NBLAST: a cluster variant of BLAST for NxN comparisons

Abstract

BackgroundThe BLAST algorithm compares biological sequences to one another in order to determine shared motifs and common ancestry. However, the comparison of all non-redundant (NR) sequences against all other NR sequences is a computationally intensive task. We developed NBLAST as a cluster computer implementation of the BLAST family of sequence comparison programs for the purpose of generating pre-computed BLAST alignments and neighbour lists of NR sequences.ResultsNBLAST performs the heuristic BLAST algorithm and generates an exhaustive database of alignments, but it only computes alignments (i.e. the upper triangle) of a possible N2 alignments, where N is the set of all sequences to be compared. A task-partitioning algorithm allows for cluster computing across all cluster nodes and the NBLAST master process produces a BLAST sequence alignment database and a list of sequence neighbours for each sequence record. The resulting sequence alignment and neighbour databases are used to serve the SeqHound query system through a C/C++ and PERL Application Programming Interface (API).ConclusionsNBLAST offers a local alternative to the NCBI's remote Entrez system for pre-computed BLAST alignments and neighbour queries. On our 216-processor 450 MHz PIII cluster, NBLAST requires ~24 hrs to compute neighbours for 850000 proteins currently in the non-redundant protein database.

Pathogen detection using short-RNA deep sequencing subtraction and assembly

“…In order to identify the non-human sequences and target to which organism it aligns, we applied de novo sequencing (sequence assembly), using an assembly software [Velvet ( Zerbino et al , 2008 )] to produce longer consensus sequences from our given short read sample. These longer assembled reads were then compared to known organisms' references [using BLAST ( Dumontier et al , 2002 )] to produce high scoring unique alignments and thus a valid and conclusive identification, which could not have been reached otherwise.…”

SeqHound: biological sequence and structure database as a platform for bioinformatics research

“…The sequence neighbour information was reconstructed using the BLAST blastpgp executable from the NCBI toolkit [8]. The blastpgp executable was customized so it can be implemented on a Beowulf cluster http://www.beowulf.org/ to allow parallelization of the task.…”

“…The NBLAST [8] and RPS-BLAST protein neighbor and domain annotation computations have added functionality to the SeqHound information systems thanks to our capacity for high-performance computing. However since these files are exportable, this design should allow users to set up SeqHound systems on relatively lightweight servers without requiring access to large clusters, but still have access to information like sequence neighbors or computed domain hits and updates through an FTP site.…”

“…While the Entrez servers are not presented by NCBI in an exportable format, the NCBI FTP site has a number of relevant and daily updated data sets that can be used to reconstruct a functional in-house database resource that behaves like an Entrez server. The only part of Entrez that seems to not be available in export format on the NCBI site is the sequence neighbour information calculated by BLAST [7], however we have recently shown that we can compute protein sequence neighbors on our own internal cluster computer using a variant of NCBI Blast called NBLAST [8]. …”

Genomic richness enables worldwide invasive success

“…Coverage along the genome assembly and mean coverage were tested by mapping the initial CLR and WGS-SR back to the polished assembly using the programs Minimap2 v.2.24 and BWA-mem v.0.7.17, respectively, and visualized with Qualimap v.2.2.1 and multiQC v.1.8 68-71 implemented in backmap.pl v.0.4 72 https://github.com/schellt/backmap. Contiguity statistics were obtained using QUAST, base-level accuracy (qv) was assessed with mercury v.1.3 73 , and genome completeness was corroborated by detecting universal single copy orthologs of metazoa using BUSCO v.5.2.2 74 We checked for DNA contaminations by comparing our sequences to those in NCBI using BLAST v.2.12 75 . The resulting quality features values were graphically represented using the software BlobTools v.2.0 76 .…”