comparison edger.R @ 15:5bf899c13979 draft default tip

planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/edger commit 025a0d70be99e50ae89ad78a70cc8c51571ea1a2

14:070900306913

unmake_names <- function(string) {
  string <- gsub(".", " ", string, fixed = TRUE)
  return(string)
}

# Generate output folder and paths
make_out <- function(filename) {
  return(paste0(out_path, "/", filename))
}

ql_pdf <- make_out("qlplot.pdf")
ql_png <- make_out("qlplot.png")
mds_pdf <- character() # Initialise character vector
mds_png <- character()
for (i in seq_len(ncol(factors))) {
  mds_pdf[i] <- make_out(paste0("mdsplot_", names(factors)[i], ".pdf"))
  mds_png[i] <- make_out(paste0("mdsplot_", names(factors)[i], ".png"))
}
md_pdf <- character()
md_png <- character()
top_out <- character()
for (i in seq_along(contrast_data)) {
  md_pdf[i] <- make_out(paste0("mdplot_", contrast_data[i], ".pdf"))
  md_png[i] <- make_out(paste0("mdplot_", contrast_data[i], ".png"))
  top_out[i] <- make_out(paste0("edgeR_", contrast_data[i], ".tsv"))
} # Save output paths for each contrast as vectors
norm_out <- make_out("edgeR_normcounts.tsv")
rda_out <- make_out("edgeR_analysis.RData")
session_out <- make_out("session_info.txt")

labels <- names(counts)

# MDS plot
png(mds_png, width = 600, height = 600)
plotMDS(data, labels = labels, col = as.numeric(factors[, 1]), cex = 0.8, main = paste("MDS Plot:", names(factors)[1]))
img_name <- paste0("MDS Plot_", names(factors)[1], ".png")
img_addr <- paste0("mdsplot_", names(factors)[1], ".png")
image_data[1, ] <- c(img_name, img_addr)
invisible(dev.off())

pdf(mds_pdf)
plotMDS(data, labels = labels, col = as.numeric(factors[, 1]), cex = 0.8, main = paste("MDS Plot:", names(factors)[1]))
link_name <- paste0("MDS Plot_", names(factors)[1], ".pdf")
link_addr <- paste0("mdsplot_", names(factors)[1], ".pdf")
link_data[1, ] <- c(link_name, link_addr)
invisible(dev.off())

# If additional factors create additional MDS plots coloured by factor
if (ncol(factors) > 1) {
  for (i in 2:ncol(factors)) {
    png(mds_png[i], width = 600, height = 600)
    plotMDS(data, labels = labels, col = as.numeric(factors[, i]), cex = 0.8, main = paste("MDS Plot:", names(factors)[i]))
    img_name <- paste0("MDS Plot_", names(factors)[i], ".png")
    img_addr <- paste0("mdsplot_", names(factors)[i], ".png")
    image_data <- rbind(image_data, c(img_name, img_addr))
    invisible(dev.off())

    pdf(mds_pdf[i])
    plotMDS(data, labels = labels, col = as.numeric(factors[, i]), cex = 0.8, main = paste("MDS Plot:", names(factors)[i]))
    link_name <- paste0("MDS Plot_", names(factors)[i], ".pdf")
    link_addr <- paste0("mdsplot_", names(factors)[i], ".pdf")
    link_data <- rbind(link_data, c(link_name, link_addr))
    invisible(dev.off())
  }
}

  # Write top expressions table
  top <- topTags(res, adjust.method = opt$pAdjOpt, n = Inf, sort.by = "PValue")
  write.table(top, file = top_out[i], row.names = FALSE, sep = "\t", quote = FALSE)

  link_name <- paste0("edgeR_", contrast_data[i], ".tsv")
  link_addr <- paste0("edgeR_", contrast_data[i], ".tsv")
  link_data <- rbind(link_data, c(link_name, link_addr))

