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Biopython

Biopython. What is Biopython ?. tools for computational molecular biology to program in python and want to make it as easy as possible to use python for bioinformatics by creating high-quality, reusable modules and scripts. What can Biopython do?. Manipulate DNA and protein sequences

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Biopython

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  1. Biopython

  2. What is Biopython? • tools for computational molecular biology • to program in python and want to make it as easy as possible to use python for bioinformatics by creating high-quality, reusable modules and scripts

  3. What can Biopython do? • Manipulate DNA and protein sequences • Run BLAST • Access public databases • Manipulate protein structures • Population genetics • Supervised learning methods • Networks of various kinds

  4. Obtaining Biopython • http://www.biopython.org

  5. Making sure it worked >>> new_seq.complement() >>> new_seq.reverse_complement()

  6. Working with sequences • A biopythonSeqobject has two important attributes: • data : as the name implies, this is the actual sequence data string of the sequence • alphabet : an object describing what the individual characters making up the string "mean" and how they should be interpreted • Two advantages • this gives an idea of the type of information the data object contains • this provides a means of contrainingthe information you have in the data object, as a means of type checking

  7. Working with sequences

  8. Working with sequences >>> protein_seq = Seq('EVRNAK', IUPAC.protein) >>> dna_seq = Seq('ACGT', IUPAC.unambiguous_dna) >>> protein_seq + dna_seq >>> my_seq.tostring() >>> my_seq[5] = 'G >>> mutable_seq = my_seq.tomutable() >>> print mutable_seq >>> mutable_seq[5] = 'T' >>> print mutable_seq >>> mutable_seq.remove('T') >>> print mutable_seq >>> mutable_seq.reverse() >>> print mutable_seq

  9. Parsing biological file formats >gi|6273290|gb|AF191664.1|AF191664 Opuntiaclavata rpl16 gene; chloroplast gene for...TATACATTAAAGGAGGGGGATGCGGATAAATGGAAAGGCGAAAGAAAGAAAAAAATGAATCTAAATGATATAGGATTCCACTATGTAAGGTCTTTGAATCATATCATAAAAGACAATGTAATAAA... import string from Bio.ParserSupport import AbstractConsumer class SpeciesExtractor(AbstractConsumer): def__init__(self): self.species_list= [] deftitle(self, title_info): title_atoms= string.split(title_info) new_species= title_atoms[1] if new_species not in self.species_list: self.species_list.append(new_species)

  10. Parsing biological file formats from Bio import Fasta defextract_organisms(file, num_records): scanner = Fasta._Scanner() consumer = SpeciesExtractor() file_to_parse= open(file, 'r') for fasta_record in range(num_records): scanner.feed(file_to_parse, consumer) file_to_parse.close() return handler.species_list

  11. Parsing biological file formats(easier) >>> from Bio import Fasta >>> parser = Fasta.RecordParser() >>> file = open("ls_orchid.fasta") >>> iterator = Fasta.Iterator(file, parser) >>> cur_record = iterator.next() >>> dir(cur_record) >>> print cur_record.title >>> print cur_record

  12. Parsing biological file formats(easier) from Bio import SeqIO myFile = open("ls_orchid.fasta") for seq_record in SeqIO.parse(myFile, "fasta"): print seq_record.id print repr(seq_record.seq) print len(seq_record) myFile.close()

  13. FASTA files as Dictionaries import string defget_accession_num(fasta_record): title_atoms= string.split(fasta_record.title) # all of the accession number information is stuck in the first element # and separated by '|'s accession_atoms= string.split(title_atoms[0], '|') # the accession number is the 4th element gb_name= accession_atoms[3] # strip the version info before returning return gb_name[:-2]

  14. FASTA files as Dictionaries(easier) >>> from Bio import Fasta >>> Fasta.index_file("ls_orchid.fasta", "my_orchid_dict.idx", get_accession_num) >>> from Bio.Alphabet import IUPAC >>> dna_parser = Fasta.SequenceParser(IUPAC.ambiguous_dna) >>> orchid_dict = Fasta.Dictionary("my_orchid_dict.idx", dna_parser)

  15. Blast for seq in SeqIO.parse('marker.fa', 'fasta'): b_results = NCBIWWW.qblast('blastn', 'nr', seq.seq, format_type='Text') print b_results.read()

  16. More information http://www.biopython.org

  17. Problem • Write a program to read a FASTA file and print the number of sequences, number of residues, and minimum, maximum and average lengths of the sequences. > python read-fasta-file.py sample.fa Number of sequences = 7 Number of residues = 285 Minimum length = 21 Maximum length = 94 Average length = 40.7

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