Description Usage Arguments Value References See Also Examples
Performs gene-level circular genomic permutations. In each permutation,the complete set of
SNP association p-values are permuted by rotation with respect to the SNPs' genomic locations.
Once these 'simulated' p-values are assigned,the joint gene p-values are calculated using
Fisher's combination test,and pathways' association tested using the hypergeometric test
1 2 3 | genes_permutation(ordered_alldata = "", pers_ids = "", pathways = "",
ntraits = "", nper = 100, threshold = 0.05, seed=10,saveto = "workspace",
gs_locs="", envir = "")
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ordered_alldata |
Return variable from "genome_order". Ordered genome and trait p-values |
gs_locs |
Return variable from "genome_order". SNP indexes |
pers_ids |
Return variable "per_ors" from "read2_paths". Gene indexes |
pathways |
Return variable "pathways" from "read2_paths" |
ntraits |
Traits INDEX to be analysed. Index according to "ordered_alldata". |
nper |
Number of permutations.Example: nper=1000 |
threshold |
Threshold to be set by the hypergeometric test. threshold=0.05 |
seed |
Set a number for random sampling |
saveto |
Save permutation results to "workspace" OR "directory" |
envir |
R environment to save the data to when saveto is set to "workspace" |
Returns "Permus_trait" variables or files (permutation datasets).
Imports phyper (from stats)
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 | #load data
data(demo,SNPsAnnotation)
all_data <- read_pvals(data_name=demo,snps_ann=SNPsAnnotation)
# Prepare Genome
genome_results <-genome_order(all_data=all_data)
# Results from genome_order
ordered_alldata <- genome_results$ordered_alldata
gs_locs <- genome_results$gs_locs
# Create new environment to save data:
gper.env <- new.env()
# Get pathways
data(RHSA164843,RHSA446343,RHSA8876384,RHSA8964572,RHSA109582,RHSA1474244,envir=gper.env)
# Map Genes to pathways
paths_res <- read2_paths(ordered_alldata=ordered_alldata,gs_locs=gs_locs,
sets_from="workspace",sets_prefix="RHSA",level="gene",envir=gper.env)
pers_ids <- paths_res$per_ors
pathways<- paths_res$pathways
# Perform Permutations:
genes_permutation(ordered_alldata=ordered_alldata,
pers_ids=pers_ids,pathways=pathways,ntraits=c(7:9),
nper=10,threshold=0.05, saveto="workspace",
gs_locs=gs_locs,envir = gper.env)
# Results
results <- get_results(res_pattern="Permus",level="gene",
from="workspace",threshold=0.05,envir= gper.env)
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