Abstract

Current tools for visualization and integration of proteomics with other omics datasets are inadequate for large-scale studies and capture only basic sequence identity information. We developed PoGo for mapping peptides identified through mass spectrometry to a reference genome to overcome these limitations. PoGo exhibited superior performance over other tools on benchmarking with large-scale human tissue and cancer phosphoproteome datasets. Additionally, extended functionality enables representation of single nucleotide variants, post-translational modifications and quantitative features.