Ontology highlight
ABSTRACT: Motivation
Many bioinformatics areas require us to assign domain matches onto stretches of a query protein. Starting with a set of candidate matches, we want to identify the optimal subset that has limited/no overlap between matches. This may be further complicated by discontinuous domains in the input data. Existing tools are increasingly facing very large data-sets for which they require prohibitive amounts of CPU-time and memory.Results
We present cath-resolve-hits (CRH), a new tool that uses a dynamic-programming algorithm implemented in open-source C++ to handle large datasets quickly (up to ∼1 million hits/second) and in reasonable amounts of memory. It accepts multiple input formats and provides its output in plain text, JSON or graphical HTML. We describe a benchmark against an existing algorithm, which shows CRH delivers very similar or slightly improved results and very much improved CPU/memory performance on large datasets.Availability and implementation
CRH is available at https://github.com/UCLOrengoGroup/cath-tools; documentation is available at http://cath-tools.readthedocs.io.Supplementary information
Supplementary data are available at Bioinformatics online.
SUBMITTER: Lewis TE
PROVIDER: S-EPMC6513158 | biostudies-literature | 2019 May
REPOSITORIES: biostudies-literature
Lewis T E TE Sillitoe I I Lees J G JG
Bioinformatics (Oxford, England) 20190501 10
<h4>Motivation</h4>Many bioinformatics areas require us to assign domain matches onto stretches of a query protein. Starting with a set of candidate matches, we want to identify the optimal subset that has limited/no overlap between matches. This may be further complicated by discontinuous domains in the input data. Existing tools are increasingly facing very large data-sets for which they require prohibitive amounts of CPU-time and memory.<h4>Results</h4>We present cath-resolve-hits (CRH), a ne ...[more]