Add updated writeBigWig function

bin/nucDyn.R

@@ -13,6 +13,7 @@ suppressPackageStartupMessages(library(NucDyn))
 suppressPackageStartupMessages(library(plyr))
 suppressPackageStartupMessages(library(parallel))
 
+
 where <- function () {
     spath <- parent.frame(2)$ofile
 
@@ -126,15 +127,13 @@ hs <- findHotspots(dyn=dyn, nuc=nuc, mc.cores=params$cores ,
 
 ## Calculate vector of -log10(p-value)s  ######################################
 message("calculate p-val")
-
 cov1 <- lapply(coverage(as(rs[[1]], "GRanges")), as.vector)
 cov2 <- lapply(coverage(as(rs[[2]], "GRanges")), as.vector)
 
 chrs <- intersect(names(cov1), names(cov2))
 pvals <- lapply(chrs, function (x) -log10(findPVals(cov1[[x]], cov2[[x]])))
 names(pvals) <- chrs
 
-
 ## Store the Result ###########################################################
 
 names(hs)[names(hs) == "type"] <- "class"
@@ -148,10 +147,15 @@ writeGff(df2gff(hs,
          params$outputGff)
 
 message("saving bigWig output")
-writeBigWig(lapply(pvals, splitAtZeros),
-            params$outputBigWig,
-            params$genome)
+
+writeBigWig_updated(pvals,
+                    params$outputBigWig,
+                    params$genome)
+
+# writeBigWig(lapply(pvals, splitAtZeros),
+#             params$outputBigWig,
+#             params$genome)
 
 message("done")
 
-###############################################################################
+###############################################################################

bin/periodicity.R

@@ -114,7 +114,10 @@ gff <- df2gff(genes.nucs,
 writeGff(gff, params$gffOutput)
 
 message("writing bigWig output")
-splited <- lapply(covPredAll, splitAtZeros)
-writeBigWig(splited, params$bwOutput, params$chrom_sizes)
+# splited <- lapply(covPredAll, splitAtZeros)
+# writeBigWig(splited, params$bwOutput, params$chrom_sizes)
+writeBigWig_updated(covPredAll,
+                    params$bwOutput,
+                    params$chrom_sizes)
 
 ##############################################################################

sourced/wig_funs.R

@@ -3,6 +3,10 @@
 ## Imports ####################################################################
 
 suppressPackageStartupMessages(library(IRanges))
+suppressPackageStartupMessages(library(plyranges))
+suppressPackageStartupMessages(library(purrr))
+suppressPackageStartupMessages(library(dplyr))
+suppressPackageStartupMessages(library(readr))
 source(paste(SOURCE.DIR, "get_genes.R", sep="/"))
 
 ## Binary paths ###############################################################
@@ -118,5 +122,39 @@ writeBigWig <- function (x, outf, chrom.sizes.f)
     file.remove(wigf)
     invisible()
 }
+# This function takes a list of vectors (x) representing signal scores across genomic regions and writes the data to a bigWig file format
+# Additionally it uses a file path to write the resulting bigWig file (outf),
+# and a file path to a file with chromosome sizes in tab seperated form (chrom.sizes.f)
+writeBigWig_updated <- function (x, outf, chrom.sizes.f) {
+
+  # Map over the input vectors to create a tibble for each vector with four columns:
+  # score, start position, width, and strand (* indicates unstranded).
+  # Combine all tibbles into a single data frame using map_df().
+  # Use .id = "seqnames" to create a new column seqnames, which contains the names of the vectors in x.
+  gr <- purrr::map_df(x,
+                      function(y) 
+                      {dplyr::tibble(score = y,
+                                     start = 1:length(y),
+                                     width = 1,
+                                     strand = "*")},
+                      .id = "seqnames") %>% 
+    as_granges()
+
+  # Read in a file containing chromosome sizes into a data frame.
+  # The file is assumed to have two columns separated by tabs: chromosome name and size.
+  chrSizes <- readr::read_delim(chrom.sizes.f,
+                                col_names = c("seqnames","size"),
+                                delim = "\t",
+                                show_col_types = FALSE)
+
+  # Filter the chromosome sizes data frame to include only the chromosomes that are present in the granges object.
+  chrSizes <- filter(chrSizes, seqnames %in% seqnames(gr)) 
+
+  # Set the sequence lengths of the granges object to the chromosome sizes in chrSizes.
+  seqlengths(gr) <- chrSizes$size
+
+  # Write the granges object to a bigWig file at the specified output path.
+  write_bigwig(gr, outf)
+}
 
 ###############################################################################