sampleRI | R Documentation |
Return a matrix of the sample specific retention indices (RI) based on the correlating selective masses.
sampleRI(samples, Lib, r_thres = 0.95, columns = NULL,
method = "dayNorm", minPairObs = 5, showProgressBar = FALSE,
makeReport = FALSE, pdfFile = "medianLibRep.pdf")
samples |
A |
Lib |
A |
r_thres |
A correlation threshold. |
columns |
Either |
method |
Normalization method. Options are |
minPairObs |
Minimum number of pair observations. Correlations between two variables are computed using all complete pairs of observations in those variables. If the number of observations is too small, you may get high correlations values just by chance, so this parameters is used to avoid that. Cannot be set lower than 5. |
showProgressBar |
Logical. Should the progress bar be displayed? |
makeReport |
Logical. If |
pdfFile |
The file name where the report will be saved. |
A matrix of correlating selective masses RI. Columns represent samples and rows the median RI of the selective masses.
Alvaro Cuadros-Inostroza, Matthew Hannah, Henning Redestig
ImportSamples
, ImportLibrary
,
medianRILib
, tsLib
, tsSample
require(TargetSearchData)
data(TSExample)
# get RI file path
RI.path <- tsd_data_path()
# update RI file path
RIpath(sampleDescription) <- RI.path
# Import Library
refLibrary <- ImportLibrary(tsd_file_path('library.txt'))
# get the sample RI
corRI <- sampleRI(sampleDescription, refLibrary, r_thres = 0.95)
# same as above, but changing the correlation threshold and the minimum number
# of observations
corRI <- sampleRI(sampleDescription, refLibrary, r_thres = 0.9,
minPairObs = 10)
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