read2_paths: Read to SNPs to sets; Map SNPs to gene-sets/pathways

In genomicper: Circular Genomic Permutation using Genome Wide Association p-Values

Description

Reads the sets/pathways, map the SNPs and genes to the gene-sets/pathways read2_paths uses the "genome_order" output(ordered_alldata, gs_locs) to assign genomic location indexes to each element in the gene-set. The permutation method must be defined (i.e. level = "snp" OR level = "gene").

Usage

read2_paths(ordered_alldata="",gs_locs="",sets_from="workspace",
sets_prefix="RHSA",level="snp",envir="")

Arguments

ordered_alldata	Ordered data according to the SNPs genomic location. Traits start at column 7 Return variable from: genome_results <-genome_order(all_data=all_data) ordered_alldata <- genome_results$ordered_alldata
gs_locs	Gene annotation,indexes and number of observations Return variable from genome_order(): genome_results <-genome_order(all_data=all_data) gs_locs <- genome_results$gs_locs
sets_from	Location of the gene-sets. Default set to "workspace" sets_from="workspace" OR sets_from="directory" "directory", only will search for information in the working directory.
sets_prefix	Prefix of the gene-set variables or files. Default set to sets_prefix= "RHSA" e.g. Variables "RHSA164843","RHSA446343","RHSA8876384" each variable/file contains the list of gene identifiers part of that pathway
level	The level at which the permutations will be performed. Assigns the indexes according to snps or genes Default value "snp" level values = "snp" OR "gene"
envir	R environment where pathway data is stored. e.g(envir=.GlobalEnv, envir=gper.env)

Value

pathways	Pathway Id, Description,Number of Genes in the pathway, Number of genes found in the dataset, Number of SNPs found in the dataset
per_ors	A list of identifiers mapped to each pathway

Format

Input: Ordered_alldata
name     Chromosome  Location GENE_ID   Symbol Orientation Trait1 Trait2
rs1001567          1 9194614     <NA>     <NA>        <NA> 0.96 0.89
rs1000313          1 15405489   23254 KIAA1026           + 0.93 0.57
rs1002365          1 19797248    <NA>     <NA>        <NA> 0.68 0.58
rs1002706          1 25051153    <NA>     <NA>        <NA> 0.71 0.02
rs1002487          1 26865971    6195  RPS6KA1           + 0.98 0.78

Input:gs_locs
      Symbol   Chromosome Location    Gene_ID Start_Indx Observations
 [1,] "ACYP2"  "2"        "54399633"  "98"    "35"       "1"         
 [2,] "AMPD3"  "11"       "10514707"  "272"   "898"      "1"         
 [3,] "ANK2"   "4"        "113830885" "287"   "479"      "4"
 
Input:pathway example
RHSA8964572
[1]   1149 128486 161247  29923 345275  63924
          
Output:pathways
     ID            GenesInPath GenesFound SNPsInPath
"RHSA109582"  "681"       "8"        "11"      
"RHSA1474244" "418"       "7"        "10"      
"RHSA164843"  "11"        "0"        "0"       
"RHSA446343"  "4"         "1"        "1"       
"RHSA8876384" "32"        "1"        "1"       
"RHSA8964572" "6"         "1"        "1"       

See Also

genes_permutation snps_permutation genome_order

Examples

## DEMO - SNP Level data stored in workspace #######################
# library(genomicper)
data(demo,SNPsAnnotation)
all_data <- read_pvals(data_name=demo,snps_ann=SNPsAnnotation)
genome_results <-genome_order(all_data=all_data)
	ordered_alldata <- genome_results$ordered_alldata
	gs_locs <- genome_results$gs_locs
	
# Create new environment to save variables (e.g. pathways, permutations):
gper.env <- new.env()

data(RHSA164843,RHSA446343,RHSA8876384,RHSA8964572,RHSA109582,RHSA1474244,envir=gper.env)

paths_res <- read2_paths(ordered_alldata=ordered_alldata,
gs_locs=gs_locs,sets_from="workspace",sets_prefix="RHSA",
level="snp",envir=gper.env)		
	pers_ids <- paths_res$per_ors
	pathways<- paths_res$pathways
####################################################################

genomicper documentation built on May 8, 2021, 9:06 a.m.