About SCANMS
SCANMS is an open source utility written in Perl that works in conjunction with Richard Hudson’s coalescent simulator MS to do parametric bootstrapping of a sliding window analysis of neutrality test statistics. Currently supported statistics are Tajima’s D and Fu and Li’s D* and F*. Its output of a joint distribution of window minima and maxima may then be used to correct for multiple comparisons in such analyses.
Downloading and Licensing of SCANMS
The current version of SCANMS is 2.02. You can get either a GNU-tarballed and gzipped or zipped version of an installation package or just get the script or see its embedded documentation. There is a preprint of the manuscript describing SCANMS containing slightly different figures from the Bioinformatics article.
SCANMS is distributed under the terms of the Academic Free License v. 2.0 by Lawrence E. Rosen. Please see http://rosenlaw.com/afl2.0.html or http://opensource.org/licenses/afl-2.0.php.
Citing SCANMS
Please cite Ardell, D.H. (2004) SCANMS: Adjusting for multiple comparisons in sliding window neutrality tests. Bioinformatics 20(12):1986-1988 if you publish analyses or modifications of SCANMS. Thanks!
Compatibility and More Information
SCANMS, being quite simple, should work on any platform to which Perl has been ported. This list includes Windows, Mac Classic and Mac OS X (where it should Just Work). But it has only been tested on Linux and Mac OS X. If you have feedback about the use or installation of SCANMS please contact me.
NEWS
January 30, 2008 — version 2.02 released fixing a bug that caused scanms to fail to recognize some valid ms input when ms with called by a relative or absolute path. Thanks to Mariano Giombini for pointing this out.
Oops: The print version of the one figure in the journal article was slightly magnified, and the axis lines (but fortunately not the axes) look like they’re missing. Check the manuscript version or the journal’s onscreen version if this is confusing, or if you want to see an additional figure showing an example histogram of sliding window maxima.