The original article was published in BMC Bioinformatics 2015 16:218
Erratum
Unfortunately, [1] was published without incorporation of all requested corrections. The correct equation for computing the E-value from a bit score is
The image file used for Figure 2 was incorrect. The correct figure is provided here as Fig. 1. The name of Additional File 1 should be “Supplemental Figures”, not “Sensitivity performance comparison for each test database.” The University of Maryland, College Park is located in College Park, Maryland, not College Park, Baltimore, Maryland. The correct addresses are provided in this erratum.
Fig. 1
Illustration of simulated sequence fragmentation. This example illustrates the four different ways in which the fragmentation scheme 1323 would be applied to a toy input test database with only three clusters containing sequences from only four organisms. The four resulting test sets represent a cross of two variables, arranged here into rows and columns. The sequences in the top row (a & b) have been split into even subsequences. The sequences in the lower row (c & d) have been randomly fragmented into uneven subsequences. In the left column (a & c), the user-defined integer assigned to each organism directly determines the number of subsequences into which each sequence is split. In the right column (b & d), these integers are first mapped to all sequences within a cluster, but are then shuffled within that cluster before fragmentation
Notes
Declarations
Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
Authors’ Affiliations
(1)
Department of Cell Biology and Molecular Genetics, University of Maryland
(2)
Center for Bioinformatics and Computational Biology, University of Maryland
(3)
Maryland Agricultural Experiment Station, University of Maryland
Reference
Gibbons TR, Mount SM, Cooper DC, Delwiche CF. Evaluation of BLAST-based edge-weighting metrics used for homology inference with the Markov Clustering algorithm. BMC Bioinformatics. 2015;16:218.View ArticlePubMedPubMed CentralGoogle Scholar
