Domain similarity based orthology detection

BMC Bioinformatics

Methodology Article

Jenny M Greenwood¹  Erich Bornberg-Bauer¹  Carsten Kemena¹  Tristan Bitard-Feildel¹ 

[1]Institute for Evolution and Biodiversity, University of Münster, Hüfferstr. 1, Münster, Germany

关键词: Domain;    Domain similarity;    Orthology;    Similarity;   

DOI  :  10.1186/s12859-015-0570-8

 received in 2014-10-01, accepted in 2015-04-10,  发布年份 2015

来源: Springer

【 摘 要 】

BackgroundOrthologous protein detection software mostly uses pairwise comparisons of amino-acid sequences to assert whether two proteins are orthologous or not. Accordingly, when the number of sequences for comparison increases, the number of comparisons to compute grows in a quadratic order. A current challenge of bioinformatic research, especially when taking into account the increasing number of sequenced organisms available, is to make this ever-growing number of comparisons computationally feasible in a reasonable amount of time. We propose to speed up the detection of orthologous proteins by using strings of domains to characterize the proteins.ResultsWe present two new protein similarity measures, a cosine and a maximal weight matching score based on domain content similarity, and new software, named porthoDom. The qualities of the cosine and the maximal weight matching similarity measures are compared against curated datasets. The measures show that domain content similarities are able to correctly group proteins into their families. Accordingly, the cosine similarity measure is used inside porthoDom, the wrapper developed for proteinortho. porthoDom makes use of domain content similarity measures to group proteins together before searching for orthologs. By using domains instead of amino acid sequences, the reduction of the search space decreases the computational complexity of an all-against-all sequence comparison.ConclusionWe demonstrate that representing and comparing proteins as strings of discrete domains, i.e. as a concatenation of their unique identifiers, allows a drastic simplification of search space. porthoDom has the advantage of speeding up orthology detection while maintaining a degree of accuracy similar to proteinortho. The implementation of porthoDom is released using python and C++ languages and is available under the GNU GPL licence 3 at http://www.bornberglab.org/pages/porthoda.

【 授权许可】

CC BY   
© Bitard-Feildelet al.; licensee BioMed Central. 2015