Earlier this week, we released the first version of Progenesis CoMet to metabolomics (and other) researchers worldwide. Using it, you’ll be able to discover and reliably quantify the compounds that are significantly changing in your samples.
Before we started development on CoMet, we knew that data analysis in the field of metabolomics could be a frustrating, disjointed experience. Typically, many separate analysis tools and databases are used, with manual intervention to move the data from one stage of analysis to the next and little opportunity to visually explore the data.
Consequently, a key goal of CoMet is to streamline the metabolomics workflow; and it’s that streamlined workflow we’ll examine in this blog post.
The CoMet workflow
The workflow in Progenesis CoMet builds on the strengths of its sister products in the Progenesis range:
- Import your data
Support for file formats from a range of different vendors is provided as standard, for both LC-MS and GC-MS data. Additionally, CoMet supports the cross-vendor mzXml file format, for which there are many free conversion tools. This wide-ranging support saves time and money, as there’s no need for training on lots of different software packages.
- Review the chromatography
A quiet strength of the Progenesis range is the instant feedback provided by its data visualisations. CoMet is no exception; displaying each run as an ion intensity map immediately after import helps you check for problems in the chromatography, reducing the likelihood of wasted analysis time:
- Correct the retention time drift
Correcting for drift in the ions’ retention times is a fundamental requirement for robust statistical analysis downstream. In CoMet, this is achieved in the Alignment screen, with clear visual feedback giving confidence in the accuracy of the process and an instant quality check.
- Peak picking
Following alignment, a peak picking algorithm, designed specifically to work with small molecule data, is used to locate the ions in your aligned runs. This guarantees that the same ion pattern is measured in all of your runs, thereby allowing valid multivariate statistics to be generated based on the ion abundances.
- Identify the interesting ions
CoMet uses information about the samples in your experiment to provide differential abundance data for each of your compound ions. These can then be filtered to show only those that exhibit interesting changes before integrating with an external database to provide the compounds’ identifications.
- Review compound identifications
The final stage of CoMet’s workflow groups the ions that share the same compound identifications. Measurements for the compound as a whole are then presented, including all adduct forms and charge states:
Often, you’ll find that a compound may, in fact, be any one of a range of different compounds. The Review Compounds screen (above) presents this information clearly. A breakdown for each compound also presents information on each of its contributing ions, helping you determine the true identification. Even where an ion has no identification, measurements are still available to help you target subsequent compound ID searches.
Finally, in common with the rest of the Progenesis range, the statistics module allows you to explore your data in even greater detail, adding Principal Components Analysis, Correlation Analysis, False Discovery Rate q-values and more to your toolset.
Try it for yourself
If you think Progenesis CoMet can help your small molecule research, click here to arrange a demo now. We’re confident we can help, and we’d love to hear your feedback.