modelTurnover {pulsedSilac} | R Documentation |
Method to apply turnover models on protein/peptide data
modelTurnover(x, ...) ## S4 method for signature 'SilacProteinExperiment' modelTurnover( x, assayName = "fraction", formula = "fraction ~ 1-exp(-k*t)", start = list(k = 0.02), robust = FALSE, mode = "protein", verbose = FALSE, returnModel = FALSE, conditionCol, timeCol, ... ) ## S4 method for signature 'SilacPeptideExperiment' modelTurnover( x, assayName = "fraction", formula = "fraction ~ 1-exp(-k*t)", start = list(k = 0.02), robust = FALSE, mode = c("grouped", "peptide"), verbose = FALSE, returnModel = FALSE, conditionCol, timeCol, proteinCol, ... ) ## S4 method for signature 'SilacProteomicsExperiment' modelTurnover( x, assayName = "fraction", formula = "fraction ~ 1-exp(-k*t)", start = list(k = 0.02), robust = FALSE, mode = c("protein", "grouped", "peptide"), verbose = FALSE, returnModel = FALSE, conditionCol, timeCol, proteinCol, ... )
x |
A |
... |
further parameters passed into |
assayName |
|
formula |
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start |
named |
robust |
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mode |
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verbose |
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returnModel |
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conditionCol |
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timeCol |
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proteinCol |
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A named list
with either model metrics in matrices or the
model objects.
data('wormsPE') wormsPE <- calculateIsotopeFraction(wormsPE, ratioAssay = 'ratio') modelList <- modelTurnover(x = wormsPE[1:10], assayName = 'fraction', formula = 'fraction ~ 1 - exp(-k*t)', start = list(k = 0.02), mode = 'protein', robust = FALSE, returnModel = TRUE)