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2
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1 MMuFLR: Missense Mutation and Frameshift Location Reporter
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2 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.
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3
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4 The parameter settings in the workflows are set for human samples.
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5
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6 To execute MMuFLR create a Galaxy history and upload the four input files:
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7 1. tumor sample forward reads fastq
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8 2. tumor sample reverse reads fastq
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9 3. dbSNP VCF file
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10 4. additional exclusions VCF
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11
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12 Select Galaxy-Workflow-MMuFLR_v1.4.ga to Run
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13 Set input files for Galaxy-Workflow-MMuFLR_v1.4.ga
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14 For the Tophat step, set:
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15 - Mean Inner Distance between Mate Pairs
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16 - Std. Dev for Distance between Mate Pairs
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17
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18 If you have reads from matched tumor/normal tissue samples,
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19 run the Galaxy-Workflow-MMuFLR_Human_germline_v1.4.ga on the noraml samples with inputs:
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20 1. normal sample forward reads fastq
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21 2. normal sample reverse reads fastq
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22 3. dbSNP VCF file
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23 and use the final VCF as input 4 "additional exclusions VCF" in the Galaxy-Workflow-MMuFLR_v1.4.ga workflow.
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24
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