MMuFLR: missense mutation and frameshift location reporter

Area of Science:

• Bioinformatics
• Genomics
• Cancer Research

Background:

• Identifying cancer-specific protein targets is crucial for immunotherapy development.
• Existing tools may not efficiently detect specific mutation types in highly expressed genes.

Purpose of the Study:

• To introduce the Missense Mutation and Frameshift Location Reporter (MMuFLR) workflow.
• To provide a reliable method for identifying novel protein candidates for cancer immunotherapy.

Main Methods:

• MMuFLR is a Galaxy-based workflow analyzing paired-end RNA sequencing data.
• It specifically identifies small frameshift and missense mutations in protein-coding genes.
• The workflow filters out known SNPs, low-quality reads, and poly-A/T sequences.

Main Results:

• MMuFLR reliably detects frameshift and missense mutations.
• It pinpoints the location and amino acid sequences of novel protein candidates.
• Results are formatted for direct input into epitope evaluation tools.

Conclusions:

• MMuFLR offers a valuable tool for cancer researchers.
• It facilitates the discovery of potential immunotherapy targets.
• The workflow enhances the identification of novel protein candidates from RNA-seq data.