 13, 13
- 7. They look pretty similar... 60s ribosomal protein 50s ribosomal protein Tuesday, August 13, 13
- 8. ...or do they? MAKLTKRMRVIREKVDATKQ YDINEAIALLKELATAKFVE SVDVAVNLGIDARKSDQNVR GATVLPHGTGRSVRVAVFTQ GANAEAAKAAGAELVGMEDL ADQIKKGEMNFDVVIASPDA MRVVGQLGQVLGPRGLMPNP KVGTVTPNVAEAVKNAKAGQ VRYRNDKNGIIHTTIGKVDF DADKLKENLEALLVALKKAK PTQAKGVYIKKVSISTTMGA GVAVDQAGLSASVN MAQDQGEKENPMRELRIRKL CLNICVGESGDRLTRAAKVL EQLTGQTPVFSKARYTVRSF GIRRNEKIAVHCTVRGAKAE EILEKGLKVREYELRKNNFS DTGNFGFGIQEHIDLGIKYD PSIGIYGLDFYVVLGRPGFS IADKKRRTGCIGAKHRISKE EAMRWFQQKYDGIILPGK 60s ribosomal protein 50s ribosomal protein Tuesday, August 13, 13
- 10. Shhh...don’t tell them I’m a biologist Tuesday, August 13, 13
- 11. 60% similar MAKLTKRMRVIREKVDATKQ YDINEAIALLKELATAKFVE SVDVAVNLGIDARKSDQNVR GATVLPHGTGRSVRVAVFTQ GANAEAAKAAGAELVGMEDL ADQIKKGEMNFDVVIASPDA MRVVGQLGQVLGPRGLMPNP KVGTVTPNVAEAVKNAKAGQ VRYRNDKNGIIHTTIGKVDF DADKLKENLEALLVALKKAK PTQAKGVYIKKVSISTTMGA GVAVDQAGLSASVN MAQDQGEKENPMRELRIRKL CLNICVGESGDRLTRAAKVL EQLTGQTPVFSKARYTVRSF GIRRNEKIAVHCTVRGAKAE EILEKGLKVREYELRKNNFS DTGNFGFGIQEHIDLGIKYD PSIGIYGLDFYVVLGRPGFS IADKKRRTGCIGAKHRISKE EAMRWFQQKYDGIILPGK 60s ribosomal protein 50s ribosomal protein Tuesday, August 13, 13
- 16. actual sequence alignment Tuesday, August 13, 13
- 17. exact identity Tuesday, August 13, 13
- 18. physical similarity Tuesday, August 13, 13
- 19. gaps Tuesday, August 13, 13
- 20. pairwise alignment problem.is a solved Tuesday, August 13, 13
- 21. so, what’s the problem? Tuesday, August 13, 13
- 22. pairwise alignment is the problem. Tuesday, August 13, 13
- 24. “nr” database Tuesday, August 13, 13
- 25. 16 Gb flat file “nr” database Tuesday, August 13, 13
- 26. 26,000,000 sequences 16 Gb flat file “nr” database Tuesday, August 13, 13
- 27. 26,000,000 sequences 9,600,000,000 residues 16 Gb flat file “nr” database Tuesday, August 13, 13
- 29. BLAST Tuesday, August 13, 13
- 30. 30-90 seconds you say? Tuesday, August 13, 13
- 31. challenge accepted. Tuesday, August 13, 13
- 32. Exact identity: term filter Tuesday, August 13, 13
- 33. Exact identity: term filter Similarity: fuzzy query Tuesday, August 13, 13
- 34. Exact identity: term filter Similarity: fuzzy query Gaps: sloppy phrase Tuesday, August 13, 13
- 35. a month passes Tuesday, August 13, 13
- 36. panic sets in Tuesday, August 13, 13
- 37. a sampler of my failures (with success at the end) Tuesday, August 13, 13
- 42. query: match: query: “MAQDQGEKENPMRELRIRKL” analyzer: ngram3 min_should_match: 20% match query Tuesday, August 13, 13
- 43. match query precision: recall: speed: C+ B+ D+ not fuzzy enough - poor gap support - I/O thrashing Tuesday, August 13, 13
- 44. query: bool: must: match: query: “MAQDQGEKENPMRELRIRKL” min_should_match: 20% should: - custom_filters_score: query: match_all filters: - “MAQ” (exact match), boost10 - “MAE” (alternative seed), boost5 - “MRL” (alternative seed), boost3 score_mode: first - custom_filters_score: ... ... min_should_match: 20% custom_filters_score Tuesday, August 13, 13
- 45. custom_filters_score precision: recall: speed: C+ A+ D+ fuzzy with no ordering - I/O thrashing - filter evictions Tuesday, August 13, 13
- 46. query: bool: should: - span_near: - span_term (MAQ) - span_term (KEN) - span_near: - span_term (KEN) - span_or: - span_term (RKL) - span_term (ROL) - span_term (RED) - span_near: - span_or: - span_term (RKL) - span_term (ROL) - span_term (RED) - span_term (...) ... span queries MAQDQGEKENPMRELRIRKL Tuesday, August 13, 13
