Progenesis LC-MS product overview

Progenesis LC-MS is an advanced proteomics research solution for your label-free quantitative analysis. It has a unique alignment based approach that gives you the following advantages:

An easy-to-use, visual approach means you can use Progenesis LC-MS to quickly interpret complex data. Try it with your own data and read about our validated workflows for differential expression analysis and protein characterisation.

Benefits for your analysis

• Quantification of all peptides followed by independent LC-MS/MS identification. This enables targeted MS/MS acquisition for low abundant peptides as well as supporting data dependant analysis.
• Quantitative peptide ion analysis is automatically collated with protein information. This helps you answer biological questions.
• No retention time or ID based matching required. Protein identification is supported but not necessary for quantitative analysis.
• Handles complex samples. This reduces the need for offline pre-fractionation, simplifying sample handling and allowing you to run more replicates without needing more instrument time.

Features of the unique analysis approach

The current version of Progenesis LC-MS has been developed based on user feedback to keep you up to date with the demands of label-free LC-MS data analysis.

Latest features available in version 2.6 »

Data Import - Supports common formats: .mzXML, Waters .RAW (including data with lock mass and dead time correction), Thermo .RAW, Agilent .d and .NetCdf file formats.

Peak modelling and data reduction decreases file sizes by an order of magnitude without compromising quantitative accuracy. You can import, view and analyse single LC-MS data files and quickly build inclusion lists for targeted LC-MS/MS.

Data Alignment - Automatic retention time alignment allows the creation of a single aggregate run containing all of the peptide ions from your runs. The total ion chromatogram (TIC) view allows you to verify the accuracy of automatic alignment, which provides an additional quality check and increased confidence in your results. Manual vectors can be used to align runs that are challenging to overlay.

Label Free Detection and Quantification - A detected feature outline map is generated from the aggregate run containing all of the peptide ions in your experiment. These outlines are passed to each of the individual runs for detection and quantification. The sensitivity of detection can be adjusted, and a minimum retention time window can be set so any peptide eluted over a shorter period of time will be rejected. This gives you full control over the feature detection process.

The sophisticated detection algorithm handles complex samples and can discern overlapping peptide ions. It is also able to distinguish between streaks and peptide ions. The end result is highly accurate detection which saves time further down the workflow. It also generates complete datasets containing no missing values that allow you to get reliable results from the multivariate statistical tools.

Filtering - Remove any peptide ions from your runs using a range of criteria. You can highlight an area on the run that you wish to exclude and remove peptide ions with a certain charge or a certain number of isotopes. Filtering out peptide ions that you wish to exclude at this stage will save time later in the analysis.

Normalisation - You can see the results of normalisation on a scatter plot and the normalisation factor for each run. You can then take corrective action to ensure experimental quality is maintained. You have the option to use raw abundances or normalised abundances in your experiment. For example, if the assumption that a significant number of peptides are not changing is invalid, you can turn off normalisation.

Experiment Design Setup - Set up experiment designs for all the comparisons you wish to make. You can choose to set up "between-subject" experiment designs and "within-subject" experiment designs (e.g. timecourse experiments).

View Results - Peptide Ion Selection - You can review statistically ordered lists of peptide ions for all the experiment designs you set up using a range of displays. Peptide ions are ordered by p-value from the one way ANOVA analysis. Any editing of detected peptide ions is made as a single edit on the aggregate run and then propagated across all runs.

A comprehensive data table contains all of the information relating to each peptide in the same location. Peptide ions can be grouped in multiple ways using the tags feature which allows you to explore complex relationships or quickly generate inclusion lists for MS-MS identification.

Progenesis Stats - Progenesis Stats is a simple-to-use tool that allows you to easily apply powerful statistical analysis and make reliable conclusions. Principal Components Analysis (PCA), Correlation Analysis, Power Analysis and q-values (false discovery rate adjusted p-values) are included to explore the trends in your data.

The tests enable you to measure:

• How your data clusters within your experiment. This can validate the hypothesis used to create the experimental groups and indicate any outliers in your data
• How similar peptides are in terms of their expression profile. This can help you find additional peptides involved in processes you are studying
• The power of your experiment. This will tell you if you've run enough replicates for valid results and is becoming a requirement for publishing research

More »

Peptide Search - A simple, visual way to validate and select MS/MS spectra for database searches using Phenyx, ProteinLynx Global SERVER™ (PLGS), Mascot™ or SEQUEST. Your search results are imported and identifications automatically displayed alongside the corresponding peptide ion. You can filter out spectra and reduce the size of spectra that you export with a range of options. This makes file sizes manageable for search engines and reduces the time taken to perform your database searches. Using these options also improves the quality of search results you get back.

Peptide Filter - When peptide and protein identifications from database searches are imported you can filter out results at this stage using a comprehensive range of criteria to reduce the number of incorrect assignments. Examples of identifications you may want to remove could be those associated with hypothetical proteins, those with a low score, or those with an incorrect taxonomy. As a result you can save time reviewing your results and quickly focus on the relevant data.

Protein View - Bring together quantitative LC-MS data and qualitative LC-MS/MS results at the protein level to define any proteins of interest between experimental groups based on expression change with ANOVA (p-value). Easily resolve "conflicts" in your results where a peptide sequence is associated with more than one protein as a result of a database search. Tags applied at the peptide level are now displayed associated with the proteins they relate to. This allows you to highlight interesting proteins based on significant measurements from the LC-MS data.

Report Results - A final report can be generated in HTML format to display and share the information from your experiment. An aggregate LC-MS run view can be included that shows the location of selected peptides of interest. The report is interactive, so clicking on a protein of interest shows you the peptides that were associated with it from your analysis and vice versa. You can export all peptide and protein measurements, including raw data needed for spectral counting.