Ubuntu
mafft package

mafft 7.127-1 source package in Ubuntu

Changelog

mafft (7.127-1) unstable; urgency=low


  * New upstream release.
  * debian/tests/with-example-data: Don't write progress to stderr on success.
    Closes: #728190, thanks to Martin Pitt <email address hidden>.
  * Conforms with Policy 3.9.5.
  * Pass CPPFLAGS within CFLAGS.

 -- Charles Plessy <email address hidden>  Sat, 30 Nov 2013 17:30:14 +0900

Upload details

Uploaded by:
Debian Med
Uploaded to:
Sid
Original maintainer:
Debian Med
Architectures:
any
Section:
science
Urgency:
Low Urgency

See full publishing history Publishing

Series Pocket Published Component Section

Downloads

File Size SHA-256 Checksum
mafft_7.127-1.dsc 1.9 KiB 70e74cb4132e8c253cda44e0a7d07fd90c8b52be54bb37eacc18c4e093dc6ebf
mafft_7.127.orig.tar.gz 374.9 KiB 930f27e21c643d60a6dc2bde9a69f070cc700869ab03b2471fbe1a0a72836b7b
mafft_7.127-1.debian.tar.gz 5.9 KiB 344a3d976a43d0ca842b9b5ba5a477879370a794386acde567f05f549f217f09

No changes file available.

Binary packages built by this source

mafft: Multiple alignment program for amino acid or nucleotide sequences

 MAFFT is a multiple sequence alignment program which offers three
 accuracy-oriented methods:
  * L-INS-i (probably most accurate; recommended for <200 sequences;
    iterative refinement method incorporating local pairwise alignment
    information),
  * G-INS-i (suitable for sequences of similar lengths; recommended for
    <200 sequences; iterative refinement method incorporating global
    pairwise alignment information),
  * E-INS-i (suitable for sequences containing large unalignable regions;
    recommended for <200 sequences),
 and five speed-oriented methods:
  * FFT-NS-i (iterative refinement method; two cycles only),
  * FFT-NS-i (iterative refinement method; max. 1000 iterations),
  * FFT-NS-2 (fast; progressive method),
  * FFT-NS-1 (very fast; recommended for >2000 sequences; progressive
    method with a rough guide tree),
  * NW-NS-PartTree-1 (recommended for ∼50,000 sequences; progressive
    method with the PartTree algorithm).