- 47. span queries precision: recall: speed: A- A- F- slow, unable to filter Tuesday, August 13, 13
- 48. Bucketed spans Chaos Game Representation w/ geohash Common Terms query Fuzzy query Synonym injection ... many hours of experiments FAILED Tuesday, August 13, 13
- 49. what’s the problem? Tuesday, August 13, 13
- 50. sparsity inverted indices love Tuesday, August 13, 13
- 51. 20 characters alphabet 3-gram: 4-gram: 5-gram: 6,840 permutations 116,280 1,860,480 Tuesday, August 13, 13
- 52. 20 characters alphabet 3-gram: 5-gram: too much sharing! too insensitive! Tuesday, August 13, 13
- 53. 3-gram: single hit Tuesday, August 13, 13
- 54. 3-gram: single hit Tuesday, August 13, 13
- 55. we need a new approach. Tuesday, August 13, 13
- 56. we need a new approach. sparsity. Tuesday, August 13, 13
- 57. we need a new approach. sparsity. fuzziness. Tuesday, August 13, 13
- 58. we need a new approach. sparsity. fuzziness. a hash! Tuesday, August 13, 13
- 59. hash? we need a Tuesday, August 13, 13
- 60. hash: distributes similar values into unique buckets Tuesday, August 13, 13
- 61. locality sensitive hash: distributes similar values into the same bucket Tuesday, August 13, 13
- 63. Random Projections 1) pick k random 3-grams QDK CVV QED MRE ...Tuesday, August 13, 13
- 64. Random Projections 2) iterate over sequence MAQDQGEKENPMRELRIRKL -3 QDKQDK Tuesday, August 13, 13
- 65. Random Projections 2) iterate over sequence ...QDK MAQDQGEKENPMRELRIRKL 6 QDK Tuesday, August 13, 13
- 66. Random Projections 2) iterate over sequence MAQDQGEKENPMRELRIRKL 13 ......QDKQDK Tuesday, August 13, 13
- 67. Random Projections 2) iterate over sequence MAQDQGEKENPMRELRIRKL 13 Emit a “1” ......QDKQDK 1 Tuesday, August 13, 13
- 68. Random Projections 3) repeat for all trigrams MAQDQGEKENPMRELRIRKL .............................................. 0CVV ......QDKQDK 1 Tuesday, August 13, 13
- 69. Random Projections 3) repeat for all trigrams MAQDQGEKENPMRELRIRKL .............................................. 0 ...........QED 1 ..........................MRE 1 CVV QED MRE ......QDKQDK 1 Tuesday, August 13, 13
- 71. 101101000101000101 Observation#1 Each bit represents a fuzzy trigram evaluation “QDK” Tuesday, August 13, 13
- 72. 101101000101000101 Observation#2 Each sequence is compressed to k bits Titin34,350 residues Tuesday, August 13, 13
- 73. 101101000101000101 Observation#3 Similar sequences share similar bitmaps 100101000101000101 Tuesday, August 13, 13
- 75. 101101000101000101 Observation#4 Output index values as tokens 001 003 Tuesday, August 13, 13
- 77. Observation#5 Term dictionary compressed to k terms Cacheable! Tuesday, August 13, 13
- 78. query: filtered: query: match: query: “MAQDQGEKENPMRELRIRKL” min_should_match: 20% analyzer: ngram3 filter: query: match: query: “MAQDQGEKENPMRELRIRKL” min_should_match: 60% analyzer: lsh rescore: smith_waterman: query: “MAQDQGEKENPMRELRIRKL” LSH query Tuesday, August 13, 13
- 79. query: filtered: query: match: query: “MAQDQGEKENPMRELRIRKL” min_should_match: 20% analyzer: ngram3 filter: query: match: query: [0x01, 0x03, 0x16] min_should_match: 60% analyzer: lsh rescore: smith_waterman: query: “MAQDQGEKENPMRELRIRKL” LSH query Tuesday, August 13, 13
- 81. Probabilistic Slower indexing speed Many parameters to tune Tuesday, August 13, 13