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Developing and Using Special Purpose Hidden Markov Model Databases Developing and Using Special Purpose Hidden Markov Model Data DevelopingDeveloping andand UsingUsing SpecialSpecial PurposePurpose HiddenHidden MarkovMarkov ModelModel DatabasesDatabases Martin Gollery Associate Director of Bioinformatics University of Nevada, Reno [email protected] TodayToday’’ss TutorialTutorial • Instructor: Martin Gollery • Associate Director of Bioinformatics, University of Nevada, Reno • Consultant to several organizations • Formerly with TimeLogic • Developed several HMM databases HiddenHidden MarkovMarkov ModelsModels • What HMM’s are • Which HMM programs are commonly used • What HMM databases are available • Why you would use one DB over another • Integrated Resources- InterPro and more • How you can build your own HMM DB • Problems with building your own • Live demonstration HiddenHidden MarkovMarkov ModelsModels-- WhatWhat areare they,they, anyway?anyway? • Statistical description of a protein family's consensus sequence • Conserved regions receive highest scores • Can be seen as a Finite State Machine RepresentationRepresentation ofof FamilyFamily MembersMembers • yciH KDGII • ZyciH KDGVI • VCA0570 KDGDI • HI1225 KNGII • sll0546 KEDCV C D E G I K N V 1 1.0 2 0.6 0.2 0.2 3 0.2 0.8 4 0.2 0.2 0.4 0.2 5 0.8 0.2 RepresentationRepresentation ofof gapsgaps inin FamilyFamily MembersMembers • yciH KDGII • ZyciH KDGVI • VCA0570 KDGDI • HI1225 KNGII • sll0546 KED-V C D E G I K N V - 1 1.0 2 0.6 0.2 0.2 3 0.2 0.8 4 0.2 0.4 0.2 0.2 5 0.8 0.2 ForFor MaximumMaximum sensitivitysensitivity-- C D E G I K N V - 1 1.0 2 0.6 0.2 0.2 3 0.2 0.8 4 0.2 0.4 0.2 0.2 5 0.8 0.2 No residue at any position should have a zero probability, even if it was not seen in the training data. StartStart withwith anan MSAMSA…… • CLUSTAL W (1.7) multiple sequence alignment • yciH KDGVIEIQGDKRDLLKSLLEAKGMKVKLAGG • ZyciH KDGVIEIQGDKRDLLKSLLEAKGMKVKLAGG • VCA0570 KDGDIEIQGDVRDQLKTLLESKGHKVKLAGG • HI1225 KNGIIEIQGEKRDLLKQLLEQKGFKVKLSGG • sll0546 KEDCVEIQGDQREKILAYLLKQGYKAKISGG • PA4840 KDGVVEIQGEHVELLIDELLKRGFKAKKSGG • AF0914 KNGVIELQGNHVNRVKELLIKKGFNPERIKT • *:. :*:**: : : * :* : : HiddenHidden MarkovMarkov ModelsModels • HMMER2.0 • NAME example2 • DESC Small example for demonstration purposes • LENG 31 • ALPH Amino • COM hmmbuild example2 example2.aln • NSEQ 7 • DATE Wed Jan 08 13:33:06 2003 • HMM A C D E F G H I K … • 1 -3217 -3413 -3082 -2664 -4291 -3257 -2104 -4231 3883… • 2 -1938 -3859 2747 1592 -4024 -1857 -1206 -3953 -1455… • 3 -2160 -3144 1834 -953 -4284 3247 -2013 -4362 -2365… • 4 -1255 2750 436 -2789 -1273 -2972 -2049 1510 -2543… • 5 -2035 -1558 -4660 -4320 -2085 -4409 -4229 3081 -4224… • 6 -3264 -3765 -1447 3822 -4535 -2948 -2636 -4814 -2810… • 7 -2423 -1951 -4843 -4395 -1156 -4544 -3680 3291 -4151… • 8 -3220 -3396 -2530 -2667 -3851 -3171 -2735 -4442 -2277… • 9 -3196 -3194 -3915 -4259 -4867 3789 -4005 -5414 -4591… • 10 -1923 -3837 2743 2134 -4005 -1854 -1196 -3929 -1434… • 11 -999 -2164 -952 -353 -2483 -1909 3321 -2139 1730… • 12 -1629 -1909 -2827 -2102 -2279 -2588 -1442 -1012 -488… EmissionEmission ProbabilitiesProbabilities • What is the likelihood that sequence X was emitted by HMM Y? • Likelihood is calculated by adding the probability of each residue at each position, and each of the transition probabilities Plan7Plan7 fromfrom OuterOuter SpaceSpace (Well, from St. Louis, anyway!) HMMHMM’’ss vsvs BLASTBLAST • Position specific scoring vs. general matrix •Example: – dDGVIvIddDKRDLLKSLiEAKkMKVKLAGG – KDGVIEIQGDKRDLLKSLLEAKGMKVKLAGG has 80% BLAST similarity, but misses highly conserved regions • Scoring emphasizes important locations • Clearer score cutoffs • However, it is MUCH slower! HMMHMM programsprograms • HMMer -Sean Eddy, Wash U • SAM - Haussler, UCSC • Wise tools - Birney, EBI • SledgeHMMer - Subramaniam, SDSC • Meta-MEME - Noble & Bailey • PSI-BLAST - NCBI • SPSpfam - Southwest Parallel Software • Ldhmmer - Logical Depth • DeCypherHMM - TimeLogic WhatWhat exactlyexactly dodo youyou want?want? • Are you searching thousands of sequences with one or a few models? • Use hmmsearch • Searching a few sequences with thousands of models? • Use hmmpfam • Thousands of sequences vs. Thousands of models? • Use an accelerator, if you do it very often HMMHMM databasesdatabases • PFAM •TIGRFAM • Superfamily •SMART • Panther • PRED-GPCR HMMHMM databasesdatabases atat thethe CFBCFB •COGfam •KinFam • HydroHMMer • NVfam-pro • NVfam-arc • NVfam-fun • NVfam-pln PFAMPFAM • From Sanger, WashU, KI, INRA • Version 17 has 7868 families • Most widely used HMM database • Good annotation team PFAMPFAM • PFAM-A is hand curated • From high quality multiple Alignments • PFAM-B is built automatically from ProDom • Generated using the Domainer algorithm • ProDom is built from SP/TREMBL PFAMPFAM • Pfam-ls = global alignments • Pfam-fs = local