Addressing inaccuracies in BLOSUM computation improves homology search performance

Background BLOSUM matrices belong to the most commonly used substitution matrix series for protein homology search and sequence alignments since their publication in 1992. In 2008, Styczynski et al. discovered miscalculations in the clustering step of the matrix computation. Still, the RBLOSUM64 matrix based on the corrected BLOSUM code was reported to perform worse at a statistically significant level than the BLOSUM62. Here, we present a further correction of the (R)BLOSUM code and provide a thorough performance analysis of BLOSUM-, RBLOSUM- and the newly derived CorBLOSUM-type matrices. Thereby, we assess homology search performance of these matrix-types derived from three different BLOCKS databases on all versions of the ASTRAL20, ASTRAL40 and ASTRAL70 subsets resulting in 51 different benchmarks in total. Our analysis is focused on two of the most popular BLOSUM matrices — BLOSUM50 and BLOSUM62. Results Our study shows that fixing small errors in the BLOSUM code results in substantially different substitution matrices with a beneficial influence on homology search performance when compared to the original matrices. The CorBLOSUM matrices introduced here performed at least as good as their BLOSUM counterparts in ∼75 % of all test cases. On up-to-date ASTRAL databases BLOSUM matrices were even outperformed by CorBLOSUM matrices in more than 86 % of the times. In contrast to the study by Styczynski et al., the tested RBLOSUM matrices also outperformed the corresponding BLOSUM matrices in most of the cases. Comparing the CorBLOSUM with the RBLOSUM matrices revealed no general performance advantages for either on older ASTRAL releases. On up-to-date ASTRAL databases however CorBLOSUM matrices performed better than their RBLOSUM counterparts in ∼74 % of the test cases. Conclusions Our results imply that CorBLOSUM type matrices outperform the BLOSUM matrices on a statistically significant level in most of the cases, especially on up-to-date databases such as ASTRAL ≥2.01. Additionally, CorBLOSUM matrices are closer to those originally intended by Henikoff and Henikoff on a conceptual level. Hence, we encourage the usage of CorBLOSUM over (R)BLOSUM matrices for the task of homology search. Electronic supplementary material The online version of this article (doi:10.1186/s12859-016-1060-3) contains supplementary material, which is available to authorized users.

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PID https://www.doi.org/10.1186/s12859-016-1060-3
PID pmc:PMC4849092
PID pmid:27122148
URL https://0-bmcbioinformatics-biomedcentral-com.brum.beds.ac.uk/articles/10.1186/s12859-016-1060-3
URL https://dx.doi.org/10.1186/s12859-016-1060-3
URL https://link.springer.com/article/10.1186%2Fs12859-016-1060-3
URL http://europepmc.org/articles/PMC4849092
URL https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4849092/
URL https://doi.org/10.1186/s12859-016-1060-3
URL https://core.ac.uk/display/81800396
URL http://link.springer.com/content/pdf/10.1186/s12859-016-1060-3
URL http://tubiblio.ulb.tu-darmstadt.de/80638/
URL http://dx.doi.org/10.1186/s12859-016-1060-3
URL https://bmcbioinformatics.biomedcentral.com/track/pdf/10.1186/s12859-016-1060-3
URL http://www.europepmc.org/articles/PMC4849092/
URL https://paperity.org/p/76025106/addressing-inaccuracies-in-blosum-computation-improves-homology-search-performance
URL https://dblp.uni-trier.de/db/journals/bmcbi/bmcbi17.html#HessKGH16
URL https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-016-1060-3
URL https://academic.microsoft.com/#/detail/2344155264
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Author Michael Goesele, 0000-0002-0944-0980
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Collected From Europe PubMed Central; PubMed Central; ORCID; UnpayWall; Datacite; Crossref; Microsoft Academic Graph; CORE (RIOXX-UK Aggregator)
Hosted By Europe PubMed Central; SpringerOpen; BMC Bioinformatics
Journal BMC Bioinformatics, 17,
Publication Date 2016-04-27
Publisher BioMed Central
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Language English
Resource Type Article; UNKNOWN
keyword BLOCKS 13+
system:type publication
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Source https://science-innovation-policy.openaire.eu/search/publication?articleId=dedup_wf_001::5ce1060da1282990776b13b67d0683f2
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Last Updated 21 December 2020, 21:13 (CET)
Created 21 December 2020, 21:13 (CET)