Sometimes it is useful to be able represent a contig produced as part of genome or EST assembly as an alignment (eg to search for potential SNPs in runs from mixed samples or to be able to write a contig out in a way it can be viewed more easily). For assemblies that use the ACE file format we can use Biopython’s ACE handling to add reads that make a contig to a generic alignment.’
Let’s represent contig in the ACE file that is used in Biopython’s testing framework: Tests/Ace/contig1.ace as an example
from Bio.Sequencing import Ace from Bio.Align.Generic import Alignment from Bio.Alphabet import IUPAC, Gapped def cut_ends(read, start, end): '''Replace residues on either end of a sequence with gaps. In this case we want to cut out the sections of each read which the assembler has decided are not good enough to include in the contig and replace them with gaps so the other information about positions in the read is maintained ''' return (start-1) * '-' + read[start-1:end] + (len(read)-end) * '-' def pad_read(read, start, conlength): ''' Pad out either end of a read so it fits into an alignment. The start argument is the position of the first base of the reads sequence in the contig it is part of. If the start value is negative (or 0 since ACE files count from 1, not 0) we need to take some sequence off the start otherwise each end is padded to the length of the consensus with gaps. ''' if start < 1: seq = read[-1*start+1:] else: seq = (start-1) * '-' + read seq = seq + (conlength-len(seq)) * '-' return seq # We will use the Ace parser to read individual contigs from file. Be aware # that using this iterator can miss WA, CT, RT and WR tags (which can be # anywhere in the file, e.g. the end). Read the file specification here: # http://bozeman.mbt.washington.edu/consed/distributions/README.14.0.txt # If you need these tags you'll need to use Ace.read() (and lots of RAM). ace_gen = Ace.parse(open("contig1.ace", 'r')) contig = ace_gen.next() align = Alignment(Gapped(IUPAC.ambiguous_dna, "-")) # Now we have started our alignment we can add sequences to it, # we will loop through contig's reads and get quality clipping from # .reads[readnumber].qa and the position of each read in the contig # .af[readnumber].padded_start and use the functions above to cut and # pad the sequences before they are added for readn in range(len(contig.reads)): clipst = contig.reads[readn].qa.qual_clipping_start clipe = contig.reads[readn].qa.qual_clipping_end start = contig.af[readn].padded_start seq = cut_ends(contig.reads[readn].rd.sequence, clipst, clipe) seq = pad_read(seq, start, len(contig.sequence)) align.add_sequence("read%i" % (readn + 1), seq)
and when you print the alignment, or the sequences within it
>>>print align Gapped(IUPACAmbiguousDNA(), '-') alignment with 2 rows and 856 columns --------------------------------------------...--- read1 ------GGATTGCCCTagtaacGGCGAGTGAAGCGGCAACAGCT...--- read2 >>> for read in align: ... print read.seq[80:159] tt*gtagagggaTGCTTCTGGGTAGCGACCGGTCTAAGTTCCTCGGAACAGGACGTCATAGAGGGTGAGAATCCCGTAT TTTGTAGAGG*ATGCTTCTGGGTAGCGACCGGTCTAAGTTCCTCGGAACAGGACGTCATAGAGGGTGAGAATCCCGTAT
You can also now write the alignment to any format you want to using AlignIO.
The details are given in the comments above, in broad strokes the ACE contig is read in with Ace.parse(), a generic alignment is started then the reads from the contig are added to the new alignment.