Description Usage Arguments Value Author(s) References
View source: R/fitProbeDistribution.R
This function fits either a normal+exponential or normal+gamma convolution model to
the probe-level intensities of a PBMExperiment.
The normal+exponential convolution model is fit using limma::normexp.fit
and
the normal+gamma convolution model is fit using NormalGamma::normgam.fit
.
This function returns the model parameter estimates for each sample in a data.frame.
For more details on the estimated parameters, see the underlying functions.
1 2 3 4 5 6 | fitProbeDistribution(
pe,
assay = SummarizedExperiment::assayNames(pe)[1],
model = c("NormGam", "NormExp"),
method = "mle"
)
|
pe |
a PBMExperiment object containing GPR intensity information. |
assay |
string name of the assay. (default = |
model |
character string specifying model for fitting intensityies. Must be one of "NormGam", "NormExp". (default = "NormGam") |
method |
method used to estimate the parameters for normal+exponential model. See more details from
|
A data.frame with scans as rows and parameters in columns.
Dongyuan Song
Ritchie, M. E., Phipson, B., Wu, D., Hu, Y., Law, C. W., Shi, W., & Smyth, G. K. (2015). limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Research, 43(7), e47.
Plancade, S., Rozenholc, Y., & Lund, E. (2012). Generalization of the normal-exponential model: exploration of a more accurate parametrisation for the signal distribution on Illumina BeadArrays. BMC Bioinformatics, 13(1), 329.
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