# This document is generated with a version of rd2html (part of Hiki) # # rd2 Tutorial.rd # # or with style sheet: # # rd2 -r rd/rd2html-lib.rb --with-css=bioruby.css Tutorial.rd > Tutorial.rd.html # # in Debian: # # rd2 -r rd/rd2html-lib --with-css="../lib/bio/shell/rails/vendor/plugins/bioruby/generators/bioruby/templates/bioruby.css" Tutorial.rd > Tutorial.rd.html # # A common problem is tabs in the text file! TABs are not allowed. # # To add tests run Toshiaki's bioruby shell and paste in the query plus # results. # # To run the embedded Ruby doctests you can use the rubydoctest tool, though # it needs a little conversion. Like: # # cat Tutorial.rd | sed -e "s,bioruby>,>>," | sed "s,==>,=>," > Tutorial.rd.tmp # rubydoctest Tutorial.rd.tmp # # alternatively, the Ruby way is # # ruby -p -e '$_.sub!(/bioruby\>/, ">>"); $_.sub!(/\=\=\>/, "=>")' Tutorial.rd > Tutorial.rd.tmp # rubydoctest Tutorial.rd.tmp # # Rubydoctest is useful to verify an example in this document (still) works # # bioruby> $: << '../lib' # make sure rubydoctest finds bioruby/lib =begin #doctest Testing bioruby = BioRuby Tutorial * Copyright (C) 2001-2003 KATAYAMA Toshiaki * Copyright (C) 2005-2011 Pjotr Prins, Naohisa Goto and others This document was last modified: 2011/10/14 Current editor: Michael O'Keefe The latest version resides in the GIT source code repository: ./doc/(()). == Introduction This is a tutorial for using Bioruby. A basic knowledge of Ruby is required. If you want to know more about the programming language, we recommend the latest Ruby book (()) by Dave Thomas and Andy Hunt - the first edition can be read online (()). For BioRuby you need to install Ruby and the BioRuby package on your computer You can check whether Ruby is installed on your computer and what version it has with the % ruby -v command. You should see something like: ruby 1.9.2p290 (2011-07-09 revision 32553) [i686-linux] If you see no such thing you'll have to install Ruby using your installation manager. For more information see the (()) website. With Ruby download and install Bioruby using the links on the (()) website. The recommended installation is via RubyGems: gem install bio See also the Bioruby (()). A lot of BioRuby's documentation exists in the source code and unit tests. To really dive in you will need the latest source code tree. The embedded rdoc documentation can be viewed online at (()). But first lets start! == Trying Bioruby Bioruby comes with its own shell. After unpacking the sources run one of the following commands: bioruby or, from the source tree cd bioruby ruby -I lib bin/bioruby and you should see a prompt bioruby> Now test the following: bioruby> require 'bio' bioruby> seq = Bio::Sequence::NA.new("atgcatgcaaaa") ==> "atgcatgcaaaa" bioruby> seq.complement ==> "ttttgcatgcat" See the the Bioruby shell section below for more tweaking. If you have trouble running examples also check the section below on trouble shooting. You can also post a question to the mailing list. BioRuby developers usually try to help. == Working with nucleic / amino acid sequences (Bio::Sequence class) The Bio::Sequence class allows the usual sequence transformations and translations. In the example below the DNA sequence "atgcatgcaaaa" is converted into the complemental strand and spliced into a subsequence; next, the nucleic acid composition is calculated and the sequence is translated into the amino acid sequence, the molecular weight calculated, and so on. When translating into amino acid sequences, the frame can be specified and optionally the codon table selected (as defined in codontable.rb). bioruby> seq = Bio::Sequence::NA.new("atgcatgcaaaa") ==> "atgcatgcaaaa" # complemental sequence (Bio::Sequence::NA object) bioruby> seq.complement ==> "ttttgcatgcat" bioruby> seq.subseq(3,8) # gets subsequence of positions 3 to 8 (starting from 1) ==> "gcatgc" bioruby> seq.gc_percent ==> 33 bioruby> seq.composition ==> {"a"=>6, "c"=>2, "g"=>2, "t"=>2} bioruby> seq.translate ==> "MHAK" bioruby> seq.translate(2) # translate from frame 2 ==> "CMQ" bioruby> seq.translate(1,11) # codon table 11 ==> "MHAK" bioruby> seq.translate.codes ==> ["Met", "His", "Ala", "Lys"] bioruby> seq.translate.names ==> ["methionine", "histidine", "alanine", "lysine"] bioruby> seq.translate.composition ==> {"K"=>1, "A"=>1, "M"=>1, "H"=>1} bioruby> seq.translate.molecular_weight ==> 485.605 bioruby> seq.complement.translate ==> "FCMH" get a random sequence with the same NA count: bioruby> counts = {'a'=>seq.count('a'),'c'=>seq.count('c'),'g'=>seq.count('g'),'t'=>seq.count('t')} ==> {"a"=>6, "c"=>2, "g"=>2, "t"=>2} bioruby!> randomseq = Bio::Sequence::NA.randomize(counts) ==!> "aaacatgaagtc" bioruby!> print counts a6c2g2t2 bioruby!> p counts {"a"=>6, "c"=>2, "g"=>2, "t"=>2} The p, print and puts methods are standard Ruby ways of outputting to the screen. If you want to know more about standard Ruby commands you can use the 'ri' command on the command line (or the help command in Windows). For example % ri puts % ri p % ri File.open Nucleic acid sequence are members of the Bio::Sequence::NA class, and amino acid sequence are members of the Bio::Sequence::AA class. Shared methods are in the parent Bio::Sequence class. As Bio::Sequence inherits Ruby's String class, you can use String class methods. For example, to get a subsequence, you can not only use subseq(from, to) but also String#[]. Please take note that the Ruby's string's are base 0 - i.e. the first letter has index 0, for example: bioruby> s = 'abc' ==> "abc" bioruby> s[0].chr ==> "a" bioruby> s[0..1] ==> "ab" So when using String methods, you should subtract 1 from positions conventionally used in biology. (subseq method will throw an exception if you specify positions