The Hi Res. Feature Detector node uses the sliding window and Xtract algorithms to perform spectral deconvolution and measure all of the deconvoluted features and their quantitation traces. The parameters used in this node are essential to the LFQ workflow. Set them according to the data you are analyzing.
One of the key parameters is the Sliding Window Averaging Width RT. This parameter establishes the RT for the sliding window average. Set this parameter to match the full width at half max of a representative peak from the analyzed data. It is recommended to measure the peak width of an average feature in your data set. Do not choose the most abundant peak or one that is at noise level.
The best parameter setting is based on your chromatography:
- If the window is too wide, then low intensity signals are averaged out of the data.
- If the window is too narrow, then you lose the advantages of signal averaging.
The following table lists the node parameters.
Parameter | Description |
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1. Xtract | |
S/N Threshold | Specifies the minimum signal-to-noise ratio for data that the node analyses. |
Lowest m/z | Specifies the portion of the input spectrum that the Xtract algorithm processes. Min: Specifies the lowest end of the input spectrum. |
Highest m/z | Specifies the portion of the input spectrum that the Xtract algorithm processes. Max: Specifies the highest end of the input spectrum. |
Min Precursor Mass | The minimum precursor mass that the Xtract algorithm considers. |
Max Precursor Mass | The maximum precursor mass that the Xtract algorithm considers. |
Lowest Charge | Sets the low end of the allowable range for the number of charge states that must appear for a component to be recognized. The Xtract algorithm rejects potential components with fewer than the minimum or greater than the maximum number of charge states. |
Highest Charge | Sets the high end of the allowable range. |
Minimum Number of Detected Charge States | Minimum required number of observed charge states for data to be analyzed by the Xtract algorithm. For top-down data, the recommended minimum is 3. Some very low-abundance species might have only 2 observable (greater than noise) peaks. However, setting this value to less than 3 lets noise through and results in false positives. |
Relative Abundance Threshold | Specifies a threshold below which the node filters out data for data reporting. This option sets a relative threshold as a percentage of the most abundant component in the spectrum. The most abundant peak in the deconvolved spectrum has a relative abundance of 100 percent, and all other peaks are calculated relative to that one. For example, if the highest peak has an absolute abundance of 1000, the relative abundance is 1 percent, and no peaks below an absolute abundance of 10 appear in the deconvolved spectrum. Range: 0–100 Zero (0) displays all results; 100 displays only the most abundant component. |
Resolution at m/z 400 | Defines the resolution of the source spectrum at an m/z value of 400. |
Fit Factor | Measures the quality of the match between a measured isotope pattern and an averagine distribution of the same mass. Enter a value between 0 and 100%
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Remainder Threshold (%) | Specifies the height of the smaller overlapping isotopic cluster, as a percentage, with respect to the height of the most abundant isotopic cluster when the Xtract algorithm attempts to resolve overlapping isotopic clusters. For example, if one isotopic cluster in a spectrum has an abundance of 100, and you set the Remainder Threshold parameter to 30%, the Xtract algorithm ignores any overlapping clusters with an abundance less than 30. |
Min. Intensity | Specifies a minimum intensity threshold to filter out possible background noise, including when you set the S/N Threshold parameter to zero. |
Expected Intensity Err. | Specifies the permissible percentage of error allowed in calculating the ratio of the most abundant isotope to the next isotope higher in mass in the isotope series. |
Consider Overlaps | When selected (default), indicates that the Xtract algorithm is more tolerant of errors when the spectrum intensity is significantly higher than expected for the theoretical isotopic cluster. This option can lead to increased false positives; select it only when you expect overlapping isotopic clusters in a data set. |
2. Sliding Window Parameters | |
Averaging Width RT | Specifies the retention time, or the width, of the sliding window, in minutes.
You can achieve the best results when the window width is between one-quarter and twice the width of the characteristic peaks in the spectrum. For most uses, the optimum value might be half the width of the characteristic peaks. For example, if those peaks have a width of one minute, the optimum width is 0.5 minutes. |
Offset Type | Specifies the offset between successive sliding windows as a number of scans or as a percentage value. Select from:
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Offset Scan | Offsets each window from its predecessor by the user-specified number of scans. An offset of n means that each window begins n scans after the beginning of its predecessor. |
Offset Percentage | Offsets each window from its predecessor by the user-specified percentage of the window width.
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Merge Tolerance | Determines how close two components in successive sliding windows must be in mass for the application to identify them as a single component.
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Merge Mode | Determines how spectra are merged:
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Minimum Number of Charge States Observed | Minimum required number of observed charge states for data to be analyzed by kDecon. For top-down data, the recommended minimum is 3. Some very low-abundance species might have only 2 observable (greater than noise) peaks. However, setting this value less than 3 lets noise through and result in false positives. |
Minimum Number of Sliding Window Detections | Specifies the minimum number of sliding window intervals that a component must appear in for the application to consider the component valid. Set this parameter to a value large enough to exclude results that are implausibly narrow in retention time but small enough to include results of realistic duration. Values in the range of 3 through 8 generally give good results. A good approach is to use whichever is larger: 3 or the minimum number of windows that can fit into a peak.
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Biggest Gap Type | Specifies the maximum allowed separation in retention time between two successive individual members of a merged component identified by the sliding windows algorithm, in minutes.
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Biggest Gap Scans | Specifies the greatest number of scans between subsequent feature detection for grouping similar features.
Set this parameter comparable to or slightly less than the expected separation in retention time between distinct components with the same mass. |
Biggest Gap Retention Time | Specifies the greatest amount of time between feature detection events for grouping similar features. |
3. Feature /PrSM Connection | |
Mass Tolerance | Delta mass (in Daltons) allowed for mapping PrSMs to features. |
RT Threshold | Retention time threshold for mapping PrSMs to features:
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4. Feature/Trace Connection | |
Trace Mass Tolerance | Specifies the trace tolerance.
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Number Of Smoothing Points |
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Time Range (min) |
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Trace Smoothing Type | Determines the method to smooth the traces:
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5. Multithreading Options | |
CPU Usage | Determines the amount of CPU to direct toward processing:
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