
-- Basic workflow using the MetWAMer package --

Michael E Sparks (mespar1@iastate.edu)
31 October 2007

(Utility-specific usage conventions can be observed
by executing each program without parameters.)

1) Having a set of fasta-formatted genomic sequences,
   derive indexFasSeq'ed indices for them, using
   indexFasSeq

2) Having access to the TIGR XML-formatted annotation
   for those genomic templates, derive training data
   using parse_tigrxml_cds

3) If clustering is wanted, extract the TISs and cluster
   using calc_medoids.  The resulting indices can be
   used to partition data accordingly.

4) Develop a negative TIS WAM using train_MetWAM

5) Develop positive TIS WAM(s) using train_MetWAM

6) If clustering, extract TISs and develop PWMs
   using train_MetPWM

7) Develop Markov chains using train_MC

8) For the perceptron-based method, derive feature
   vector representations of training instances using
   build_featvecs

9) For the perceptron-based method, train the neuron
   using train_perceptron

10) Identify potential TISs in a set of fasta-formatted
    sequences using MetWAMer.CDS