smaller than or equal to 0 for either one of the "from" or "to".) The window_search(window_size, step_size) method shows a typical Ruby way of writing concise and clear code using 'closures'. Each sliding window creates a subsequence which is supplied to the enclosed block through a variable named +s+. * Show average percentage of GC content for 20 bases (stepping the default one base at a time): bioruby> seq = Bio::Sequence::NA.new("atgcatgcaattaagctaatcccaattagatcatcccgatcatcaaaaaaaaaa") ==> "atgcatgcaattaagctaatcccaattagatcatcccgatcatcaaaaaaaaaa" bioruby> a=[]; seq.window_search(20) { |s| a.push s.gc_percent } bioruby> a ==> [30, 35, 40, 40, 35, 35, 35, 30, 25, 30, 30, 30, 35, 35, 35, 35, 35, 40, 45, 45, 45, 45, 40, 35, 40, 40, 40, 40, 40, 35, 35, 35, 30, 30, 30] Since the class of each subsequence is the same as original sequence (Bio::Sequence::NA or Bio::Sequence::AA or Bio::Sequence), you can use all methods on the subsequence. For example, * Shows translation results for 15 bases shifting a codon at a time bioruby> a = [] bioruby> seq.window_search(15, 3) { | s | a.push s.translate } bioruby> a ==> ["MHAIK", "HAIKL", "AIKLI", "IKLIP", "KLIPI", "LIPIR", "IPIRS", "PIRSS", "IRSSR", "RSSRS", "SSRSS", "SRSSK", "RSSKK", "SSKKK"] Finally, the window_search method returns the last leftover subsequence. This allows for example * Divide a genome sequence into sections of 10000bp and output FASTA formatted sequences (line width 60 chars). The 1000bp at the start and end of each subsequence overlapped. At the 3' end of the sequence the leftover is also added: i = 1 textwidth=60 remainder = seq.window_search(10000, 9000) do |s| puts s.to_fasta("segment #{i}", textwidth) i += 1 end if remainder puts remainder.to_fasta("segment #{i}", textwidth) end If you don't want the overlapping window, set window size and stepping size to equal values. Other examples * Count the codon usage bioruby> codon_usage = Hash.new(0) bioruby> seq.window_search(3, 3) { |s| codon_usage[s] += 1 } bioruby> codon_usage ==> {"cat"=>1, "aaa"=>3, "cca"=>1, "att"=>2, "aga"=>1, "atc"=>1, "cta"=>1, "gca"=>1, "cga"=>1, "tca"=>3, "aag"=>1, "tcc"=>1, "atg"=>1} * Calculate molecular weight for each 10-aa peptide (or 10-nt nucleic acid) bioruby> a = [] bioruby> seq.window_search(10, 10) { |s| a.push s.molecular_weight } bioruby> a ==> [3096.2062, 3086.1962, 3056.1762, 3023.1262, 3073.2262] In most cases, sequences are read from files or retrieved from databases. For example: require 'bio' input_seq = ARGF.read # reads all files in arguments my_naseq = Bio::Sequence::NA.new(input_seq) my_aaseq = my_naseq.translate puts my_aaseq Save the program above as na2aa.rb. Prepare a nucleic acid sequence described below and save it as my_naseq.txt: gtggcgatctttccgaaagcgatgactggagcgaagaaccaaagcagtgacatttgtctg atgccgcacgtaggcctgataagacgcggacagcgtcgcatcaggcatcttgtgcaaatg tcggatgcggcgtga na2aa.rb translates a nucleic acid sequence to a protein sequence. For example, translates my_naseq.txt: % ruby na2aa.rb my_naseq.txt or use a pipe! % cat my_naseq.txt|ruby na2aa.rb Outputs VAIFPKAMTGAKNQSSDICLMPHVGLIRRGQRRIRHLVQMSDAA* You can also write this, a bit fancifully, as a one-liner script. % ruby -r bio -e 'p Bio::Sequence::NA.new($<.read).translate' my_naseq.txt In the next section we will retrieve data from databases instead of using raw sequence files. One generic example of the above can be found in ./sample/na2aa.rb. == Parsing GenBank data (Bio::GenBank class) We assume that you already have some GenBank data files. (If you don't, download some .seq files from ftp://ftp.ncbi.nih.gov/genbank/) As an example we will fetch the ID, definition and sequence of each entry from the GenBank format and convert it to FASTA. This is also an example script in the BioRuby distribution. A first attempt could be to use the Bio::GenBank class for reading in the data: #!/usr/bin/env ruby require 'bio' # Read all lines from STDIN split by the GenBank delimiter while entry = gets(Bio::GenBank::DELIMITER) gb = Bio::GenBank.new(entry) # creates GenBank object print ">#{gb.accession} " # Accession puts gb.definition # Definition puts gb.naseq # Nucleic acid sequence # (Bio::Sequence::NA object) end But that has the disadvantage the code is tied to GenBank input. A more generic method is to use Bio::FlatFile which allows you to use different input formats: #!/usr/bin/env ruby require 'bio' ff = Bio::FlatFile.new(Bio::GenBank, ARGF) ff.each_entry do |gb| definition = "#{gb.accession} #{gb.definition}" puts gb.naseq.to_fasta(definition, 60) end For example, in turn, reading FASTA format files: #!/usr/bin/env ruby require 'bio' ff = Bio::FlatFile.new(Bio::FastaFormat, ARGF) ff.each_entry do |f| puts "definition : " + f.definition puts "nalen : " + f.nalen.to_s puts "naseq : " + f.naseq end In the above two scripts, the first arguments of Bio::FlatFile.new are database classes of BioRuby. This is expanded on in a later section. Again another option is to use the Bio::DB.open class: #!/usr/bin/env ruby require 'bio' ff = Bio::GenBank.open("gbvrl1.seq") ff.each_entry do |gb| definition = "#{gb.accession} #{gb.definition}" puts gb.naseq.to_fasta(definition, 60) end Next, we are going to parse the GenBank 'features', which is normally very complicated: #!