xieyying

Here I post the link of mass data: https://drive.google.com/drive/folders/1CZBRSU_hdhq7UHXdqJYQSrMUVcSfarGy?usp=drive_link

Sure， Here is the reduced code: import pyopenms as oms class FeatureDetection: """ Extract features from mzML files using pyopenms """ def __init__(self, file): self.file = file self.exp = oms.MSExperiment()...

The data can be directly downloaded without need to request. https://drive.google.com/drive/folders/11Nz3HQvyH0_yk3DuL4DoW81iQuAJ2JQV?usp=drive_link For this data, I try the following parameter in the step of mass_trace_detection. mtd_par.setValue('trace_termination_criterion', 'sample_rate') mtd_par.setValue('min_sample_rate', 0.01) I can...

> @xieyying Which of these files did you use in your example? I am so sorry, this is the correct link. https://drive.google.com/drive/folders/1CZBRSU_hdhq7UHXdqJYQSrMUVcSfarGy?usp=drive_link

> What happens if you keep "trace_termination_criterion" as "outlier" but reduce the number of outliers with "trace_termination_outliers" to zero? The algorithm is looking for peaks left and right which have...

> The issue is your peak map contains only data related to that simulated metabolite, but no noise at all (not realistic). Once you add some noise left and right...