| Title: | A Novel Quantile Regression Approach for eQTL discovery |
|---|---|
| Description: | A Quantile Rank-score based test for the identification of expression quantitative trait loci. |
| Authors: | Xiaoyu Song |
| Maintainer: | Xiaoyu Song <[email protected]> |
| License: | GPL (>= 2) |
| Version: | 1.0 |
| Built: | 2024-12-02 06:36:29 UTC |
| Source: | CRAN |
A Quantile Rank-score (QRank) based test for the identification of expression quantitative trait loci (eQTLs).
We use a Quantile Rank-score (QRank) based test to identify the expression quantitative trait loci (eQTLs) that are associated with the conditional quantile function of gene expressions.
Xiaoyu Song
Maintainer: Xiaoyu Song <[email protected]>
Xiaoyu Song, Gen Li, Zhenwei Zhou, Xianling Wang, Iuliana Ionita-Laza and Ying Wei (2016). QRank: A Novel Quantile Regression Tool for eQTL Discovery. Under revision for Bioinformatics.
set.seed(123) # n=300 # x=rbinom(n, 2, 0.2) # y=rnorm(n, mean=0, sd=1) # z=cbind(rbinom(n, 1, 0.3), rnorm(n, mean=2, sd=2)) # taus=c( 0.25, 0.5, 0.75) # # - run the proposed QRank approach # QRank(gene=y, snp=x, cov=z, tau=taus) # # - output # #Composite.pvalue: # #[1] 0.2241873 # #Quantile.specific.pvalue: # # 0.25 0.5 0.75 # #0.5452044 0.1821452 0.5938421 #set.seed(123) # n=300 # x=rbinom(n, 2, 0.2) # y=rnorm(n, mean=0, sd=1) # z=cbind(rbinom(n, 1, 0.3), rnorm(n, mean=2, sd=2)) # taus=c( 0.25, 0.5, 0.75) # # - run the proposed QRank approach # QRank(gene=y, snp=x, cov=z, tau=taus) # # - output # #Composite.pvalue: # #[1] 0.2241873 # #Quantile.specific.pvalue: # # 0.25 0.5 0.75 # #0.5452044 0.1821452 0.5938421 #
Calculate the heterogeneity index of quantile regression coefficients at multiple quantile levels. It measures the variation of the quantile coefficients across quantile levels.
heter.QRank(object, newtaus=NULL)heter.QRank(object, newtaus=NULL)
object |
Object returned from "QRank" |
newtaus |
a vector of quantile levels based on which heterogeneity index are calculated. Default is NULL, in which case the quantile levels inherited from "QRank" will be used. Include the formula of index. |
heterogeneity index |
one hetergeneity index |
# continuted from "QRank" taus=c( 0.25, 0.5, 0.75) q = QRank(gene=y, snp=x, cov=z, tau=taus) heter.QRank(q) # default uses taus inherited from "QRank" # - output #Heterogeneity index: #[1] 2.474184 heter.QRank(q,newtaus = 1:9/10) # calculate based on new taus values # - output #Heterogeneity index: #[1] 2.69242# continuted from "QRank" taus=c( 0.25, 0.5, 0.75) q = QRank(gene=y, snp=x, cov=z, tau=taus) heter.QRank(q) # default uses taus inherited from "QRank" # - output #Heterogeneity index: #[1] 2.474184 heter.QRank(q,newtaus = 1:9/10) # calculate based on new taus values # - output #Heterogeneity index: #[1] 2.69242
Print the object of QRank
## S3 method for class 'QRank' print(x, ...)## S3 method for class 'QRank' print(x, ...)
x |
Object returned from QRank. |
... |
Optional arguments |
Print the object of heter.QRank
## S3 method for class 'QRank.heter' print(x, ...)## S3 method for class 'QRank.heter' print(x, ...)
x |
Object returned from heter.QRank. |
... |
Optional arguments |
A function to obtain the p-value on the association between a gene expression and a genetic variant based on quantile rank-score test.
QRank(gene, snp, cov = NULL, tau)QRank(gene, snp, cov = NULL, tau)
gene |
a gene expression level from a selected gene. No parametric assumption is needed for underlying distribution. |
snp |
a selected SNP. |
cov |
a vector or matrix of covariates. Default is NULL. |
tau |
the quantile levels to be estimated. Tau can be a single value or a vector of quantile levels. |
This function conducts Quantile Rank-score (QRank) based test for the continuous traits. It can be used to identify expression quantitative trait loci (eQTLs) that are associated with the conditional quantile functions of gene expression.
composite.pvalue |
a single p-value for across all quantile levels under consideration, testing H0: No genetic association at the selected quantile levels. |
quantile.specific.pvalue |
p-values of each quantile level, testing |
Xiaoyu Song
Xiaoyu Song, Gen Li, Zhenwei Zhou, Xianling Wang, Iuliana Ionita-Laza and Ying Wei (2016). QRank: A Novel Quantile Regression Tool for eQTL Discovery. Under revision for Bioinformatics.
set.seed(123) # n=300 # x=rbinom(n, 2, 0.2) # y=rnorm(n, mean=0, sd=1) # z=cbind(rbinom(n, 1, 0.3), rnorm(n, mean=2, sd=2)) # taus=c( 0.25, 0.5, 0.75) # # - run the proposed QRank approach # QRank(gene=y, snp=x, cov=z, tau=taus) # # - output # #Composite.pvalue: # #[1] 0.2241873 # #Quantile.specific.pvalue: # # 0.25 0.5 0.75 # #0.5452044 0.1821452 0.5938421 #set.seed(123) # n=300 # x=rbinom(n, 2, 0.2) # y=rnorm(n, mean=0, sd=1) # z=cbind(rbinom(n, 1, 0.3), rnorm(n, mean=2, sd=2)) # taus=c( 0.25, 0.5, 0.75) # # - run the proposed QRank approach # QRank(gene=y, snp=x, cov=z, tau=taus) # # - output # #Composite.pvalue: # #[1] 0.2241873 # #Quantile.specific.pvalue: # # 0.25 0.5 0.75 # #0.5452044 0.1821452 0.5938421 #