Label-free protein quantification software tools | Mass spectrometry-based untargeted proteomics
There is a great interest in reliable ways to obtain absolute protein abundances at a proteome-wide scale. To this end, label-free LC-MS/MS quantification methods have been proposed where all identified proteins are assigned an estimated abundance.
Allows to analyze small molecule concerning liquid chromatography-mass spectrometry (LC-MS) data. Progenesis QI includes a search engine named Metascope. The characteristics of this tool (peak modelling, analysis workflow, algorithms) is to help users to handle highly complex samples. It enables ID of compounds using up to 5 different criteria including: (1) Collisional Cross-Section (CCS), (2) RT, (3) mass, (4) fragmentation, (5) spectra. It also permits users to create their own mass, RT or fragment spectra databases.
A quantitative proteomics software package designed for analyzing large mass-spectrometric data sets. MaxQuant is specifically aimed at high-resolution MS data. Several labeling techniques as well as label-free quantification are supported.
Offers a platform dedicated to determination and relative abundance quantification of proteins. ProteinPilot consists of two main algorithms: (i) ProGroup, that allows users to generate reports about the proteins which are detected in a sample and; (ii) Paragon, which enables large-scale searching to perform an improved protein identification by tandem mass spectrometry with a peptide identification approach.
Provides an integrated mass-informatics platform for quantitative and qualitative proteomics research. PLGS is a software based on open and pluggable system architecture, providing scalable, automated workflow for high-throughput data processing and data interpretation. It also includes project and database management tools with integrated results visualization and reporting.
Recognizes and quantifies protein in biologic complex samples. Proteome Discoverer covers a wide range of possible proteomic investigations from proteins and peptides identification to post-translational modification. It searches in many databases and several dissociation technics for performing complete studies. This tool automatizes data analyze and allows researchers to represent results thanks to modules like gene ontology (GO) enrichment.
Offers solutions for discovery proteomics. PEAKS X enables protein identification and quantification, analysis of post-translational modifications (PTMs) and sequence variants (mutations), as well as peptide/protein de novo sequencing. The software includes a feature-based identification method to increase sensitivity and maximize peptide identification efficiency for in-depth shotgun analysis of complex proteomes.
Allows visualization and validation of peptide identification results directly on the raw mass spectrometric data. MSQuant iteratively recalibrates MS data thereby significantly increasing mass accuracy leading to fewer false positive peptide identifications. Algorithms to increase data quality include an MS(3) score for peptide identification and a post-translational modification (PTM) score that determines the probability that a modification such as phosphorylation is placed at a specific residue in an identified peptide. MSQuant supports relative protein quantitation based on precursor ion intensities, including element labels (e.g., (15)N), residue labels (e.g., SILAC and ICAT), termini labels (e.g., (18)O), functional group labels (e.g., mTRAQ), and label-free ion intensity approaches.