alignments, so that matches may include only part of the model • Both the –ls and –fs versions are local W.R.T. the sequence PFAMPFAM • Note ‘type’ annotation • Labeled TP • Family • Domain • Repeat •Motif TIGRFAMsTIGRFAMs • Available at (www.tigr.org/TIGRFAMs/) • Organized by functional role • Equivalogs: a set of homologous proteins that are conserved with respect to function since their last common ancestor • Equivalog domains: domains of conserved function TIGRFAMsTIGRFAMs • 2453 models in release 4.1 • Complementary to PFAM, so run both • Part of the Comprehensive Microbial Resource (CMR) TIGRFAMsTIGRFAMs TIGRfam and PFAM alignments for Pyruvate carboxylase. The thin line represents the sequence. The bars represent hit regions. SuperFamilySuperFamily • By Julian Gough, formerly MRC, now Riken GSC • www.supfam.org • Provides structural (and hence implied functional) assignments to protein sequences at the superfamily level • Built from SCOP (Structural Classification of Proteins) database, which is built from PDB • Available in HMMer, SAM, and PSI-BLAST formats SuperFamilySuperFamily • 1447 SCOP Superfamilies • Each represented by a group of HMMs • Over 8500 models total • Table provides comparison to GO, Interpro, PFAM SMARTSMART • Simple Modular Architecture Research Tool • Version 3.4 contains 654 HMMs • Emphasis on mobile eukaryotic domains • smart.embl-heidelberg.de • Annotated with respect to phyletic distributions, functional class, tertiary structures and functionally important residues SMARTSMART • Use for signaling domains or extracellular domains • Normal and Genomic mode PREDPRED--GPCRGPCR • Papasaikas et al, U of Athens • 265 HMMs in 67 GPCR families • Based on TiPs Pharmacological classification. • Filters with CAST • signatures regularly updated • Entire system redone each year PREDPRED--GPCRGPCR webserverwebserver PantherPanther • Protein ANalysis THrough Evolutionary Relationships • Family and subfamily: families are evolutionarily related proteins; subfamilies are related proteins with the same function • Molecular function: the function of the protein by itself or with directly interacting proteins at a biochemical level, e.g. a protein kinase • Biological process: the function of the protein in the context of a larger network of proteins that interact to accomplish a process at the level of the cell or organism, e.g. mitosis. • Pathway: similar to biological process, but a pathway also explicitly specifies the relationships between the interacting molecules. PantherPanther •(Thomas et al., Genome Research 2003; Mi et al. NAR 2005) • 6683 protein families • 31,705 functionally distinct protein subfamilies. PantherPanther • Due to the size, searches could be slow • First, BLAST against consensus seqs • Then, search against models represented by those hits • With an accelerator, you don’t have to do that… PantherPanther • So- how does it perform? • I took 3451 Arabidopsis proteins with no hit to PFAM, Superfamily, SMART or TIGRfam • Ran it against Panther • Found 160 significant hits! COGCOG--HMMsHMMs • Clusters of Orthologous Groups of proteins • www.ncbi.nlm.nih.gov/cog/ • Each COG is from at least 3 lineages • Ancient conserved domain • 4873 alignments available • Alignments from NCBI, HMMs from me at [email protected] CDDCDD • Conserved Domain Database (NCBI) • Psi-BLAST profiles are similar to HMMs • 10991 PSSMs - SMART + COG +KOG+ Pfam+CD • Runs with RPS-BLAST • Much faster searches KinFamKinFam • Kinfam- models represent 53 different classes of PKs • Assigns Kinase Class and Group • Based on Hanks’ classification scheme • Database is small, so searches are fast KinFamKinFam • Categorizes Kinase data • Available for download from bioinformatics.unr.edu RANK SCORE QF TARGET|ACCESSION E_VALUE DESCRIPTION 1 852.93 1 KinFam||ptkgrp15 9.3e-256 Fibroblast GF recept 2 479.14 1 KinFam||ptkgrp14 3.1e-143 Platelet derived GF 3 423.33 1 KinFam||ptkother 1.9e-126 Other membrane-span HydroHmmerHydroHmmer • Hydrohmmer finds LEAs, other hydrophilin classes • Small target size makes for very fast searches NVFAMsNVFAMs • HMM’s reflect the training data • Specific training sets provide better results • So… use Archaeal data to study Archaeons, Fungal data to study Fungi, etc. • Designed for use with PFAM, not stand alone • Recent redesign, name change NVFAMsNVFAMs • NVFAM-pro used to study E. faecalis • Demonstrated higher scores, better aligns • However, PFAM had more total hits • P.falciparum used as negative control • PFAM showed better scores, aligns as predicted • Automated design by Garrett Taylor- scripts are available! • Contact me for input, collaboration, or help to build your own WhichWhich databasedatabase toto use?use? OneOne ComparisonComparison TestTest-- (Your(Your resultsresults maymay varyvary……)) • Compare 563 I. pini sequences to COGhmm, PFAM,
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