gespeR

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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

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

## S4 method for signature '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, ...)

## S4 method for signature '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

Slots

SSP

The observed siRNA-specific phenotypes

GSP

The deconvoluted gene-specific phenotypes

target.relations

The siRNA-to-gene target relations, e.g. predicted by TargetScan

is.fitted

An indicator wheter the gespeR model was fitted

model

The fitted regularized linear regression model

Author(s)

Fabian Schmich

See Also

gespeR-package

plot.gespeR

gsp

ssp

scores

stability

target.relations

Examples

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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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