Scimm is an unsupervised method for clustering metagenomic sequences using interpolated Markov models in a framework similar to the k-means clustering algorithm. Currently, we suggest LikelyBin and CompostBin to initially partition a subset of the sequences in order to initialize the IMMs, and the package provides wrapping code for these programs. PhyScimm initially partitions the sequences using a supervised classification algorithm Phymm, which performs better in high complexity datasets and when the species encountered are well-represented in public databases.
0.3.0 release - 2/9/2012
Numerous small, but important bug fixes.

0.2.0 release - 11/27/2010
Added PhymmBL v3 compatibility to PhyScimm.

0.1.1 release - 6/25/2010
Fixed a few installation and fasta header issues.

0.1.0 release - 4/26/2010
The first public release of Scimm and PhyScimm is now available for download. See the manual for instructions on how to set up and run the programs