LFQ-Analyst: an interactive platform to analyse & visualise proteomics data processed with MaxQuant

Presenter: Dr Anup Shah, Monash Bioinformatics Platform and Monash Proteomics & Metabolomics Facility, Monash University Proteomics data, generated from advanced mass-spectrometers, is often difficult to interpret for beginners. LFQ Analyst offers streamlined statistical analysis and visualization of such complex label-free quantitative proteomics datasets. Relative label-free quantification (LFQ) of shotgun proteomics data using precursor (MS1) signal intensities is one of the most commonly used application to comprehensively and globally quantify proteins across biological samples and conditions. Owing to the popularity of the technique, software suites like MaxQuant have been developed to extract, analyse and compare spectral features and report quantitative information of peptide, protein and even post-translationally modified (PTM) sites. There is still a lack of accessible tools for the interpretation and downstream statistical analysis of these complex datasets. Therefore, we developed LFQ-Analyst; a web application to streamline differential expression analysis and visualisation of label-free quantitative proteomics datasets. This tool provides a wealth of user-analytics features including differential expression, dimensionality reduction, clustering and different quality checks in tabular and graphical forms to facilitate exploratory and statistical analysis of quantitative datasets produced from proteomics investigations. LFQ-Analyst was designed to use sophisticated techniques for analysis, yet be accessible to researchers without extensive proteomics experience. Furthermore, users can automatically generate comprehensive analysis reports. For more information visit LFQ-Analyst (https://bioinformatics.erc.monash.edu...) or consult the paper (https://doi.org/10.1021/acs.jproteome....