/usr/bin/env ruby require 'bio' ff = Bio::FlatFile.new(Bio::GenBank, ARGF) # iterates over each GenBank entry ff.each_entry do |gb| # shows accession and organism puts "# #{gb.accession} - #{gb.organism}" # iterates over each element in 'features' gb.features.each do |feature| position = feature.position hash = feature.assoc # put into Hash # skips the entry if "/translation=" is not found next unless hash['translation'] # collects gene name and so on and joins it into a string gene_info = [ hash['gene'], hash['product'], hash['note'], hash['function'] ].compact.join(', ') # shows nucleic acid sequence puts ">NA splicing('#{position}') : #{gene_info}" puts gb.naseq.splicing(position) # shows amino acid sequence translated from nucleic acid sequence puts ">AA translated by splicing('#{position}').translate" puts gb.naseq.splicing(position).translate # shows amino acid sequence in the database entry (/translation=) puts ">AA original translation" puts hash['translation'] end end * Note: In this example Feature#assoc method makes a Hash from a feature object. It is useful because you can get data from the hash by using qualifiers as keys. But there is a risk some information is lost when two or more qualifiers are the same. Therefore an Array is returned by Feature#feature. Bio::Sequence#splicing splices subsequences from nucleic acid sequences according to location information used in GenBank, EMBL and DDBJ. When the specified translation table is different from the default (universal), or when the first codon is not "atg" or the protein contains selenocysteine, the two amino acid sequences will differ. The Bio::Sequence#splicing method takes not only DDBJ/EMBL/GenBank feature style location text but also Bio::Locations object. For more information about location format and Bio::Locations class, see bio/location.rb. * Splice according to location string used in a GenBank entry naseq.splicing('join(2035..2050,complement(1775..1818),13..345') * Generate Bio::Locations object and pass the splicing method locs = Bio::Locations.new('join((8298.8300)..10206,1..855)') naseq.splicing(locs) You can also use this splicing method for amino acid sequences (Bio::Sequence::AA objects). * Splicing peptide from a protein (e.g. signal peptide) aaseq.splicing('21..119') === More databases Databases in BioRuby are essentially accessed like that of GenBank with classes like Bio::GenBank, Bio::KEGG::GENES. A full list can be found in the ./lib/bio/db directory of the BioRuby source tree. In many cases the Bio::DatabaseClass acts as a factory pattern and recognises the database type automatically - returning a parsed object. For example using Bio::FlatFile class as described above. The first argument of the Bio::FlatFile.new is database class name in BioRuby (such as Bio::GenBank, Bio::KEGG::GENES and so on). ff = Bio::FlatFile.new(Bio::DatabaseClass, ARGF) Isn't it wonderful that Bio::FlatFile automagically recognizes each database class? #!/usr/bin/env ruby require 'bio' ff = Bio::FlatFile.auto(ARGF) ff.each_entry do |entry| p entry.entry_id # identifier of the entry p entry.definition # definition of the entry p entry.seq # sequence data of the entry end An example that can take any input, filter using a regular expression and output to a FASTA file can be found in sample/any2fasta.rb. With this technique it is possible to write a Unix type grep/sort pipe for sequence information. One example using scripts in the BIORUBY sample folder: fastagrep.rb '/At|Dm/' database.seq | fastasort.rb greps the database for Arabidopsis and Drosophila entries and sorts the output to FASTA. Other methods to extract specific data from database objects can be different between databases, though some methods are common (see the guidelines for common methods in bio/db.rb). * entry_id --> gets ID of the entry * definition --> gets definition of the entry * reference --> gets references as Bio::Reference object * organism --> gets species * seq, naseq, aaseq --> returns sequence as corresponding sequence object Refer to the documents of each database to find the exact naming of the included methods. In general, BioRuby uses the following conventions: when a method name is plural, the method returns some object as an Array. For example, some classes have a "references" method which returns multiple Bio::Reference objects as an Array. And some classes have a "reference" method which returns a single Bio::Reference object. === Alignments (Bio::Alignment) The Bio::Alignment class in bio/alignment.rb is a container class like Ruby's Hash and Array classes and BioPerl's Bio::SimpleAlign. A very simple example is: bioruby> seqs = [ 'atgca', 'aagca', 'acgca', 'acgcg' ] bioruby> seqs = seqs.collect{ |x| Bio::Sequence::NA.new(x) } # creates alignment object bioruby> a = Bio::Alignment.new(seqs) bioruby> a.consensus ==> "a?gc?" # shows IUPAC consensus p a.consensus_iupac # ==> "ahgcr" # iterates over each seq a.each { |x| p x } # ==> # "atgca" # "aagca" # "acgca" # "acgcg" # iterates over each site a.each_site { |x| p x } # ==> # ["a", "a", "a", "a"] # ["t", "a", "c", "c"] # ["g", "g", "g", "g"] # ["c", "c", "c", "c"] # ["a", "a", "a", "g"] # doing alignment by using CLUSTAL W. # clustalw command must be installed. factory = Bio::ClustalW.new a2 = a.do_align(factory) Read a ClustalW or Muscle 'ALN' alignment file: bioruby> aln = Bio::ClustalW::Report.new(File.read('../test/data/clustalw/example1.aln')) bioruby> aln.header ==> "CLUSTAL 2.0.9 multiple sequence alignment" Fetch a sequence: bioruby> seq = aln.get_sequence(1) bioruby> seq.definition ==> "gi|115023|sp|P10425|" Get a partial sequence: bioruby> seq.to_s[60..120] ==> "LGYFNG-EAVPSNGLVLNTSKGLVLVDSSWDNKLTKELIEMVEKKFQKRVTDVIITHAHAD" Show the full alignment residue match information for the sequences in the set: bioruby> aln.match_line[60..120] ==> " . **. . .. ::*: . * : : . .: .