AlignBucket: a tool to speed up 'all-against-all' protein sequence alignments optimizing length constraints

Bioinformatics. 2015 Dec 1;31(23):3841-3. doi: 10.1093/bioinformatics/btv451. Epub 2015 Jul 30.

Abstract

Motivation: The next-generation sequencing era requires reliable, fast and efficient approaches for the accurate annotation of the ever-increasing number of biological sequences and their variations. Transfer of annotation upon similarity search is a standard approach. The procedure of all-against-all protein comparison is a preliminary step of different available methods that annotate sequences based on information already present in databases. Given the actual volume of sequences, methods are necessary to pre-process data to reduce the time of sequence comparison.

Results: We present an algorithm that optimizes the partition of a large volume of sequences (the whole database) into sets where sequence length values (in residues) are constrained depending on a bounded minimal and expected alignment coverage. The idea is to optimally group protein sequences according to their length, and then computing the all-against-all sequence alignments among sequences that fall in a selected length range. We describe a mathematically optimal solution and we show that our method leads to a 5-fold speed-up in real world cases.

Availability and implementation: The software is available for downloading at http://www.biocomp.unibo.it/∼giuseppe/partitioning.html.

Contact: giuseppe.profiti2@unibo.it.

Supplementary information: Supplementary data are available at Bioinformatics online.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms*
  • Computational Biology / methods*
  • Databases, Protein*
  • Humans
  • Proteins / chemistry*
  • Sequence Alignment / methods*
  • Software*

Substances

  • Proteins