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merge_similar_clusters.R: improved syntax and documentation; fixed typos
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,77 +1,79 @@ | ||
| #!/usr/bin/env Rscript | ||
| if (!require(optparse)) install.packages("optparse"); library(optparse) | ||
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| option_list <- list( | ||
| make_option(opt_str = c("-i", "--input"), default = NULL, help = "Input TSV-file. Output from merged tomtom results", metavar = "character"), | ||
| make_option(opt_str = c("-l", "--list"), default = NULL, help = "Numerically sorted whitespace separated list of absolute fasta-file paths", metavar = "character"), | ||
| make_option(opt_str = c("-w", "--min"), default = NULL, help = "Minimum weight of edge allowed in graph clusters.", metavar = "character") | ||
| ) | ||
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| opt_parser <- OptionParser(option_list = option_list, | ||
| description = "Adding Cluster ID to Query_ID Column") | ||
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| opt <- parse_args(opt_parser) | ||
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| #' Merging FASTA-files, which motifs are similar. | ||
| #' | ||
| #' @parameter tsv_in <string> Path to TSV file generated by Tomtom. | ||
| #' The input for Tomtom is a from all clusters merged meme-file. | ||
| #' @parameter file_list <string> Numerically sorted whitespace separated list of absolute fasta-file paths | ||
| #' @parameter min_weight <INT> Minimum weight of edge allowed in graph clusters. | ||
| #' | ||
| #' @author René Wiegandt | ||
| #' @contact rene.wiegandt(at)mpi-bn.mpg.de | ||
| merge_similar <- function(tsv_in, file_list, min_weight){ | ||
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| files <- unlist(as.list(strsplit(file_list, ","))) | ||
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| # split the string on the character "." in the first to columns and safe the last value each, to get the number of the cluster. | ||
| tsv <- data.table::fread(tsv_in, header = TRUE, sep = "\t",colClasses = 'character') | ||
| query_cluster <- unlist(lapply(strsplit(tsv[["Query_ID"]],"\\."), function(l){ | ||
| tail(l,n=1) | ||
| })) | ||
| target_cluster <- unlist(lapply(strsplit(tsv[["Target_ID"]],"\\."), function(l){ | ||
| tail(l,n=1) | ||
| })) | ||
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| # create data.table with only the cluster-numbers | ||
| sim_not_unique <- data.table::data.table(query_cluster,target_cluster) | ||
| # convert from character to numeric values | ||
| sim_not_unique[, query_cluster := as.numeric(query_cluster)] | ||
| sim_not_unique[, target_cluster := as.numeric(target_cluster)] | ||
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| # remove rows if column 1 is idential to column 2 | ||
| edgelist <- sim_not_unique[query_cluster != target_cluster] | ||
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| # create graph from data.frame | ||
| g <- igraph::graph_from_edgelist(as.matrix(edgelist)) | ||
| # converting graph to adjacency matrix | ||
| adj_matrix <- igraph::get.adjacency(g, names = T) | ||
| # generating weighted graph from adjacency matrix | ||
| g_adj <- igraph::graph_from_adjacency_matrix(adj_matrix, weighted = T) | ||
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| # get subgraphs from graph with edges of weight > min_weight | ||
| s1 <- igraph::subgraph.edges(g_adj, igraph::E(g_adj)[igraph::E(g_adj)$weight>min_weight], del=F) | ||
| png('motif_clusters.png') | ||
| plot(s1) | ||
| dev.off() | ||
| clust <- igraph::clusters(s1) | ||
| if (clust$no < 1){ | ||
| b <- lapply(files, function(f){ | ||
| system(paste("cat",f,">",basename(f))) | ||
| }) | ||
| } | ||
| # merge FASTA-files depending on the clustered graphs | ||
| a <- lapply(seq(from = 1, to = clust$no, by = 1), function(i){ | ||
| cl <- as.vector(which(clust$membership %in% c(i))) | ||
| fasta_list <- paste(files[cl], collapse = " ") | ||
| name <- paste0("Cluster_",i,".fasta") | ||
| system(paste("cat",fasta_list,">",name)) | ||
| }) | ||
| } | ||
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| # run function merge_similar with given parameteres if not in interactive context (e.g. run from shell) | ||
| if (!interactive()) { | ||
| merge_similar(opt$input, opt$list, opt$min) | ||
