A new version of Progenesis CoMet for metabolomics data analysis

Right now, we have a beta version of Progenesis CoMet v2.0 that we’d love to share with you. The first version was launched back in May 2011 and since then we have been working hard to improve it based on your feedback.

It continues to solve the main challenges you face, by giving you confidence in quantitative results and providing a single unified workflow for metabolomics data analysis. However, a major change is that the software now deconvolutes the different ions formed during experimental analysis of metabolites, recombining them to provide accurate measurements of each compound. This massively reduces the complexity of generating reliable compound identifications of biological interest.

I’ll cover the important changes in v2.0 here, including deconvolution of compound ions, but you can see it for yourself by asking for a demo.

The Progenesis CoMet v2.0 workflow

select-adductsProgenesis CoMet is platform independent; it analyses data from Thermo, Agilent, Bruker and Waters instruments. It also supports the mzXML, mzML and NetCDF cross-vendor file formats. Prior to data import you are now prompted to select from a list of possible adducts present in your samples. If a specific adduct is not listed, it can easily be added to the list.

Next comes accurate retention time alignment, which lies at the heart of all Progenesis software. The result is that all compound ions are in the same location and co-detected across all sample runs to produce a complete data set. No missing values means data satisfies the conditions for valid multivariate statistical tests.

Peak picking
Once you have organised your runs into the correct experiment design, you can apply peak picking. You can change the peak picking parameters to ensure optimal detection for each experiment. The new peak picking screen has the added advantage of displaying an ion intensity map of the results, so you can review this and optimise before proceeding.


I should say the same peak picking algorithm from v1.0 is used to detect compound ions in complex samples, including overlapping compound ions, which helps generate accurate quantification data.

Reviewing compounds
This is where the results of quantification and identification are automatically brought together. All the compound ions are automatically deconvoluted to provide accurate quantitation of each compound. Here you can find the compounds of biological interest based on differences in abundance, Anova p-values between experimental groups and other measurements. The Review Compounds screen has been enhanced with a 3D view, a feature to automatically accept a compound identification based on a search score threshold and a visual display of isotope peak distribution.


Identifying compounds
We have developed a brand new search tool, MetaScope, integrated into the software. In a single-click you can search your own data and return compound identifications directly back into the workflow. It is that easy! You can run a search of neutral mass, or m/z along with retention time data against a flat file of compound identifications that you curate. The results, with a MetaScope compound identification score applied, are automatically associated with the compounds in Progenesis CoMet.

You also have the added flexibility of searching for compound identifications by:

  • export exact mass and RT data via a .csv file
  • export data to perform a METLIN search.

We can responsively support any new search options required by developing plug-ins to suit your own workflows. If you have something in mind, simply ask us.


Reviewing deconvolution
The Review Deconvolution screen allows you to review the quantified compounds, including any identification results, in terms of the component compound ions. The compound’s ions are displayed in a montage of ion map areas, with locations of missing adduct forms also shown. Mass spectra and extracted ion chromatograms are also displayed for each compound ion, so you can see how they similar they are. This is useful in visually checking the quality of data underlying each quantified compound.


If any compounds have an ion whose profile appears as an outlier in terms of its m/z and RT characteristics, within expected limits, it can be removed. Likewise, you have the opportunity to look if a compound ion appears at an expected position on the ion intensity map and, if it is present, add it to the compound quantification calculation.


Finally, you can export data to perform further analysis e.g. pathway analysis as well as explore your data in even greater detail with Progenesis Stats. This includes Principal Components Analysis, Correlation Analysis, False Discovery Rate q-values and now a view of how adduct abundance varies between runs.

Progenesis CoMet v2.0 beta in summary…

Progenesis CoMet is designed to give you confidence in results from quantitative analysis of metabolomics data in discovery experiments. It does this using a simple workflow that avoids the need for working with multiple, disjointed, external tools. The result is that you can reliably quantify and then identify relative differences in compound abundance that help explain the biological changes within your samples.

If you would like to see Progenesis CoMet v2.0 (beta) and trial it on your own data, contact us and we can arrange this with you.

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  1. […] to bring some of your own data if you would prefer. If you’re interested in metabolomics, the Progenesis CoMet v2.0 Beta (not yet available to download from the website) will be on show – so its a great opportunity to […]