dot-filterFewMeasurements: Remove features with a small number of (non-missing)...
In MSstatsConvert: Import Data from Various Mass Spectrometry Signal Processing Tools to MSstats Format
Description
Usage
Arguments
Value
Description
Remove features with a small number of (non-missing) measurements across runs
Usage
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2
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.filterFewMeasurements(
input,
min_intensity,
remove_few,
feature_columns = NULL
)
Arguments
input
data.table pre-processed by one of the .cleanRaw* functions.
min_intensity
minimum intensity that will be considered non-missing.
remove_few
logical, if TRUE, features that have less than three
measurements will be removed. If FALSE, only features with all missing runs
will be removed.
features_columns
chr, vector of names of columns that define features.
Value
data.table
MSstatsConvert documentation built on Nov. 8, 2020, 5:49 p.m.
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Description Usage Arguments Value
Description
Remove features with a small number of (non-missing) measurements across runs
Usage
1 2 3 4 5 6 | .filterFewMeasurements(
input,
min_intensity,
remove_few,
feature_columns = NULL
)
|
Arguments
input |
|
min_intensity |
minimum intensity that will be considered non-missing. |
remove_few |
logical, if TRUE, features that have less than three measurements will be removed. If FALSE, only features with all missing runs will be removed. |
features_columns |
chr, vector of names of columns that define features. |
Value
data.table
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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