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authorPetar Petrov <slackalaxy@gmail.com>2020-05-22 23:39:23 +0700
committerWilly Sudiarto Raharjo <willysr@slackbuilds.org>2020-05-22 23:39:23 +0700
commitec11283d0bb9ac35f712d56176ebdc8e649ccdc9 (patch)
treeff553cc5865623cf9e38936f6bafd0434911d324 /academic/muscle/README
parentc57f7c320114e3d8ad233b9626e140dbcb2ceb27 (diff)
downloadslackbuilds-ec11283d0bb9ac35f712d56176ebdc8e649ccdc9.tar.gz
academic/muscle: Update script and added manual page.
Signed-off-by: Willy Sudiarto Raharjo <willysr@slackbuilds.org>
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@@ -3,7 +3,29 @@ nucleotide sequences. A range of options is provided that give you the
choice of optimizing accuracy, speed, or some compromise between the
two.
-For details and citation:
-Edgar, R.C. (2004) MUSCLE: multiple sequence alignment with high
-accuracy and high throughput. Nucleic Acids Res. 32(5):1792-1797.
-doi:10.1093/nar/gkh340
+Fast, accurate and easy to use
+MUSCLE is one of the best-performing multiple alignment programs
+according to published benchmark tests, with accuracy and speed that
+are consistently better than CLUSTALW. MUSCLE can align hundreds of
+sequences in seconds. Most users learn everything they need to know
+about MUSCLE in a few minutes—only a handful of command-line options
+are needed to perform common alignment tasks.
+
+NOTE about the "-stable" option no longer being supported:
+The "-stable" option had a bug, which sometimes resulted in incorrect
+alignments to be produced. The author has created a python script to
+be used as a workaround. The SlackBuild includes it and its usage is:
+
+ python muscle-stable.py input.fasta aligned.fasta > stable.fasta
+
+Papers
+There are two papers. The first (NAR) introduced the algorithm, and is
+the primary citation if you use the program. The second (in BMC Bio-
+informatics) gives more technical details, including descriptions of
+non-default options.
+
+Edgar, R.C. (2004) MUSCLE: multiple sequence alignment with high
+accuracy and high throughput. Nucleic Acids Res. 32(5):1792-1797
+
+Edgar, R.C. (2004) MUSCLE: a multiple sequence alignment method with
+reduced time and space complexity BMC Bioinformatics, (5) 113