Dataset Information
HPC-CLUST: distributed hierarchical clustering for large sets of nucleotide sequences.
Ontology highlight
ABSTRACT: Motivation
Nucleotide sequence data are being produced at an ever increasing rate. Clustering such sequences by similarity is often an essential first step in their analysis-intended to reduce redundancy, define gene families or suggest taxonomic units. Exact clustering algorithms, such as hierarchical clustering, scale relatively poorly in terms of run time and memory usage, yet they are desirable because heuristic shortcuts taken during clustering might have unintended consequences in later analysis steps.Results
Here we present HPC-CLUST, a highly optimized software pipeline that can cluster large numbers of pre-aligned DNA sequences by running on distributed computing hardware. It allocates both memory and computing resources efficiently, and can process more than a million sequences in a few hours on a small cluster.Availability and implementation
Source code and binaries are freely available at http://meringlab.org/software/hpc-clust/; the pipeline is implemented in Cþþ and uses the Message Passing Interface (MPI) standard for distributed computing.
SUBMITTER: Matias Rodrigues JF
PROVIDER: S-EPMC3892691 | biostudies-literature | 2014 Jan
REPOSITORIES: biostudies-literature
Publications
HPC-CLUST: distributed hierarchical clustering for large sets of nucleotide sequences.
Bioinformatics (Oxford, England) 20131109 2
<h4>Motivation</h4>Nucleotide sequence data are being produced at an ever increasing rate. Clustering such sequences by similarity is often an essential first step in their analysis-intended to reduce redundancy, define gene families or suggest taxonomic units. Exact clustering algorithms, such as hierarchical clustering, scale relatively poorly in terms of run time and memory usage, yet they are desirable because heuristic shortcuts taken during clustering might have unintended consequences in ...[more]
