TITLE: “moPepGen: a fast custom database generator from multi-omics data for proteogenomics.”
ABSTRACT: Cancers are driven by genomic variants such as SNV (single nucleotide variants) and INDEL, often accompanied by many transcriptional variants. Modern mass spectrometry based proteomics is able to identify and quantify peptides and proteins comprehensively, however the variant-harboring peptides that are absent in canonical databases are largely under-studied. A common problem in custom database construction is the large number of combinations of variants to consider. Thus major proteogenomic studies often choose a strategy that only captures peptides harboring a single variant. Existing algorithms also suffer from limited sources of variation. We developed moPepGen (multi-omics peptide database generator) that aims at accelerating proteogenomic researching by generating custom peptide database from variety of genomic and transcriptional variants. MoPepGen uses a graph-based algorithm that achieves a linear time complexity in integrating variants in contrast to the exponential complexity of exhaust searching. MoPepGen integrates variants from a variety of sources including SNV, indel, transcription fusion, alternative splicing, RNA editing, and circRNA. It is able to generate peptides harboring any combinations of variants on the single peptide. MoPepGen is also highly extensible for other types of genomic and transcriptional variants.
