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Last data update: 2014.03.03

R: gespeR

gespeR-class

R Documentation

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, ...)

## 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

Examples

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)

Results


R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

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Type 'license()' or 'licence()' for distribution details.

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Type 'demo()' for some demos, 'help()' for on-line help, or
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Type 'q()' to quit R.

> library(gespeR)
Loading required package: ggplot2
> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/gespeR/gespeR-class.Rd_%03d_medium.png", width=480, height=480)
> ### Name: gespeR-class
> ### Title: gespeR
> ### Aliases: gespeR gespeR,Phenotypes,TargetRelations-method
> ###   gespeR,numeric,Matrix-method gespeR-class
> 
> ### ** Examples
> 
> 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)
1500 GSP Phenotypes

Source: local data frame [1,500 x 2]

            ID Scores
        <fctr>  <dbl>
1  geneID_0001     NA
2  geneID_0002     NA
3  geneID_0003     NA
4  geneID_0004     NA
5  geneID_0005     NA
6  geneID_0006     NA
7  geneID_0007     NA
8  geneID_0008     NA
9  geneID_0009     NA
10 geneID_0010     NA
..         ...    ...
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>