Progenesis QI for proteomics software enables you to quantify and identify proteins in your complex samples using the advantages of label-free analysis. With support for all common vendor data formats and a highly visual guided workflow, Progenesis QI for proteomics enables you to rapidly, objectively and reliably discover proteins of interest from single or fractionated samples and using multi-group experimental designs. As well as conventional data-dependent analysis (DDA), Progenesis QI for proteomics supports the analysis of Waters MSE and HDMSE data-independent (DIA) data. Uniquely, the software also takes advantage of the additional dimension of resolution offered by Ion Mobility separations to give improvements in accuracy and precision of identification and quantification.
Label-free LC‑MS provides a wide range of benefits when compared to labeled techniques, including:
Consistently measure the peptides in all samplesThe 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 abundanceProgenesis 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 peptidesProgenesis 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. |
Progenesis QI for proteomics is highly flexible in that it can be used to search both DIA and DDA data using a variety of user-selectable search engines. Data from multiple searches can be combined in a single experiment. If required, the software can be supplied with ProteinLynx Global Server (PLGS) facilitating the analysis of Waters MSE, HDMSE, DDA and HD-DDA data.
Guided data-processing workflowThe 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).
|
How do we understand the protein differences in our experiment? One option is to use Pathway Analysis, which determines which biological pathways are implicated in the data and thus provides the next level of information for biological contextualisation. In Progenesis QI for proteomics, we have provided export tools to easily and quickly interface with third-party Pathway Analysis programs.
Progenesis QI for proteomics is instrument platform independent supporting LC-MS data from Waters, Thermo, ABSciex, Agilent, and Bruker. Also supported are universal formats such as .mzML, .mzXML, and NetCDF.
For more information about Progenesis QI for proteomics, please see www.nonlinear.com.