This is the command poa that can be run in the OnWorks free hosting provider using one of our multiple free online workstations such as Ubuntu Online, Fedora Online, Windows online emulator or MAC OS online emulator
PROGRAM:
NAME
poa - align a set of sequences or alignments.
SYNOPSIS
poa [OPTIONS] [MATRIXFILE]
One of the -read_fasta, -read_msa, or -read_msa_list arguments must be used, since a
sequence or alignment file is required.
DESCRIPTION
POA is Partial Order Alignment, a fast program for multiple sequence alignment (MSA) in
bioinformatics. Its advantages are speed, scalability, sensitivity, and the superior
ability to handle branching / indels in the alignment. Partial order alignment is an
approach to MSA, which can be combined with existing methods such as progressive
alignment. POA optimally aligns a pair of MSAs and which therefore can be applied directly
to progressive alignment methods such as CLUSTAL. For large alignments, Progressive POA is
10 to 30 times faster than CLUSTALW.
EXAMPLES
poa -read_fasta multidom.seq -clustal m.aln blosum80.mat
On Debian systems, poa can be tested using the following command:
poa -read_fasta /usr/share/doc/poa/examples/multidom.seq -clustal /dev/stdout -v
/usr/share/poa/blosum80.mat
OPTIONS
INPUT
-read_fasta FILE
Read in FASTA sequence file.
-read_msa FILE
Read in MSA alignment file.
-read_msa2 FILE
Read in second MSA file.
-subset FILE
Filter MSA to include list of seqs in file.
-subset2 FILE
Filter second MSA to include list of seqs in file.
-remove FILE
Filter MSA to include list of seqs in file.
-remove2 FILE
Filter second MSA to include list of seqs in file.
-read_msa_list FILE
Read an MSA from each filename listed in file.
-tolower
Force FASTA/MSA sequences to lowercase (nucleotides in our matrix files).
-toupper
Force FASTA/MSA sequences to UPPERCASE (amino acids in our matrix files).
ALIGNMENT
-do_global
Do global alignment.
-do_progressive
Perform progressive alignment using a guide tree built by neighbor joining from a set
of sequence-sequence similarity scores.
-read_pairscores FILE
Read tab-delimited file of similarity scores (If not provided, scores are constructed
using pairwise sequence alignment.)
-fuse_all
Fuse identical letters on align rings.
ANALYSIS
-hb
Perform heaviest bundling to generate consensi.
-hbmin VALUE
Include in heaviest bundle sequences with percent ID (as a fraction) >= VALUE.
OUTPUT
-pir FILE
Write out MSA in PIR format.
-clustal FILE
Write out MSA in CLUSTAL format.
-po FILE
Write out MSA in PO format.
-preserve_seqorder
Write out MSA with sequences in their input order.
-printmatrix LETTERS
Print score matrix to stdout.
-best
Restrict MSA output to heaviest bundles (PIR only).
-v
Run in verbose mode (e.g. output gap penalties).
REFERENCE
Please cite Grasso C, Lee C. (2004) Combining partial order alignment and progressive
multiple sequence alignment increases alignment speed and scalability to very large
alignment problems. Bioinformatics. 2004 Jul 10;20(10):1546-56. Epub 2004 Feb 12.
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