MMuFLR: Missense Mutation and Frameshift Location Reporter
analyzes Next Generation Sequencing (NGS) paired read RNA-seq output to reliably identify small frameshift mutations, as well as missense mutations, in highly expressed protein-coding genes. MMuFLR ignores known SNPs, low quality reads, and poly-A/T sequences. For each frameshift and missense mutation identified MMuFLR provides the location and sequence of the amino acid substitutions in the novel protein candidates for direct input into epitope evaluation tools.

The parameter settings in the workflows are set for human samples.

To execute MMuFLR create a Galaxy history and upload the four input files: 
  1. tumor sample forward reads fastq 
  2. tumor sample reverse reads fastq 
  3. dbSNP VCF file 
  4. additional exclusions VCF

Select Galaxy-Workflow-MMuFLR_v1.4.ga to Run
Set input files for Galaxy-Workflow-MMuFLR_v1.4.ga
For the Tophat step, set:
 - Mean Inner Distance between Mate Pairs
 - Std. Dev for Distance between Mate Pairs

If you have reads from matched tumor/normal tissue samples, 
run the Galaxy-Workflow-MMuFLR_Human_germline_v1.4.ga on the noraml samples with inputs:
  1. normal sample forward reads fastq 
  2. normal sample reverse reads fastq 
  3. dbSNP VCF file 
and use the final VCF as input 4 "additional exclusions VCF" in the Galaxy-Workflow-MMuFLR_v1.4.ga workflow.