| } | ||
| #!/usr/bin/env Rscript | ||
| if (!require(optparse)) install.packages("optparse"); library(optparse) | ||
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| option_list <- list( | ||
| make_option(opt_str = c("-i", "--input"), default = NULL, help = "Input TSV-file. Output from merged tomtom results", metavar = "character"), | ||
| make_option(opt_str = c("-l", "--list"), default = NULL, help = "Numerically sorted whitespace separated list of absolute fasta-file paths", metavar = "character"), | ||
| make_option(opt_str = c("-w", "--min"), default = NULL, help = "Minimum weight of edge allowed in graph clusters.", metavar = "character") | ||
| ) | ||
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| opt_parser <- OptionParser(option_list = option_list, | ||
| description = "Adding Cluster ID to Query_ID Column", | ||
| epilogue = "Author: Rene Wiegandt <Rene.Wiegandt@mpi-bn.mpg.de>") | ||
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| opt <- parse_args(opt_parser) | ||
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| #' Merging FASTA-files, which motifs are similar. | ||
| #' | ||
| #' @parameter tsv_in <string> Path to TSV file generated by Tomtom. | ||
| #' The input for Tomtom is a from all clusters merged meme-file. | ||
| #' @parameter file_list <string> Numerically sorted comma separated list of absolute fasta-file paths | ||
| #' @parameter min_weight <INT> Minimum weight of edge allowed in graph clusters. | ||
| #' | ||
| #' @author René Wiegandt | ||
| #' @contact rene.wiegandt(at)mpi-bn.mpg.de | ||
| merge_similar <- function(tsv_in, file_list, min_weight){ | ||
|
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| files <- unlist(strsplit(file_list, ",")) | ||
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| # split the string on the character "." in the first to columns and safe the last value each, to get the number of the cluster. | ||
| tsv <- data.table::fread(tsv_in, header = TRUE, sep = "\t",colClasses = 'character') | ||
| query_cluster <- vapply(strsplit(tsv[["Query_ID"]],"\\."), function(l){ | ||
| tail(l, n = 1) | ||
| },"") | ||
| target_cluster <- vapply(strsplit(tsv[["Target_ID"]],"\\."), function(l){ | ||
| tail(l, n = 1) | ||
| },"") | ||
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| # create data.table with only the cluster-numbers | ||
| sim_not_unique <- data.table::data.table(as.numeric(query_cluster),as.numeric(target_cluster)) | ||
|
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| # remove rows if column 1 is identical to column 2 | ||
| edgelist <- sim_not_unique[query_cluster != target_cluster] | ||
|
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| # create graph from data.frame | ||
| g <- igraph::graph_from_edgelist(as.matrix(edgelist)) | ||
| # converting graph to adjacency matrix | ||
| adj_matrix <- igraph::get.adjacency(g, names = T) | ||
| # generating weighted graph from adjacency matrix | ||
| g_adj <- igraph::graph_from_adjacency_matrix(adj_matrix, weighted = T) | ||
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| # get subgraphs from graph with edges of weight > min_weight | ||
| s1 <- igraph::subgraph.edges(g_adj, igraph::E(g_adj)[igraph::E(g_adj)$weight > min_weight], del = F) | ||
| png('motif_clusters.png') | ||
| plot(s1) | ||
| dev.off() | ||
| clust <- igraph::clusters(s1) | ||
| if (clust$no < 1) { | ||
| b <- lapply(files, function(f){ | ||
| system(paste("cat",f,">",basename(f))) | ||
| }) | ||
| } | ||
| # merge FASTA-files depending on the clustered graphs | ||
| a <- lapply(seq(from = 1, to = clust$no, by = 1), function(i){ | ||
| #get vector with cluster ids, which are clustered together in "motif cluster" i | ||
| cl <- as.vector(which(clust$membership %in% c(i))) | ||
| #create string, which represents a list, containing all FASTA-files to be merged | ||
| fasta_list <- paste(files[cl], collapse = " ") | ||
| #create name for merged FASTA-file | ||
| name <- paste0("Cluster_",i,".fasta") | ||
| #merge fasta files | ||
| system(paste("cat",fasta_list,">",name)) | ||
| }) | ||
| } | ||
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| # run function merge_similar with given parameteres if not in interactive context (e.g. run from shell) | ||
| if (!interactive()) { | ||
| merge_similar(opt$input, opt$list, opt$min) | ||
| } |