Giuseppe Profiti1, Piero Fariselli2, Rita Casadio3. 1. Department of Computer Science and Engineering, via Mura Anteo Zamboni 7, Bologna, Bologna Biocomputing group, via S. Giacomo 9/2, Bologna and Health Sciences and Technologies ICIR, via Tolara di Sopra 41/E, Ozzano dell'Emilia, Italy. 2. Department of Computer Science and Engineering, via Mura Anteo Zamboni 7, Bologna, Bologna Biocomputing group, via S. Giacomo 9/2, Bologna and. 3. Bologna Biocomputing group, via S. Giacomo 9/2, Bologna and Health Sciences and Technologies ICIR, via Tolara di Sopra 41/E, Ozzano dell'Emilia, Italy.
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.
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.