AlignStat: a web-tool and R package for statistical comparison of alternative multiple sequence alignments

Shafee, Thomas, and Cooke, Ira (2016) AlignStat: a web-tool and R package for statistical comparison of alternative multiple sequence alignments. BMC Bioinformatics, 17 (1). pp. 1-6.

PDF (Published Version) - Published Version
Available under License Creative Commons Attribution.

Download (1MB) | Preview
View at Publisher Website:


Background: Alternative sequence alignment algorithms yield different results. It is therefore useful to quantify the similarities and differences between alternative alignments of the same sequences. These measurements can identify regions of consensus that are likely to be most informative in downstream analysis. They can also highlight systematic differences between alignments that relate to differences in the alignment algorithms themselves.

Results: Here we present a simple method for aligning two alternative multiple sequence alignments to one another and assessing their similarity. Differences are categorised into merges, splits or shifts in one alignment relative to the other. A set of graphical visualisations allow for intuitive interpretation of the data.

Conclusions: AlignStat enables the easy one-off online use of MSA similarity comparisons or into R pipelines. The web-tool is available at The R package, readme and example data are available on CRAN and

Item ID: 47988
Item Type: Article (Research - C1)
ISSN: 1471-2105
Additional Information:

© The Author(s). 2016. Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (, 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.

Funders: Australian Research Council (ARC), Victorian Life Sciences Computation Initiative
Date Deposited: 22 Mar 2017 00:29
FoR Codes: 31 BIOLOGICAL SCIENCES > 3104 Evolutionary biology > 310410 Phylogeny and comparative analysis @ 20%
46 INFORMATION AND COMPUTING SCIENCES > 4601 Applied computing > 460103 Applications in life sciences @ 80%
SEO Codes: 97 EXPANDING KNOWLEDGE > 970106 Expanding Knowledge in the Biological Sciences @ 100%
Downloads: Total: 793
Last 12 Months: 80
More Statistics

Actions (Repository Staff Only)

Item Control Page Item Control Page