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+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.
+