# Read to SNPs to sets; Map SNPs to gene-sets/pathways 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"). ```r 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) ## Returns - **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 0.96 0.89 rs1000313 1 15405489 23254 KIAA1026 + 0.93 0.57 rs1002365 1 19797248 0.68 0.58 rs1002706 1 25051153 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 ```r ## 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 #################################################################### ```

read2_paths function