Consistently measure the peptides in all samples

The quantify-the-identify approach taken by Progenesis QI for proteomics allows you to automatically align the features in each sample and create an in-silico aggregate map containing every peptide in the complete sample set. This aggregate map is used to consistently detect and quantify features across all samples and create a data matrix with no missing values, irrespective of the number of samples or replicates. This means maintenance of statistical power in the analysis with no sacrifice of potentially important data, without the need for imputation. 

QC Metrics to evaluate the quality of LC-MS input data (v2.0 feature)

QC metric tools aim to prevent you wasting valuable time performing analysis on sub-optimal LC-MS data, and include readouts such as LC peak width, feature dynamic range, precursor mass error, missed cleavage count and peptide per protein count. In addition, these QC metric tools can be used to guide process optimization and troubleshooting.

Reliable quantification based on ion abundance

Progenesis QI for proteomics quantifies peptides based on ion abundance. Version 2.0 offers the facility to utilize a spiked internal standard and user selectable "HiN" metrics to estimate absolute abundance.

Protein quantification based on unique peptides

Progenesis QI for proteomics automatically combines peptide ion quantification and identification from search results and if desired, allows the quantification of proteins based only on unique peptides.

Guided data-processing workflow

The menu-guided workflow in Progenesis QI for proteomics helps to guide you through the experimental steps in the software. If required, automation routines allow you to seamlessly move through multiple stages to maximize opportunities for unsupervised overnight and weekend data processing (v2.0 feature).

• Data import
• Automatic reference run selection and alignment
• Automatic peak picking and normalization
• Automatic protein quantification
• Protein database search