Feature Detection on Centroided Data#
To quantify peptide features, TOPP offers the FeatureFinder tools. In this section the FeatureFinderCentroided is used, which works only on centroided data. There are other FeatureFinders available that also work on profile data.
For this example the file LCMS-centroided.mzML
from the examples data is used (File > Open example data). In order
to adapt the algorithm to the data, some parameters have to be set.
Intensity#
The algorithm estimates the significance of peak intensities in a local environment. Therefore, the HPLC-MS map is
divided into n
times n
regions. Set the intensity:bins
parameter to 10
for the whole map. For a small region, set
it to 1
.
Mass trace#
For the mass traces, define the number of adjacent spectra in which a mass has to occur (mass_trace:min_spectra
). In
order to compensate for peak picking errors, missing peaks can be allowed (mass_trace:max_missing
) and a tolerated
mass deviation must be set (mass_trace:mz_tolerance
).
Isotope pattern#
The expected isotopic intensity pattern is estimated from an averagene amino acid composition. The algorithm searches
all charge states in a defined range (isotopic_pattern:change_min
to isotopic_pattern:change_max
). Just as for mass
traces, a tolerated mass deviation between isotopic peaks has to be set (isotopic_pattern:mz_tolerance
).
The image shows the centroided peak data and the found peptide features. The used parameters can be found in the TOPP tools dialog.