Methods of remote homology detection can be combined to increase coverage by 10% in the midnight zone

被引:27
作者
Reid, Adam James [1 ]
Yeats, Corin [1 ]
Orengo, Christine Anne [1 ]
机构
[1] UCL, Dept Biochem & Mol Biol, London WC1E 6BT, England
基金
英国生物技术与生命科学研究理事会;
关键词
HIDDEN MARKOV-MODELS; SEQUENCE; DATABASE; PROTEINS; CLASSIFICATION; ALIGNMENTS; FAMILIES; COMPASS; TOOL;
D O I
10.1093/bioinformatics/btm355
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Motivation: A recent development in sequence- based remote homologue detection is the introduction of profile - profile comparison methods. These are more powerful than previous technologies and can detect potentially homologous relationships missed by structural classifications such as CATH and SCOP. As structural classifications traditionally act as the gold standard of homology this poses a challenge in benchmarking them. Results: We present a novel approach which allows an accurate benchmark of these methods against the CATH structural classification. We then apply this approach to assess the accuracy of a range of publicly available methods for remote homology detection including several profile-profile methods (COMPASS, HHSearch, PRC) from two perspectives. First, in distinguishing homologous domains from non-homologues and second, in annotating proteomes with structural domain families. PRC is shown to be the best method for distinguishing homologues. We show that SAM is the best practical method for annotating genomes, whilst using COMPASS for the most remote homologues would increase coverage. Finally, we introduce a simple approach to increase the sensitivity of remote homologue detection by up to 10%. This is achieved by combining multiple methods with a jury vote.
引用
收藏
页码:2353 / 2360
页数:8
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