AutoLogis is designed to help automate the process of assigning peaks in spectra from complex organic matter samples, or other similar complex samples, producing predominantly singly charged ions; e.g. metabolomics, crude oil, food aqueous extracts etc.

AutoLogis can assign peaks in mass spectra using two different methods: accurate mass and mass difference.  In the accurate mass approach, AutoLogis will use both the accurate mass and isotopic distribution to assign identities to ions in spectra.  In the mass difference approach, it uses the accurate mass difference between a known peak and an unknown peak to infer the formula of the unknown peak.  By building a network of links between peaks in a spectrum you can assign most peaks from a single starting peak.  Both approaches are highly automated and can be applied to batches of many (even hundreds or thousands) of spectra.

AutoLogis can also be used to help sequence proteins, ab initio, by help to highlight peaks that are separated by amino acid residue masses.

Outputs

AutoVectis can output its assignments in many different formats including publication ready graphs, tables, to Excel, as SQLite databates etc. If you need your results in a specific format for onwards processing, we will ensure that you have access to what you need.

Assignment by inference – mass difference

In many spectra, a large proportion of the peaks can be assigned by inference:  you can infer the formula of an unknown peak based on the mass difference or defect between that peak and a peak that is already assigned.  This is the process behind the well known Kendrick mass analysis method.

The Kendrick method is commonly undertaken using the CH₂ mass defect.  AutoLogis will search for any common defect in your data, that is comprised of C, H, O, N or S.  Alternatively you can add known links of your own.  It connects all the peaks in the spectrum to all other peaks where the mass difference is assigned – this is called the connections net.

Then you must assign at least one peak in the spectrum – preassigned peaks like this are known as seeds.  Using the connections net, AutoLogis can then infer the formulae of all peaks connected to these seeds.  And, to all peaks connected to the newly inferred peaks – and so on.

AutoLogis also makes it easy to edit the assigned list (deleting suspicious assignments) and to recalibrate your data, based on the assignments.

AutoLogis Data Viewing

AutoLogis has a dedicated results viewing tool to help you review and expore your results.

AutoLogis can display your data as mass spectral, two-dimensional Kendrick mass defect space view; van Krevelen diagrams; double bond equivalence and z plots; and in mass error plots.  This data can be easily exported as figures or even directly to Excel.  The heat map outputs can be exported as images or as vector files.  Having these views exported as vector files makes it very easy for users to create publication quality images for journal papers or posters, with no fears about pixelation or losses in image quality.

AutoLogis can also generate 3D outputs for the assigned peaks.  This can be very useful for visualizing complex datasets.

This 3D display allows the user to manipulate the view to let them explore the 3D shape of their data.

New Isotopic Distribution Capabilities

AutoLogis has some new capabilities – new tools and methods to allow you to make best use of the isotopic distribution (and fine-structure – is visible in your spectra) to make your assignment more confident and fast.  Enjoy!

Commercial licenses and support are available for AutoVectis through Spectroswiss.

For collaborators who wish to partner in development of new features, other options are available.  Please contact us for more information and to discuss your needs and ideas.

We are happy to provide examples of AutoVectis and Autophaser capability on trial data you send us for testing.  We can also supply trial versions of all tools on a test license.