VIQoR: a web service for Visually supervised protein Inference and protein Quantification

Abstract

MotivationIn quantitative bottom-up mass spectrometry (MS)-based proteomics the reliable estimation of protein concentration changes from peptide quantifications between different biological samples is essential. This estimation is not a single task but comprises the two processes of protein inference and protein abundance summarization. Furthermore, due to the high complexity of proteomics data and associated uncertainty about the performance of these processes, there is a demand for comprehensive visualization methods able to integrate protein with peptide quantitative data including their post-translational modifications. Hence, there is a lack of a suitable tool that provides post-identification quantitative analysis of proteins with simultaneous interactive visualization. ResultsIn this article, we present VIQoR, a user-friendly web service that accepts peptide quantitative data of both labeled and label-free experiments and accomplishes the processes for relative protein quantification, along with interactive visualization modules, including the novel VIQoR plot. We implemented two parsimonious algorithms to solve the protein inference problem, while protein summarization is facilitated by a well established factor analysis algorithm called fast-FARMS followed by a weighted average summarization function that minimizes the effect of missing values. In addition, summarization is optimized by the so-called Global Correlation Indicator (GCI). We test the tool on three publicly available ground truth datasets and demonstrate the ability of the protein inference algorithms to handle degenerate peptides. We furthermore show that GCI increases the accuracy of the quantitative analysis in data sets with replicated design. Availability and implementationVIQoR is accessible at: http://computproteomics.bmb.sdu.dk:8192/app_direct/VIQoR/ The source code is available at: https://bitbucket.org/vtsiamis/viqor/ Contactveits@bmb.sdu.dk Supplementary informationSupplementary data are available at Bioinformatics online.