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gespeR (version 1.4.2)

gespeR-class: gespeR

Description

Class that represents a gespeR model. It contains a SSP Phenotypes and TargetRelations representing a siRNA knockdown experiment. When the model is fitted, it additionaly contains estimated GSP Phenotypes.

Usage

gespeR(phenotypes, target.relations, ...)

## S3 method for class 'Phenotypes,TargetRelations': gespeR(phenotypes, target.relations, mode = c("cv", "stability"), alpha = 0.5, nbootstrap = 100, fraction = 0.67, threshold = 0.9, EV = 1, weakness = 0.8, ncores = 1, ...)

## S3 method for class 'numeric,Matrix': gespeR(phenotypes, target.relations, ...)

Arguments

phenotypes
The siRNA-spefic phenotypes. Single object for univariate phenotypes and list of Phenotypes objects for multivariate phenotypes.
target.relations
The siRNA-to-gene target relations
...
Additional arguments
mode
The mode of covariate selectino ("cv" or "stability")
alpha
The glmnet mixing parameter
nbootstrap
The number of bootstrap samples
fraction
The fraction for each bootstrap sample
threshold
The selection threshold
EV
The expected value of wrongly selected elements
weakness
The weakness parameter for randomised lasso
ncores
The number of cores for parallel computation

Value

  • A gespeR object

See Also

gespeR-package

plot.gespeR

gsp

ssp

scores

stability

target.relations

Examples

Run this code
phenos <- Phenotypes(system.file("extdata", "Phenotypes_screen_A.txt", package = "gespeR"),
type = "SSP",
col.id = 1,
col.score = 2)
trels <- TargetRelations(readRDS(system.file("extdata", "TR_screen_A.rds", package = "gespeR")))
res <- gespeR(phenotypes = phenos,
    target.relations = trels,
    mode = "stability",
    nbootstrap = 100,
    fraction = 0.67,
    threshold = 0.75,
    EV = 1,
    weakness = 0.8,
    ncores = 1)
gsp(res)

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