What is Direct Sample Analysis?
Direct Sample Analysis allows you to analyse your samples whilst minimizing time spent on sample preparation.
How do I use direct sample analysis in Progenesis?
- When creating an experiment, choose the Direct sample analysis machine type
- Pre-process your raw data using Progenesis Bridge (which is included with MassLynx)
- Import the pre-processed data using the Waters (.raw) data format
How does enabling direct sample analysis affect the Progenesis workflow?
If you have chosen the direct sample analysis machine type when creating your experiment, Progenesis QI will modify its analysis in the following ways:
- Alignment is disabled
- Data that has been processed by Progenesis Bridge will be perfectly aligned, so this step is unnecessary. The Review alignment step is removed from the workflow, and no alignment is performed.
- Isotope clustering is disabled
- When peak picking, Progenesis will only pick single isotopes, and not attempt to cluster isotopes into a single ion. This is because the lack of LC separation means many different compounds co-elute, and performing isotope clustering would produce a high number of false negatives (i.e. grouping two ions as isotopes when in fact they are just co-eluting ions 1 Da apart).
- Adduct deconvolution is disabled
- For a similar reason, adduct deconvolution is disabled. The lack of LC separation would lead to a large number of different compounds being grouped together as adducts. The Review Deconvolution screen is still enabled, to allow you to perform manual deconvolution if desired.
- Peak picking sensitivity is maximised
- Progenesis QI provides a range of options for its peak picking sensitivity. By default this uses a noise estimation algorithm to determine the noise levels in the data. However, when using direct sample analysis, your data has already been noise-reduced by Progenesis Bridge. Therefore, Progenesis QI will set the peak picking sensitivity to use a minimum peak intensity of 0 (essentially it will consider all peaks in the data).