Package 'poolVIM'

Title: Gene-Based Association Tests using the Actual Impurity Reduction (AIR) Variable Importance. <doi:10.1093/Bioinformatics/Bty373>
Description: Gene-based association tests using the actual impurity reduction (AIR) variable importance. The function aggregates AIR importance measures from a group of SNPs or probes and outputs a p-value for each gene.
Authors: Stefano Nembrini <[email protected]>
Maintainer: Stefano Nembrini <[email protected]>
License: GPL (>= 2)
Version: 1.0.0
Built: 2025-03-11 04:01:05 UTC
Source: https://github.com/snembrini/poolvim

Help Index

fisher

Description

fisher

Usage

fisher(p, adjust, R)

Arguments

p

vector of pvalues
adjust

if correlation has to be taken into account
R

correlation matrix

gaussianize null variable importances

Description

gaussianize null variable importances

Usage

gaussianize(x, a)

Arguments

x

distr
a

value to interpolate/extrapolate

meff. written by Ozan Cinar and Wolfgang Viechtbauer.

Description

meff. written by Ozan Cinar and Wolfgang Viechtbauer.

Usage

m_effective(R)

Arguments

R

R

after the Actual Impurity Reduction Importance is computed with a Random Forest, pvalues from different probes or SNPs belonging to the same gene can be aggregated in order to obtain a single pvalue for that gene. Correlation between probes can also be taken into account.

Description

after the Actual Impurity Reduction Importance is computed with a Random Forest, pvalues from different probes or SNPs belonging to the same gene can be aggregated in order to obtain a single pvalue for that gene. Correlation between probes can also be taken into account.

Usage

poolVIM(rf, genenames, x, method = "Tippett", adjust)

Arguments

rf

a ranger object with "importance="impurity_corrected"
genenames

a vector of the name of the gene to which each probe or SNP belongs, it has to be of size dim(x)[1]
x

design matrix used by the random forest
method

one of Tippett, Fisher, Kost, EBM
adjust

"no" / "yes" depending if correlation has to be taken into account

Examples

n <- 250
x=replicate(50, runif(n))
dat <- data.frame(y = factor(rbinom(n, 1, .5)), x)
library(ranger)
rf <- ranger(y ~ ., dat, importance = "impurity_corrected",num.trees=100)
genenames=colnames(x)=rep(c("G1","G2"),50/2)
poolVIM(rf,genenames,x,method="Fisher",adjust="no")

tippett.

Description

tippett.

Usage

tippett(p, adjust, R)

Arguments

p

vector of pvalues
adjust

if correlation has to be taken into account
R

correlation matrix