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Alexis Delabriere edited this page Nov 8, 2021 · 2 revisions

This list a list of common recurring issues with SLAW.

  • I ran SLAW the processing and I don't have an output

    1. Are your files in .mzML format ? If not convert them.
    2. Are your files centroided ? You have to centroid them before inputting them to SLAW. You can centroidize your files using proteowizard using the vendor DLL (If you are on Linux have a look here: ProteoWizard Docker)
    3. Are your files huge (>1 Go mzML) ? Sadly we developped SLAW mainly for shorter gradients, longer gradients can sometimes be harder to process, since the optimization works generally too well resulting in hundreds of thousands of picked features, which are often real features, just with low intensity. You may want to include a threshold in the peakpicking arguments.
  • SLAW is really slow, is there any way to run it faster

To optimize the peakpicking parameters, SLAW has to run some peakpicking. This can be time consuming, especially when running ADAP, because it is a slow algorithm. SLAW already uses a small subset of thje files you speed it up further by reducing the * optimization/files_used, optimization/num_iterations, optimization/number_of_points parameters.

  • I have a strange error message that I don t understand.

The most common cause of failed processing is the lack of centroidization As SLAW call a lot of R and python package and different softwares, it is sometimes hard to make clear error messages. Don t hesitate to open a github issue.

  • The datamatrix is too big to process SLAW id very sensitive with optimized parameters, as it was mainly designed with large-scale clinical study in mind. If you are looking for natural product with very complex matrix and complex matrices, especially on longer gradient, this can become very hard to work with. You can use a filter one the peaktable before alignment as described here

  • Anything else

Please report or ask in the Github issues tracker, so that other can benefits from your experience: SLAW will be actively maintained and developed in the next few years.

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