Oral Presentation 25th Annual Lorne Proteomics Symposium 2020

LFQ-Analyst, an interactive web-platform to analyse quantitative proteomics data (#44)

Anup Shah 1 , Robert JA Goode 1 , Cheng Huang 1 , David R Powell 1 , Ralf Schittenhelm 1
  1. Department of Biochemistry and Molecular Biology, Monash University, Clayton, VIC, Australia

Relative label-free quantification (LFQ) of shotgun proteomics data using precursor (MS1) signal intensities is one of the most commonly used applications to comprehensively and globally quantify proteins across biological samples and conditions. Due to the popularity of this technique, several software packages – such as the popular software suite MaxQuant – have been developed to extract, analyze and compare spectral features, and to report quantitative information of peptides, proteins and even post-translationally modified (PTM) sites. However, there is still a lack of accessible tools for the interpretation and downstream statistical analysis of these complex datasets, in particular for researchers and biologists with no or only limited experience in proteomics, bioinformatics and statistics.
We have therefore created LFQ-Analyst, which is an easy-to-use, interactive web application developed to perform differential expression analysis with “one click” and to visualize label-free quantitative proteomic datasets preprocessed with MaxQuant. LFQ-Analyst provides a wealth of user-analytic features and offers numerous publication-quality result graphics to facilitate statistical and exploratory analysis of label-free quantitative datasets. LFQ-Analyst, including an in-depth user manual, is freely available at https://bioinformatics.erc.monash.edu/apps/LFQ-Analyst.