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CAFS: Clustering Analysis of Functional Shifts
-CAFS is a simple and fast method for Clustering functionally divergent (FD)
-genes by Functional Category.
+CAFS is a simple and fast method for Clustering functionally divergent
+(FD) genes by Functional Category.
-The method implemented in CAFS is one of several sequence-based methods
-for identifying the 'interesting' subset of substitutions that might
-underpin functional divergence. These methods are based on the idea of that
-functionally-important residues are highly conserved, so that evolutionary
-rates tend to be low at important sites. Functional divergence can then be
-identified by comparing rates (or levels of conservation) between two
-clades of proteins at a homologous site. Alternatively, a significant
-change in amino acid identity (such as a large, positively-charged residue
-in one group of sequences versus a small, neutral residue in the other)
-could indicate functional divergence even without a change in rate.
+The method implemented in CAFS is one of several sequence-based
+methods for identifying the 'interesting' subset of substitutions
+that might underpin functional divergence. These methods are based
+on the idea of that functionally-important residues are highly
+conserved, so that evolutionary rates tend to be low at important
+sites. Functional divergence can then be identified by comparing
+rates (or levels of conservation) between two clades of proteins at
+a homologous site. Alternatively, a significant change in amino acid
+identity (such as a large, positively-charged residue in one group of
+sequences versus a small, neutral residue in the other) could indicate
+functional divergence even without a change in rate.
This program analyses alignments and provides the user with the best
putative sites under functional divergence.
-NOTE: This only repackages the 64bit binary provided from upstream. A 32bit
-executable is not available.
+NOTE: This only repackages the 64bit binary provided from upstream. A
+32bit executable is not available.
Citing:
Caffrey BE, Williams TA, Jiang X, Toft C, Hokamp K, Fares MA (2011).