Description Usage Arguments Details Value Author(s) References Examples
Calculate gene- and pathway-environment interaction p-values using the Adaptive Rank Truncated Product method. This function uses mainly the function ARTP_pathway
developped
by Kai Yu (R package ARTP).
1 2 3 | ARTP.GE(data.gene.pathway, list.gene.snp, p.snp.permut, p.snp.obs,
inspect.snp.n = 1, inspect.snp.percent = 0, inspect.gene.n = 10,
inspect.gene.percent = 0.05, temp.dir = "TEMP/", nperm)
|
data.gene.pathway |
Data frame (Gene X Pathways) of 0 and 1 values. The rownames (gene name considered) and the colnames (names of the studied pathways) have to be specified. The value 1 indicates that a gene is included in the corresponding pathway. |
list.gene.snp |
List containing for each gene the corresponding SNP ids. This list could be generated by |
p.snp.permut |
the output matrix from either |
p.snp.obs |
The output data frame from |
inspect.snp.n |
The number of candidate truncation points to inspect the top SNPs in a gene. The default is 1. |
inspect.snp.percent |
A value x between 0 and 1 such that a truncation point will be defined at every x percent of the top SNPs.
The default is 0 so that the truncation points will be |
inspect.gene.n |
The number of candidate truncation points to inspect the top genes in the pathway. The default is 10. |
inspect.gene.percent |
A value x between 0 and 1 such that a truncation point will be defined at every x percent of the top genes. The default is 0.05. |
temp.dir |
A folder to keep temporary files that will be created. |
nperm |
Number of permutation used or number of parametric bootsrap used. |
If the p-values are not computed using permutation.snp
, bootstrap.snp
and compute.p.snp.obs
then the format for p.snp.obs and p.snp.permut should be as follows.
Both files must be uncompressed, comma seperated files with the first row as the SNP ids in the same order.
Row 2 of obs.file has the observed p-values, and starting from row 2 in perm.file are the permuted p-values or the boostrap p-values.
A random seed should be set before calling ARTP.GE.R
in order to reproduce results.
The randomness is due to the ranking of p-values, where ties are broken randomly.
The returned value is a list with names "res.gene.list" and "res.pathway".
res.gene.list
is a list with length equals to the number of investigated
pathways. Each element of the list is a data frame containing the gene name, number of SNPs belonging to the gene that were included in the analysis, and the ARTP p-value for the gene.
res.pathway
contains the ARTP p-values for all the pathway analysed. The results contained in res.pathway
are saved in a file named "ARTP-GEI.RData".
The data frame containing all the gene analysed, the number of SNPs belonging to each gene and the ARTP p-value are saved in a file named "ARTP-GENE.RData".
Benoit Liquet benoit.liquet@univ-pau.fr
Therese Truong therese.truong@inserm.fr
Yu K, Li Q, Berger AW, Pfeiffer R, Rosenberg P, Caporaso N, Kraft P, Chatterjee N (2009). Pathway analysis by adaptive combination of P-values. Genet Epidemiol 33:700-709.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 | data(data.pathway)
data(list.gene.snp)
## Not run:
data(data.pige)
###First example: compute observed p-value (orignal data) and permuted p-value
res <-data.to.PIGE(data=data.pige,data.pathway=data.pathway,
list.gene.snp=list.gene.snp,choice.pathway=c(1,2))
formul <- formula(y~factor(cov1)+factor(cov2)+factor(cov3)+factor(cov4)
+var_int)
p.snp.obs.ex <- compute.p.snp.obs(data=data.pige,model=formul,
indice.snp=res$snp.selected,var.inter="var_int",class.inter=NULL)
p.snp.permut.ex <- permutation.snp(model=formul,data=data.pige,
indice.snp=res$snp.selected,var.inter="var_int",class.inter=NULL,
nbcpu=3,Npermut=9,file.out="res-permut")
set.seed(10)
result.1 <- ARTP.GE(data.gene.pathway=data.pathway,
list.gene.snp=list.gene.snp,p.snp.permut=p.snp.permut.ex,
p.snp.obs=p.snp.obs.ex,inspect.snp.n=5,inspect.snp.percent=0.05
,inspect.gene.n=10,inspect.gene.percent=0.05,temp.dir="TEMP/"
,nperm=9)
result.1
##Second example: observed and permuted p-values have already been computed
path.data <- paste(system.file("sampleData", package="PIGE"),"/",sep="")
res.permut <- read.table(file=paste(path.data,"res-permut.txt",sep="")
,header=TRUE,sep=" ")
res.obs <- read.table(file=paste(path.data,"res-obs.txt",sep="")
,header=TRUE,sep=" ")
result.2 <- ARTP.GE(data.gene.pathway=data.pathway,
list.gene.snp=list.gene.snp, p.snp.permut=res.permut,
p.snp.obs=res.obs,inspect.snp.n=5,inspect.snp.percent=0.05,
inspect.gene.n=10,inspect.gene.percent=0.05,temp.dir="TEMP/",nperm=90)
result.2
##Third example: Survival data
##observed and permuted p-values have already been computed
data(data.surv)
data(data.pathway.surv)
data(list.gene.snp.surv)
path.data <- paste(system.file("sampleData", package="PIGE"),"/",sep="")
res.permut <- read.table(file=paste(path.data,"res-permut-surv.txt",sep="")
,header=TRUE,sep=" ")
res.obs <- read.table(file=paste(path.data,"res-obs-surv.txt",sep="")
,header=TRUE,sep=" ")
result.3 <- ARTP.GE(data.gene.pathway=data.pathway.surv,
list.gene.snp=list.gene.snp.surv, p.snp.permut=res.permut,
p.snp.obs=res.obs,inspect.snp.n=5,inspect.snp.percent=0.05,
inspect.gene.n=10,inspect.gene.percent=0.05,temp.dir="TEMP/",nperm=90)
result.3
## End(Not run)
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.