Improved: Motif clustering #39
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HendrikSchultheis
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HendrikSchultheis
requested changes
Jan 6, 2019
| @@ -1,13 +1,13 @@ | |||
| #!/usr/bin/env Rscript | |||
| library("optparse") | |||
| 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 bed-file. Second last column must be sequences and last column must be the cluster_id.", metavar = "character"), | |||
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cluster_id -> cluster id
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| option_list <- list( | ||
| make_option(opt_str = c("-i", "--input"), default = NULL, help = "Input bed-file. Second last column must be sequences and last column must be the cluster_id.", metavar = "character"), | ||
| make_option(opt_str = c("-p", "--prefix"), default = "" , help = "Prefix for file names. Default = '%default'", metavar = "character"), | ||
| make_option(opt_str = c("-m", "--min_seq"), default = 100, help = "Minimum amount of sequences in clusters. Default = %default", metavar = "integer") | ||
| ) | ||
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| opt_parser <- OptionParser(option_list = option_list, | ||
| opt_parser <- OptionParser(option_list = option_list, | ||
| description = "Convert BED-file to one FASTA-file per cluster") |
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Author and email are missing.
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| option_list <- list( | ||
| make_option(opt_str = c("-i", "--input"), default = NULL, help = "Input bed-file. Second last column must be sequences and last column must be the cluster_id.", metavar = "character"), | ||
| make_option(opt_str = c("-p", "--prefix"), default = "" , help = "Prefix for file names. Default = '%default'", metavar = "character"), | ||
| make_option(opt_str = c("-m", "--min_seq"), default = 100, help = "Minimum amount of sequences in clusters. Default = %default", metavar = "integer") | ||
| ) | ||
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| opt_parser <- OptionParser(option_list = option_list, | ||
| opt_parser <- OptionParser(option_list = option_list, | ||
| description = "Convert BED-file to one FASTA-file per cluster") | ||
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| opt <- parse_args(opt_parser) |
There was a problem hiding this comment.
The Sequences of each cluster are written as an FASTA-file.
| if (is.null(bedInput)) { | ||
| stop("ERROR: Input parameter cannot be null! Please specify the input parameter.") | ||
| } | ||
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| bed <- data.table::fread(bedInput, sep = "\t") | ||
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| # Get last column of data.table, which refers to the cluster, as a vector. | ||
| cluster_no <- as.vector(bed[[ncol(bed)]]) |
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You can remove as.vector. Using [[]] already returns a vector.
| # Split data.table bed on its last column (cluster_no) into list of data.frames | ||
| clusters <- split(bed, cluster_no, sorted = TRUE, flatten = FALSE) | ||
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| # For each data.frame(cluster) in list clusters: | ||
| discard <- lapply(1:length(clusters), function(i){ |
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It's nicer to use seq_len instead of 1:x.
| #' @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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The as.list is redundant strsplit already returns a 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){ |
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Use vapply instead it already returns a vector.
| tail(l,n=1) | ||
| })) | ||
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| # create data.table with only the cluster-numbers |
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You don't have to convert later if you create your data.table with numeric columns right away.
| 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 |
| system(paste("cat",f,">",basename(f))) | ||
| }) | ||
| } | ||
| # merge FASTA-files depending on the clustered graphs |
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One or two more comments would be nice in this lapply.
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Link #16 |
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Improved motif clustering by comparing the motifs of each cluster separately with the merged motif file.
Added new R-script which labels the TSV-files with the corresponding cluster ID.