Skip to main content

PRALINE sequence alignment toolkit

Project description

PRALINE

Reimplementation of the PRALINE multiple sequence alignment program.

Features

  • Progressive multiple sequence alignment
  • Tree generation through hierarchical clustering and on-the-fly (PRALINE-style)
  • Profile-profile pairwise alignment
  • Affine and linear gap penalties supported; arbitrary gap penalties supported w/ reduced speed
  • Semi-global, global alignment for the MSA merge step
  • Local, global and semi-global preprofile generation
  • Improved preprofile sampling through PSI-BLAST search (requires local installation of NCBI BLAST+)
  • Nucleotide and amino acid alphabets supported out of the box
  • Easy to extend to with arbitrary alphabets (e.g. secondary sequence)
  • Packaged with common substitution matrices (BLOSUM), can be provided to the program.

Coming soon

  • HMM-like gap penalties per position
  • Heuristics to speed up tree building for large numbers of sequences
  • Better multithreading for improved scaling on many-core systems

Installing PRALINE

Requirements

  • Python 2.7 / Python 3.6 (earlier 3.x versions may also work, but have not been tested)
  • A C compiler (C99 support required)
  • NCBI BLAST+ (optional, for homology searching using PSI-BLAST)

Instructions

You can install PRALINE by cloning this repository and running (in a shell):

python setup.py install

PRALINE is also available on PyPI. You can install it with the following command:

pip install praline

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

praline-aln-1.1.0.tar.gz (60.7 kB view details)

Uploaded Source

Built Distributions

If you're not sure about the file name format, learn more about wheel file names.

praline_aln-1.1.0-cp36-cp36m-macosx_10_13_x86_64.whl (95.1 kB view details)

Uploaded CPython 3.6mmacOS 10.13+ x86-64

praline_aln-1.1.0-cp27-cp27m-macosx_10_14_intel.whl (91.6 kB view details)

Uploaded CPython 2.7mmacOS 10.14+ Intel (x86-64, i386)

File details

Details for the file praline-aln-1.1.0.tar.gz.

File metadata

  • Download URL: praline-aln-1.1.0.tar.gz
  • Upload date:
  • Size: 60.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.12.1 pkginfo/1.4.2 requests/2.20.1 setuptools/40.6.2 requests-toolbelt/0.8.0 tqdm/4.28.1 CPython/3.6.4

File hashes

Hashes for praline-aln-1.1.0.tar.gz
Algorithm Hash digest
SHA256 23b7338b4df0741b679e0fd6e61bf9df2c6077a23b3ce148ec433a79543ed0fc
MD5 9d00f31ed0d3ac0cbb4d6a1bf28f83c4
BLAKE2b-256 35455952c81f7e4ed53df8208628ab4c37cfb2151ed3df0c616c9b2b8dbd4424

See more details on using hashes here.

File details

Details for the file praline_aln-1.1.0-cp36-cp36m-macosx_10_13_x86_64.whl.

File metadata

  • Download URL: praline_aln-1.1.0-cp36-cp36m-macosx_10_13_x86_64.whl
  • Upload date:
  • Size: 95.1 kB
  • Tags: CPython 3.6m, macOS 10.13+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.12.1 pkginfo/1.4.2 requests/2.20.1 setuptools/40.6.2 requests-toolbelt/0.8.0 tqdm/4.28.1 CPython/3.6.4

File hashes

Hashes for praline_aln-1.1.0-cp36-cp36m-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 d4d6dfd27c26d31b57a2f17646fa8b5b3ad60dc4e55bb547f56e67f0ccf98b4e
MD5 b76228e0f9606ce44bf4120dd8d5096e
BLAKE2b-256 b20c89988457a63c1aa23cd1f30acbba5ca0786e2cfebbee4d01739141d9c1c6

See more details on using hashes here.

File details

Details for the file praline_aln-1.1.0-cp27-cp27m-macosx_10_14_intel.whl.

File metadata

  • Download URL: praline_aln-1.1.0-cp27-cp27m-macosx_10_14_intel.whl
  • Upload date:
  • Size: 91.6 kB
  • Tags: CPython 2.7m, macOS 10.14+ Intel (x86-64, i386)
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.12.1 pkginfo/1.4.2 requests/2.20.1 setuptools/40.6.2 requests-toolbelt/0.8.0 tqdm/4.28.1 CPython/3.6.4

File hashes

Hashes for praline_aln-1.1.0-cp27-cp27m-macosx_10_14_intel.whl
Algorithm Hash digest
SHA256 f8546351e89c7b08ea6eefe12fdb03c1f62f41a73b64a325f11a7415d6ba87ac
MD5 682180d643daaed3932054fe452b243d
BLAKE2b-256 cc815bdc4895177efe0c608b009bfa2bf82c57d2323e362ad6d18b58403de679

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page