From 7fc867cb2e9723fe9a756c16b2fa2483c213bd9c Mon Sep 17 00:00:00 2001 From: corinnabrungs Date: Mon, 22 Jan 2024 09:55:07 +0100 Subject: [PATCH] factor of lowest signal also for profile data --- .../mass-detection-algorithms.md | 19 +++++++++++-------- docs/wizard.md | 7 ++++--- 2 files changed, 15 insertions(+), 11 deletions(-) diff --git a/docs/module_docs/featdet_mass_detection/mass-detection-algorithms.md b/docs/module_docs/featdet_mass_detection/mass-detection-algorithms.md index 942c89ec..f1f660df 100644 --- a/docs/module_docs/featdet_mass_detection/mass-detection-algorithms.md +++ b/docs/module_docs/featdet_mass_detection/mass-detection-algorithms.md @@ -2,25 +2,28 @@ Mass detection can be done with the following six algorithms: +- Factor of lowest signal - Centroid -- Factor of the lowest signal - Exact mass - Local maxima - Recursive threshold - Wavelet transform - Auto -## **Centroid** +## **Factor of lowest signal** -:material-lightbulb: This mass detector is suitable for already centroided data. +:material-lightbulb: This mass detector is suitable for centroid or profile data. -Centroid algorithm assumes that each signal above a given noise level is a detected ion. +Choose the **Factor of lowest signal** for both centroided or profile data where each spectrum contains noise signals, often represented by many signals at the same low intensity (spectral grass). This may correspond to static noise or single counts. This algorithm removes all data points below a spectrum's lowest intensity multiplied by a factor. If the spectra are free of noise, for example +because they were already filtered, use an **absolute intensity** threshold. -## **Factor of the lowest signal** +## **Centroid** + +:material-lightbulb: This mass detector is suitable for already centroided data. -:material-lightbulb: This mass detector is suitable for already centroided data. +Centroid algorithm assumes that each signal above a given noise level is a detected ion. Here, the noise +level is set as an absolute fixed value for each MSn level. -It removes all data points below a spectrum's lowest intensity multiplied by a factor. ## **Exact mass** @@ -95,7 +98,7 @@ The lower (LL) and upper (UL) limits, where the Mexican Hat wavelet is evaluated **Scale level** -Number of wavelet coeficients to use in m/z feature detection. Serves as the scale factor that either dilates or compresses the wavelet signal. +Number of wavelet coefficients to use in m/z feature detection. Serves as the scale factor that either dilates or compresses the wavelet signal. When the scale factor is relatively low, the signal is more contracted, which results in a more detailed resulting graph and more noisy peaks are detected. On the other hand, when the scale factor is high, the signal is stretched out, which means that the resulting graph will be less detailed with a smoothed signal. diff --git a/docs/wizard.md b/docs/wizard.md index 005994c2..48758a26 100644 --- a/docs/wizard.md +++ b/docs/wizard.md @@ -65,7 +65,8 @@ The full-width at half maximum for IMS features ## MS instrument, e.g., Orbitrap, qTOF, FTICR #### Noise threshold (MS1/MS2) -Choose the mass detector from the drop down menu. Choose the **Factor of lowest signal** for centroided data where each spectrum contains noise signals, often represented by many signals at the same low intensity (spectral grass). This may correspond to static noise or single counts. Otherwise use an **absolute intensity** threshold. +Choose the mass detector from the drop down menu. Choose the **Factor of lowest signal** for both centroided or profile data where each spectrum contains noise signals, often represented by many signals at the same low intensity (spectral grass). This may correspond to static noise or single counts. If the spectra are free of noise, for example +because they were already filtered, use an **absolute intensity** threshold. Depending on the selected mass detector, separate absolute noise levels or factors are defined to threshold spectra of MS level 1 and 2 (or above). So the MS2 noise level is used for MSn data with level > 1. These parameters can be optimized by looking at the spectral raw data in the raw data overview. @@ -74,7 +75,7 @@ The minimum height of chromatograms and features #### Scan-to-scan m/z tolerance Relative and absolute m/z tolerance. Always applies the maximum tolerance based on the m/z this means that smaller and higher values are stronger affected by the absolute and relative tolerance, respectively. -Used to find the same signal in different scans when connecting chromatigrams. Reflects on the mass accuracy between scans in the same raw data file. +Used to find the same signal in different scans when connecting chromatograms. Reflects on the mass accuracy between scans in the same raw data file. #### Feature-to-feature m/z tolerance Relative and absolute m/z tolerance. Always applies the maximum tolerance based on the m/z this means that smaller and higher values are stronger affected by the absolute and relative tolerance, respectively. @@ -82,7 +83,7 @@ Used to group isotopes and adducts of the same molecule. Those m/z values are al #### Sample-to-sample m/z tolerance Relative and absolute m/z tolerance. Always applies the maximum tolerance based on the m/z this means that smaller and higher values are stronger affected by the absolute and relative tolerance, respectively. -Used to align features across samples. Those m/z values are already averaged over their features but originate from differnt samples. +Used to align features across samples. Those m/z values are already averaged over their features but originate from different samples.