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author | Jim Johnson <jj@umn.edu> |
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date | Tue, 04 Jun 2013 09:03:30 -0500 |
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1 MMuFLR: Missense Mutation and Frameshift Location Reporter | |
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. | |
3 | |
4 The parameter settings in the workflows are set for human samples. | |
5 | |
6 To execute MMuFLR create a Galaxy history and upload the four input files: | |
7 1. tumor sample forward reads fastq | |
8 2. tumor sample reverse reads fastq | |
9 3. dbSNP VCF file | |
10 4. additional exclusions VCF | |
11 | |
12 Select Galaxy-Workflow-MMuFLR_v1.4.ga to Run | |
13 Set input files for Galaxy-Workflow-MMuFLR_v1.4.ga | |
14 For the Tophat step, set: | |
15 - Mean Inner Distance between Mate Pairs | |
16 - Std. Dev for Distance between Mate Pairs | |
17 | |
18 If you have reads from matched tumor/normal tissue samples, | |
19 run the Galaxy-Workflow-MMuFLR_Human_germline_v1.4.ga on the noraml samples with inputs: | |
20 1. normal sample forward reads fastq | |
21 2. normal sample reverse reads fastq | |
22 3. dbSNP VCF file | |
23 and use the final VCF as input 4 "additional exclusions VCF" in the Galaxy-Workflow-MMuFLR_v1.4.ga workflow. | |
24 |