runNPARC {NPARC} | R Documentation |
Wrapper function for melting curve fitting and hypothesis testing.
runNPARC(x, y, id, groupsNull = NULL, groupsAlt, BPPARAM = BiocParallel::SerialParam(progressbar = TRUE), dfType = c("theoretical", "empirical"), control = getParams())
x |
numeric vector of the independent variables (typically temperature) |
y |
numeric vector of the dependent variables (typically relative abundance measurements) |
id |
character vector with the protein ID to which each each data point belongs. |
groupsNull |
one or more vectors with grouping variables for the null models. See details. |
groupsAlt |
one or more vectors with grouping variables for the alternative models. See details. |
BPPARAM |
BiocParallel parameter object to invoke curve fitting in parallel. Default: BiocParallel::SerialParam() |
dfType |
character value indicating the method for degrees of freedom computation for the F-test. Theoretical yields the text-book solution. Empirical yields estimates derived from the distribution moments of the RSS. |
control |
list of parameters used to control specific parts of the analyse |
groupsNull
or groupsAlt
can either be a single vector each, or data.frames of the same length as x
and y
with one column per factor
data frame with fitted model parameters and additional columns listing e.g. residuals sum of squares of null and alterantive model
data(stauro_TPP_data_tidy) df <- dplyr::filter(stauro_TPP_data_tidy, grepl("CDK|GTP|CRK", uniqueID)) testResults <- runNPARC(x = df$temperature, y = df$relAbundance, id = df$uniqueID, groupsAlt = df$compoundConcentration, dfType = "empirical")