Poster Presentation HUPO 2019 - 18th Human Proteome Organization World Congress

LFQ-Analyst: An easy-to-use interactive web-platform to analyze and visualize quantitative proteomics data (#832)

Anup D. Shah 1 2 , Robert J.A Goode 1 , Cheng Huang 1 , David R. Powell 2 , Ralf B. Schittenhelm 1
  1. Monash Proteomics and Metabolomics Facility, Monash University, Clayton, VIC, Australia
  2. Monash Bioinformatics Platform, 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 the technique, several software suites – such as 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 a web application developed to perform differential expression analysis with “one click” and to visualize label-free quantitative proteomic datasets preprocessed with the popular software suite MaxQuant.  LFQ-Analyst provides a wealth of user-analytic features including differential expression analysis, dimensionality reduction, clustering and various quality control checks in tabular and graphical format to facilitate exploratory and statistical analysis of label-free quantitative datasets. LFQ-Analyst is freely available at https://bioinformatics.erc.monash.edu/apps/LFQ-Analyst