* * *" Return a Bio::Alignment object: bioruby> aln.alignment.consensus[60..120] ==> "???????????SN?????????????D??????????L??????????????????H?H?D" == Restriction Enzymes (Bio::RE) BioRuby has extensive support for restriction enzymes (REs). It contains a full library of commonly used REs (from REBASE) which can be used to cut single stranded RNA or double stranded DNA into fragments. To list all enzymes: rebase = Bio::RestrictionEnzyme.rebase rebase.each do |enzyme_name, info| p enzyme_name end and to cut a sequence with an enzyme follow up with: res = seq.cut_with_enzyme('EcoRII', {:max_permutations => 0}, {:view_ranges => true}) if res.kind_of? Symbol #error err = Err.find_by_code(res.to_s) unless err err = Err.new(:code => res.to_s) end end res.each do |frag| em = EnzymeMatch.new em.p_left = frag.p_left em.p_right = frag.p_right em.c_left = frag.c_left em.c_right = frag.c_right em.err = nil em.enzyme = ar_enz em.sequence = ar_seq p em end == Sequence homology search by using the FASTA program (Bio::Fasta) Let's start with a query.pep file which contains a sequence in FASTA format. In this example we are going to execute a homology search from a remote internet site or on your local machine. Note that you can use the ssearch program instead of fasta when you use it in your local machine. === using FASTA in local machine Install the fasta program on your machine (the command name looks like fasta34. FASTA can be downloaded from ftp://ftp.virginia.edu/pub/fasta/). First, you must prepare your FASTA-formatted database sequence file target.pep and FASTA-formatted query.pep. #!/usr/bin/env ruby require 'bio' # Creates FASTA factory object ("ssearch" instead of # "fasta34" can also work) factory = Bio::Fasta.local('fasta34', ARGV.pop) (EDITOR's NOTE: not consistent pop command) ff = Bio::FlatFile.new(Bio::FastaFormat, ARGF) # Iterates over each entry. the variable "entry" is a # Bio::FastaFormat object: ff.each do |entry| # shows definition line (begins with '>') to the standard error output $stderr.puts "Searching ... " + entry.definition # executes homology search. Returns Bio::Fasta::Report object. report = factory.query(entry) # Iterates over each hit report.each do |hit| # If E-value is smaller than 0.0001 if hit.evalue < 0.0001 # shows identifier of query and hit, E-value, start and # end positions of homologous region print "#{hit.query_id} : evalue #{hit.evalue}\t#{hit.target_id} at " p hit.lap_at end end end We named above script f_search.rb. You can execute it as follows: % ./f_search.rb query.pep target.pep > f_search.out In above script, the variable "factory" is a factory object for executing FASTA many times easily. Instead of using Fasta#query method, Bio::Sequence#fasta method can be used. seq = ">test seq\nYQVLEEIGRGSFGSVRKVIHIPTKKLLVRKDIKYGHMNSKE" seq.fasta(factory) When you want to add options to FASTA commands, you can set the third argument of the Bio::Fasta.local method. For example, the following sets ktup to 1 and gets a list of the top 10 hits: factory = Bio::Fasta.local('fasta34', 'target.pep', '-b 10') factory.ktup = 1 Bio::Fasta#query returns a Bio::Fasta::Report object. We can get almost all information described in FASTA report text with the Report object. For example, getting information for hits: report.each do |hit| puts hit.evalue # E-value puts hit.sw # Smith-Waterman score (*) puts hit.identity # % identity puts hit.overlap # length of overlapping region puts hit.query_id # identifier of query sequence puts hit.query_def # definition(comment line) of query sequence puts hit.query_len # length of query sequence puts hit.query_seq # sequence of homologous region puts hit.target_id # identifier of hit sequence puts hit.target_def # definition(comment line) of hit sequence puts hit.target_len # length of hit sequence puts hit.target_seq # hit of homologous region of hit sequence puts hit.query_start # start position of homologous # region in query sequence puts hit.query_end # end position of homologous region # in query sequence puts hit.target_start # start posiotion of homologous region # in hit(target) sequence puts hit.target_end # end position of homologous region # in hit(target) sequence puts hit.lap_at # array of above four numbers end Most of above methods are common to the Bio::Blast::Report described below. Please refer to the documentation of the Bio::Fasta::Report class for FASTA-specific details. If you need the original output text of FASTA program you can use the "output" method of the factory object after the "query" method. report = factory.query(entry) puts factory.output === using FASTA from a remote internet site * Note: Currently, only GenomeNet (fasta.genome.jp) is supported. check the class documentation for updates. For accessing a remote site the Bio::Fasta.remote method is used instead of Bio::Fasta.local. When using a remote method, the databases available may be limited, but, otherwise, you can do the same things as with a local method. Available databases in GenomeNet: * Protein database * nr-aa, genes, vgenes.pep, swissprot, swissprot-upd, pir, prf, pdbstr * Nucleic acid database * nr-nt, genbank-nonst, gbnonst-upd, dbest, dbgss, htgs, dbsts, embl-nonst, embnonst-upd, genes-nt, genome, vgenes.nuc Select the databases you require. Next, give the search program from the type of query sequence and database. * When query is an amino acid sequence * When protein database, program is "fasta". * When nucleic database, program is "tfasta". * When query is a nucleic acid sequence * When nucleic database, program is "fasta". * (When protein database, the search would fail.) For example, run: program = 'fasta' database = 'genes' factory = Bio::Fasta.remote(program, database) and try out the same commands as with the local search shown earlier. == Homology search by using BLAST (Bio::Blast class) The BLAST interface is very similar to that of FASTA and both local and remote execution are supported. Basically replace above examples Bio::Fasta with Bio::Blast! For example the BLAST version of f_search.rb is: # create BLAST factory object factory = Bio::Blast.local('blastp', ARGV.pop) For remote execution of BLAST in GenomeNet, Bio::Blast.remote is used. The parameter "program" is different from FASTA - as you can expect: * When query is a amino acid sequence * When protein database, program is "blastp". * When nucleic database, program is "tblastn". * When query is a nucleic acid sequence * When protein database, program is "blastx" * When nucleic database, program is "blastn". * ("tblastx" for six-frame search.) Bio::BLAST uses "-m 7" XML output of BLAST by default when either XMLParser or REXML (both of them are XML parser libraries for Ruby - of the two XMLParser is the fastest) is installed on your computer. In Ruby version 1.8.0 or later, REXML is bundled with Ruby's distribution. When no XML parser library is present, Bio::BLAST uses "-m 8" tabular deliminated format. Available information is limited with the "-m 8" format so installing an XML parser is recommended. Again, the methods in Bio::Fasta::Report and Bio::Blast::Report (and Bio::Fasta::Report::Hit and Bio::Blast::Report::Hit) are similar. There are some additional BLAST methods, for example, bit_score and midline. report.each do |hit| puts hit.bit_score puts hit.query_seq puts hit.midline puts hit.target_seq puts hit.evalue puts hit.identity puts hit.overlap puts hit.query_id puts hit.query_def puts hit.query_len puts hit.target_id puts hit.target_def puts hit.target_len puts hit.query_start puts hit.query_end puts hit.target_start puts hit.target_end puts hit.lap_at end For simplicity and API compatibility, some information such as score is extracted from the first Hsp (High-scoring Segment Pair). Check the documentation for Bio::Blast::Report to see what can be retrieved. For now suffice to say that Bio::Blast::Report has a hierarchical structure mirroring the general BLAST output stream: * In a Bio::Blast::Report object, @iterations is an array of Bio::Blast::Report::Iteration objects. * In a Bio::Blast::Report::Iteration object, @hits is an array of Bio::Blast::Report::Hits objects. * In a Bio::Blast::Report::Hits object, @hsps is an array of Bio::Blast::Report::Hsp objects. See bio/appl/blast.rb and bio/appl/blast/*.rb for more information. === Parsing existing BLAST output files When you already have BLAST output files and you want to parse them, you can directly create Bio::Blast::Report objects without the Bio::Blast factory object. For this purpose use Bio::Blast.reports, which supports the "-m 0" default and "-m 7" XML type output format. * For example: blast_version = nil; result = [] Bio::Blast.reports(File.new("../test/data/blast/blastp-multi.m7")) do |report| blast_version = report.version report.iterations.each do |itr| itr.hits.each do |hit| result.push hit.target_id end end end blast_version # ==> "blastp 2.2.18 [Mar-02-2008]" result # ==> ["BAB38768", "BAB38768", "BAB38769", "BAB37741"] * another example: require 'bio' Bio::Blast.reports(ARGF) do |report| puts "Hits for " + report.query_def + " against " + report.db report.each do |hit| print hit.target_id, "\t", hit.evalue, "\n" if hit.evalue < 0.001 end end Save the script as hits_under_0.001.rb and to process BLAST output files *.xml, you can run it with: % ruby hits_under_0.001.rb *.xml Sometimes BLAST XML output may be wrong and can not be parsed. Check whether blast is version 2.2.5 or later. See also blast --help. Bio::Blast loads the full XML file into memory. If this causes a problem you can split the BLAST XML file into smaller chunks using XML-Twig. An example can be found in (()). === Add remote BLAST search sites Note: this section is an advanced topic Here a more advanced application for using BLAST sequence homology search services. BioRuby currently only supports GenomeNet. If you want to add other sites, you must write the following: * the calling CGI (command-line options must be processed for the site). * make sure you get BLAST output text as supported format by BioRuby (e.g. "-m 8", "-m 7" or default("-m 0")). In addition, you must write a private class method in Bio::Blast named "exec_MYSITE" to get query sequence and to pass the result to Bio::Blast::Report.new(or Bio::Blast::Default::Report.new): factory = Bio::Blast.remote(program, db, option, 'MYSITE') When you write above routines, please send them to the BioRuby project, and they may be included in future releases. == Generate a reference list using PubMed (Bio::PubMed) Nowadays using NCBI E-Utils is recommended. Use Bio::PubMed.esearch and Bio::PubMed.efetch. #!/usr/bin/env ruby require 'bio' # NCBI announces that queries without email address will return error # after June 2010. When you modify the script, please enter your email # address instead of the staff's. Bio::NCBI.default_email = 'staff@bioruby.org' keywords = ARGV.join(' ') options = { 'maxdate' => '2003/05/31', 'retmax' => 1000, } entries = Bio::PubMed.esearch(keywords, options) Bio::PubMed.efetch(entries).each do |entry| medline = Bio::MEDLINE.new(entry) reference = medline.reference puts reference.bibtex end The script works same as pmsearch.rb. But, by using NCBI E-Utils, more options are available. For example published dates to search and maximum number of hits to show results can be specified. See the (()) for more details. === More about BibTeX In this section, we explain the simple usage of TeX for the BibTeX format bibliography list collected by above scripts. For example, to save BibTeX format bibliography data to a file named genoinfo.bib. % ./pmfetch.rb 10592173 >> genoinfo.bib % ./pmsearch.rb genome bioinformatics >> genoinfo.bib The BibTeX can be used with Tex or LaTeX to form bibliography information with your journal article. For more information on using BibTex see (()). A quick example: Save this to hoge.tex: \documentclass{jarticle} \begin{document} \bibliographystyle{plain} foo bar KEGG database~\cite{PMID:10592173} baz hoge fuga. \bibliography{genoinfo} \end{document} Then, % latex hoge % bibtex hoge # processes genoinfo.bib % latex hoge # creates bibliography list % latex hoge # inserts correct bibliography reference Now, you get hoge.dvi and hoge.ps - the latter of which can be viewed with any Postscript viewer. === Bio::Reference#bibitem When you don't want to create a bib file, you can use Bio::Reference#bibitem method instead of Bio::Reference#bibtex. In the above pmfetch.rb and pmsearch.rb scripts, change puts reference.bibtex to puts reference.bibitem Output documents should be bundled in \begin{thebibliography} and \end{thebibliography}. Save the following to hoge.tex \documentclass{jarticle} \begin{document} foo bar KEGG database~\cite{PMID:10592173} baz hoge fuga. \begin{thebibliography}{00} \bibitem{PMID:10592173} Kanehisa, M., Goto, S. KEGG: kyoto encyclopedia of genes and genomes., {\em Nucleic Acids Res}, 28(1):27--30, 2000. \end{thebibliography} \end{document} and run % latex hoge # creates bibliography list % latex hoge # inserts corrent bibliography reference = OBDA OBDA (Open Bio Database Access) is a standardized method of sequence database access developed by the Open Bioinformatics Foundation. It was created during the BioHackathon by BioPerl, BioJava, BioPython, BioRuby and other projects' members (2002). * BioRegistry (Directory) * Mechanism to specify how and where to retrieve sequence data for each database. * BioFlat * Flatfile indexing by using binary tree or BDB(Berkeley DB). * BioFetch * Server-client model for getting entry from database via http. * BioSQL * Schemas to store sequence data to relational databases such as MySQL and PostgreSQL, and methods to retrieve entries from the database. This tutorial only gives a quick overview of OBDA. Check out (()) for more extensive details. == BioRegistry BioRegistry allows for locating retrieval methods and database locations through configuration files. The priorities are * The file specified with method's parameter * ~/.bioinformatics/seqdatabase.ini * /etc/bioinformatics/seqdatabase.ini * http://www.open-bio.org/registry/seqdatabase.ini Note that the last locaation refers to www.open-bio.org and is only used when all local configulation files are not available. In the current BioRuby implementation all local configulation files are read. For databases with the same name settings encountered first are used. This means that if you don't like some settings of a database in the system's global configuration file (/etc/bioinformatics/seqdatabase.ini), you can easily override them by writing settings to ~/.bioinformatics/seqdatabase.ini. The syntax of the configuration file is called a stanza format. For example [DatabaseName] protocol=ProtocolName location=ServerName You can write a description like the above entry for every database. The database name is a local label for yourself, so you can name it freely and it can differ from the name of the actual databases. In the actual specification of BioRegistry where there are two or more settings for a database of the same name, it is proposed that connection to the database is tried sequentially with the order written in configuration files. However, this has not (yet) been implemented in BioRuby. In addition, for some protocols, you must set additional options other than locations (e.g. user name for MySQL). In the BioRegistory specification, current available protocols are: * index-flat * index-berkeleydb * biofetch * biosql * bsane-corba * xembl In BioRuby, you can use index-flat, index-berkleydb, biofetch and biosql. Note that the BioRegistry specification sometimes gets updated and BioRuby does not always follow quickly. Here is an example. It creates a Bio::Registry object and reads the configuration files: reg = Bio::Registry.new # connects to the database "genbank" serv = reg.get_database('genbank') # gets entry of the ID entry = serv.get_by_id('AA2CG') The variable "serv" is a server object corresponding to the settings written in the configuration files. The class of the object is one of Bio::SQL, Bio::Fetch, and so on. Note that Bio::Registry#get_database("name") returns nil if no database is found. After that, you can use the get_by_id method and some specific methods. Please refer to the sections below for more information. == BioFlat BioFlat is a mechanism to create index files of flat files and to retrieve these entries fast. There are two index types. index-flat is a simple index performing binary search without using any external libraries of Ruby. index-berkeleydb uses Berkeley DB for indexing - but requires installing bdb on your computer, as well as the BDB Ruby package. To create the index itself, you can use br_bioflat.rb command bundled with BioRuby. % br_bioflat.rb --makeindex database_name [--format data_format] filename... The format can be omitted because BioRuby has autodetection. If that doesn't work, you can try specifying the data format as the name of a BioRuby database class. Search and retrieve data from database: % br_bioflat.rb database_name identifier For example, to create an index of GenBank files gbbct*.seq and get the entry from the database: % br_bioflat.rb --makeindex my_bctdb --format GenBank gbbct*.seq % br_bioflat.rb my_bctdb A16STM262 If you have Berkeley DB on your system and installed the bdb extension module of Ruby (see (()) ), you can create and search indexes with Berkeley DB - a very fast alternative that uses little computer memory. When creating the index, use the "--makeindex-bdb" option instead of "--makeindex". % br_bioflat.rb --makeindex-bdb database_name [--format