fit {FRASER} | R Documentation |
This method corrects for confounders in the data and fits a beta-binomial distribution to the introns/splice sites.
For more details please see FRASER
.
## S3 method for class 'FraserDataSet' fit( object, implementation = c("PCA", "PCA-BB-Decoder", "AE", "AE-weighted", "PCA-BB-full", "fullAE", "PCA-regression", "PCA-reg-full", "PCA-BB-Decoder-no-weights", "BB"), q, type = "psi3", rhoRange = c(1e-08, 1 - 1e-08), weighted = FALSE, noiseAlpha = 1, convergence = 1e-05, iterations = 15, initialize = TRUE, control = list(), BPPARAM = bpparam(), nSubset = 15000, minDeltaPsi = 0.1, ... )
object |
A |
implementation |
The method that should be used to correct for confounders. |
q |
The encoding dimensions to be used during the fitting proceadure.
Should be fitted using |
type |
The type of PSI (psi5, psi3 or theta for theta/splicing efficiency) |
rhoRange |
Defines the range of values that rho parameter from the beta-binomial distribution is allowed to take. For very small values of rho, the loss can be instable, so it is not recommended to allow rho < 1e-8. |
weighted |
If TRUE, the weighted implementation of the autoencoder is used |
noiseAlpha |
Controls the amount of noise that is added for the denoising autoencoder. |
convergence |
The fit is considered to have converged if the difference between the previous and the current loss is smaller than this threshold. |
iterations |
The maximal number of iterations. When the autoencoder has not yet converged after these number of iterations, the fit stops anyway. |
initialize |
If FALSE and a fit has been previoulsy run, the values from the previous fit will be used as initial values. If TRUE, (re-)initialization will be done. |
control |
List of control parameters passed on to optim(). |
BPPARAM |
the BiocParallel parameters for the parallelization |
nSubset |
The size of the subset to be used in fitting if subsetting is used. |
minDeltaPsi |
Minimal delta psi of an intron to be be considered a variable intron. |
... |
Currently not used |