new.aligned.learn: Feature data after alignment and weak signal recovery. The...
In yufree/apLCMS: Adaptive processing of LC-MS data
new.aligned.learn R Documentation
Feature data after alignment and weak signal recovery. The initial peak detection is done by machine learning approach.
Description
This is the aligned feature data from 4 sample profiles after weaker signal recovery.
Usage
data(new.aligned)
Format
The format is:
List of 4
$ aligned.ftrs: A matrix with m/z, median elution time, and signal strength in each spectrum.
$ pk.times : A matrix with m/z, median elution time, and elution time in each spectrum.
$ mz.tol : num 1.14e-05 (the m/z tolerance level in alignment)
$ chr.tol : num 79.21 (the elution time tolerance level in alignment)
Source
Dean Jones lab. Emory University, School of Medicine.
Examples
data(new.aligned.learn)
yufree/apLCMS documentation built on May 19, 2024, 1:22 p.m.
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| new.aligned.learn | R Documentation |
Feature data after alignment and weak signal recovery. The initial peak detection is done by machine learning approach.
Description
This is the aligned feature data from 4 sample profiles after weaker signal recovery.
Usage
data(new.aligned)Format
The format is: List of 4 $ aligned.ftrs: A matrix with m/z, median elution time, and signal strength in each spectrum. $ pk.times : A matrix with m/z, median elution time, and elution time in each spectrum. $ mz.tol : num 1.14e-05 (the m/z tolerance level in alignment) $ chr.tol : num 79.21 (the elution time tolerance level in alignment)
Source
Dean Jones lab. Emory University, School of Medicine.
Examples
data(new.aligned.learn)
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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