data_format] filename... == BioFetch Note: this section is an advanced topic BioFetch is a database retrieval mechanism via CGI. CGI Parameters, options and error codes are standardized. Client access via http is possible giving the database name, identifiers and format to retrieve entries. The BioRuby project has a BioFetch server at bioruby.org. It uses GenomeNet's DBGET system as a backend. The source code of the server is in sample/ directory. Currently, there are only two BioFetch servers in the world: bioruby.org and EBI. Here are some methods to retrieve entries from our BioFetch server. (1) Using a web browser http://bioruby.org/cgi-bin/biofetch.rb (2) Using the br_biofetch.rb command % br_biofetch.rb db_name entry_id (3) Directly using Bio::Fetch in a script serv = Bio::Fetch.new(server_url) entry = serv.fetch(db_name, entry_id) (4) Indirectly using Bio::Fetch via BioRegistry in script reg = Bio::Registry.new serv = reg.get_database('genbank') entry = serv.get_by_id('AA2CG') If you want to use (4), you have to include some settings in seqdatabase.ini. For example: [genbank] protocol=biofetch location=http://bioruby.org/cgi-bin/biofetch.rb biodbname=genbank === The combination of BioFetch, Bio::KEGG::GENES and Bio::AAindex1 Bioinformatics is often about gluing things together. Here is an example that gets the bacteriorhodopsin gene (VNG1467G) of the archaea Halobacterium from KEGG GENES database and gets alpha-helix index data (BURA740101) from the AAindex (Amino acid indices and similarity matrices) database, and shows the helix score for each 15-aa length overlapping window. #!/usr/bin/env ruby require 'bio' entry = Bio::Fetch.query('hal', 'VNG1467G') aaseq = Bio::KEGG::GENES.new(entry).aaseq entry = Bio::Fetch.query('aax1', 'BURA740101') helix = Bio::AAindex1.new(entry).index position = 1 win_size = 15 aaseq.window_search(win_size) do |subseq| score = subseq.total(helix) puts [ position, score ].join("\t") position += 1 end The special method Bio::Fetch.query uses the preset BioFetch server at bioruby.org. (The server internally gets data from GenomeNet. Because the KEGG/GENES database and AAindex database are not available from other BioFetch servers, we used the bioruby.org server with Bio::Fetch.query method.) == BioSQL BioSQL is a well known schema to store and retrive biological sequences using a RDBMS like PostgreSQL or MySQL: note that SQLite is not supported. First of all, you must install a database engine or have access to a remote one. Then create the schema and populate with the taxonomy. You can follow the (()) to accomplish these steps. Next step is to install these gems: * ActiveRecord * CompositePrimaryKeys (Rails doesn't handle by default composite primary keys) * The layer to comunicate with you preferred RDBMS (postgresql, mysql, jdbcmysql in case you are running JRuby ) You can find ActiveRecord's models in /bioruby/lib/bio/io/biosql When you have your database up and running, you can connect to it like this: #!/usr/bin/env ruby require 'bio' connection = Bio::SQL.establish_connection({'development'=>{'hostname'=>"YourHostname", 'database'=>"CoolBioSeqDB", 'adapter'=>"jdbcmysql", 'username'=>"YourUser", 'password'=>"YouPassword" } }, 'development') #The first parameter is the hash contaning the description of the configuration; similar to database.yml in Rails applications, you can declare different environment. #The second parameter is the environment to use: 'development', 'test', or 'production'. #To store a sequence into the database you simply need a biosequence object. biosql_database = Bio::SQL::Biodatabase.find(:first) ff = Bio::GenBank.open("gbvrl1.seq") ff.each_entry do |gb| Bio::SQL::Sequence.new(:biosequence=>gb.to_biosequence, :biodatabase=>biosql_database end #You can list all the entries into every database Bio::SQL.list_entries #list databases: Bio::SQL.list_databases #retriving a generic accession bioseq = Bio::SQL.fetch_accession("YouAccession") #If you use biosequence objects, you will find all its method mapped to BioSQL sequences. #But you can also access to the models directly: #get the raw sequence associated with your accession bioseq.entry.biosequence #get the length of your sequence; this is the explicit form of bioseq.length bioseq.entry.biosequence.length #convert the sequence into GenBank format bioseq.to_biosequence.output(:genbank) BioSQL's (()) is not very intuitive for beginners, so spend some time on understanding it. In the end if you know a little bit of Ruby on Rails, everything will go smoothly. You can find information on Annotation (()). ToDo: add exemaples from George. I remember he did some cool post on BioSQL and Rails. = PhyloXML PhyloXML is an XML language for saving, analyzing and exchanging data of annotated phylogenetic trees. PhyloXML's parser in BioRuby is implemented in Bio::PhyloXML::Parser, and its writer in Bio::PhyloXML::Writer. More information can be found at (()). == Requirements In addition to BioRuby, you need the libxml Ruby bindings. To install, execute: % gem install -r libxml-ruby For more information see the (()) == Parsing a file require 'bio' # Create new phyloxml parser phyloxml = Bio::PhyloXML::Parser.open('example.xml') # Print the names of all trees in the file phyloxml.each do |tree| puts tree.name end If there are several trees in the file, you can access the one you wish by specifying its index: tree = phyloxml[3] You can use all Bio::Tree methods on the tree, since PhyloXML::Tree inherits from Bio::Tree. For example, tree.leaves.each do |node| puts node.name end PhyloXML files can hold additional information besides phylogenies at the end of the file. This info can be accessed through the 'other' array of the parser object. phyloxml = Bio::PhyloXML::Parser.open('example.xml') while tree = phyloxml.next_tree # do stuff with trees end puts phyloxml.other == Writing a file # Create new phyloxml writer writer = Bio::PhyloXML::Writer.new('tree.xml') # Write tree to the file tree.xml writer.write(tree1) # Add another tree to the file writer.write(tree2) == Retrieving data Here is an example of how to retrieve the scientific name of the clades included in each tree. require 'bio' phyloxml = Bio::PhyloXML::Parser.open('ncbi_taxonomy_mollusca.xml') phyloxml.each do |tree| tree.each_node do |node| print "Scientific name: ", node.taxonomies[0].scientific_name, "\n" end end == Retrieving 'other' data require 'bio' phyloxml = Bio::PhyloXML::Parser.open('phyloxml_examples.xml') while tree = phyloxml.next_tree #do something with the trees end p phyloxml.other puts "\n" #=> output is an object representation #Print in a readable way puts phyloxml.other[0].to_xml, "\n" #=>: # # # acgtcgcggcccgtggaagtcctctcct # aggtcgcggcctgtggaagtcctctcct # taaatcgc--cccgtgg-agtccc-cct # #Once we know whats there, lets output just sequences phyloxml.other[0].children.each do |node| puts node.value end #=> # #acgtcgcggcccgtggaagtcctctcct #aggtcgcggcctgtggaagtcctctcct #taaatcgc--cccgtgg-agtccc-cct == The BioRuby example programs Some sample programs are stored in ./samples/ directory. For example, the n2aa.rb program (transforms a nucleic acid sequence into an amino acid sequence) can be run using: ./sample/na2aa.rb test/data/fasta/example1.txt == Unit testing and doctests BioRuby comes with an extensive testing framework with over 1300 tests and 2700 assertions. To run the unit tests: cd test ruby runner.rb We have also started with doctest for Ruby. We are porting the examples in this tutorial to doctest - more info upcoming. == Further reading See the BioRuby in anger Wiki. A lot of BioRuby's documentation exists in the source code and unit tests. To really dive in you will need the latest source code tree. The embedded rdoc documentation for the BioRuby source code can be viewed online at (()). == BioRuby Shell The BioRuby shell implementation is located in ./lib/bio/shell. It is very interesting as it uses IRB (the Ruby intepreter) which is a powerful environment described in (()). IRB commands can be typed directly into the shell, e.g. bioruby!> IRB.conf[:PROMPT_MODE] ==!> :PROMPT_C Additionally, you also may want to install the optional Ruby readline support - with Debian libreadline-ruby. To edit a previous line you may have to press line down (down arrow) first. = Helpful tools Apart from rdoc you may also want to use rtags - which allows jumping around source code by clicking on class and method names. cd bioruby/lib rtags -R --vi For a tutorial see (()) = APPENDIX == Biogem: Additional BioRuby plugins Biogem is one of the exciting developments for Ruby in bioinformatics! Biogems add new functionality next to the BioRuby core project (BioRuby is a biogem itself). A biogem is simply installed with gem install bio # The core BioRuby gem gem install bio-core # BioRuby + stable pure Ruby biogems gem install bio-core-ext # bio-core + stable Ruby extensions Information on these biogems, and the many others available, see (()) or (()). == Ruby Ensembl API The Ruby Ensembl API is a Ruby API to the Ensembl database. It is NOT currently included in the BioRuby archives. To install it, see (()) for more information. === Gene Ontology (GO) through the Ruby Ensembl API Gene Ontologies can be fetched through the Ruby Ensembl API package: require 'ensembl' Ensembl::Core::DBConnection.connect('drosophila_melanogaster') infile = IO.readlines(ARGV.shift) # reading your comma-separated accession mapping file (one line per mapping) infile.each do |line| accs = line.split(",") # Split the comma-sep.entries into an array drosphila_acc = accs.shift # the first entry is the Drosophila acc mosq_acc = accs.shift # the second entry is your Mosq. acc gene = Ensembl::Core::Gene.find_by_stable_id(drosophila_acc) print "#{mosq_acc}" gene.go_terms.each do |go| print ",#{go}" end end Prints each mosq. accession/uniq identifier and the GO terms from the Drosphila homologues. == Using BioPerl or BioPython from Ruby A possible route is to opt for JRuby and Jython on the JAVA virtual machine (JVM). At the moment there is no easy way of accessing BioPerl or BioPython directly from Ruby. A possibility is to create a Perl or Python server that gets accessed through XML/RPC or SOAP. == Installing required external libraries At this point for using BioRuby no additional libraries are needed, except if you are using the Bio::PhyloXML module; then you have to install libxml-ruby. This may change, so keep an eye on the Bioruby website. Also when a package is missing BioRuby should show an informative message. At this point installing third party Ruby packages can be a bit painful, as the gem standard for packages evolved late and some still force you to copy things by hand. Therefore read the README's carefully that come with each package. === Installing libxml-ruby The simplest way is to use the RubyGems packaging system: gem install -r libxml-ruby If you get `require': no such file to load - mkmf (LoadError) error then do sudo apt-get install ruby-dev If you have other problems with installation, then see (()). == Trouble shooting * Error: in `require': no such file to load -- bio (LoadError) Ruby is failing to find the BioRuby libraries - add it to the RUBYLIB path, or pass it to the interpeter. For example: ruby -I$BIORUBYPATH/lib yourprogram.rb == Modifying this page IMPORTANT NOTICE: This page is maintained in the BioRuby source code repository. Please edit the file there otherwise changes may get lost. See (()) for repository and mailing list access. =end