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SIFTER: Statistical Inference of Function Through Evolutionary Relationships

SIFTER software and instructions reside at the Brenner Lab at UC Berkeley, although I am still actively maintaining the code.

This software uses a statistical model to predict protein molecular function for unannotated proteins using functional annotations from a set of homologous proteins, described in

B.E. Engelhardt, M.I. Jordan, J.R. Srouji, and S.E. Brenner (2010) Genome-scale phylogenetic function annotation of large and diverse protein families. Submitted.

Sparse factor analysis (SFA)

This software uses ECME to compute a sparse, low-rank matrix factorization for a given matrix, as described in

Engelhardt BE, Stephens M (2010) "Analysis of population structure: a unifying framework and novel methods based on sparse factor analysis." PLoS Genetics 6(9):e1001117.

Download C++ code and instructions for SFA 1.0 and further documentation for the SFA model.