  # Plot MD (log ratios vs mean difference) using limma package
  pdf(md_pdf[i])
  limma::plotMD(res,

    xlab = "Average Expression", ylab = "logFC"
  )

  abline(h = 0, col = "grey", lty = 2)

  link_name <- paste0("MD Plot_", contrast_data[i], ".pdf")
  link_addr <- paste0("mdplot_", contrast_data[i], ".pdf")
  link_data <- rbind(link_data, c(link_name, link_addr))
  invisible(dev.off())

  png(md_png[i], height = 600, width = 600)
  limma::plotMD(res,

    xlab = "Average Expression", ylab = "logFC"
  )

  abline(h = 0, col = "grey", lty = 2)

  img_name <- paste0("MD Plot_", contrast_data[i], ".png")
  img_addr <- paste0("mdplot_", contrast_data[i], ".png")
  image_data <- rbind(image_data, c(img_name, img_addr))
  invisible(dev.off())
}
sig_diff <- data.frame(Up = up_count, Flat = flat_count, Down = down_count)
row.names(sig_diff) <- contrast_data

15:5bf899c13979

unmake_names <- function(string) {
  string <- gsub(".", " ", string, fixed = TRUE)
  return(string)
}

# Sanitise file base names coming from factors or contrasts
sanitise_basename <- function(string) {
  string <- gsub("[/^]", "_", string)
  return(string)
}

# Generate output folder and paths
make_out <- function(filename) {
  return(paste0(out_path, "/", filename))
}

ql_pdf <- make_out("qlplot.pdf")
ql_png <- make_out("qlplot.png")
mds_pdf <- character() # Initialise character vector
mds_png <- character()
for (i in seq_len(ncol(factors))) {
  mds_pdf[i] <- make_out(paste0("mdsplot_", sanitise_basename(names(factors)[i]), ".pdf"))
  mds_png[i] <- make_out(paste0("mdsplot_", sanitise_basename(names(factors)[i]), ".png"))
}
md_pdf <- character()
md_png <- character()
top_out <- character()
for (i in seq_along(contrast_data)) {
  md_pdf[i] <- make_out(paste0("mdplot_", sanitise_basename(contrast_data[i]), ".pdf"))
  md_png[i] <- make_out(paste0("mdplot_", sanitise_basename(contrast_data[i]), ".png"))
  top_out[i] <- make_out(paste0("edgeR_", sanitise_basename(contrast_data[i]), ".tsv"))
} # Save output paths for each contrast as vectors
norm_out <- make_out("edgeR_normcounts.tsv")
rda_out <- make_out("edgeR_analysis.RData")
session_out <- make_out("session_info.txt")

labels <- names(counts)

# MDS plot
png(mds_png, width = 600, height = 600)
plotMDS(data, labels = labels, col = as.numeric(factors[, 1]), cex = 0.8, main = paste("MDS Plot:", names(factors)[1]))
img_name <- paste0("MDS Plot_", sanitise_basename(names(factors)[1]), ".png")
img_addr <- paste0("mdsplot_", sanitise_basename(names(factors)[1]), ".png")
image_data[1, ] <- c(img_name, img_addr)
invisible(dev.off())

pdf(mds_pdf)
plotMDS(data, labels = labels, col = as.numeric(factors[, 1]), cex = 0.8, main = paste("MDS Plot:", names(factors)[1]))
link_name <- paste0("MDS Plot_", sanitise_basename(names(factors)[1]), ".pdf")
link_addr <- paste0("mdsplot_", sanitise_basename(names(factors)[1]), ".pdf")
link_data[1, ] <- c(link_name, link_addr)
invisible(dev.off())

# If additional factors create additional MDS plots coloured by factor
if (ncol(factors) > 1) {
  for (i in 2:ncol(factors)) {
    png(mds_png[i], width = 600, height = 600)
    plotMDS(data, labels = labels, col = as.numeric(factors[, i]), cex = 0.8, main = paste("MDS Plot:", names(factors)[i]))
    img_name <- paste0("MDS Plot_", sanitise_basename(names(factors)[i]), ".png")
    img_addr <- paste0("mdsplot_", sanitise_basename(names(factors)[i]), ".png")
    image_data <- rbind(image_data, c(img_name, img_addr))
    invisible(dev.off())

    pdf(mds_pdf[i])
    plotMDS(data, labels = labels, col = as.numeric(factors[, i]), cex = 0.8, main = paste("MDS Plot:", names(factors)[i]))
    link_name <- paste0("MDS Plot_", sanitise_basename(names(factors)[i]), ".pdf")
    link_addr <- paste0("mdsplot_", sanitise_basename(names(factors)[i]), ".pdf")
    link_data <- rbind(link_data, c(link_name, link_addr))
    invisible(dev.off())
  }
}

  # Write top expressions table
  top <- topTags(res, adjust.method = opt$pAdjOpt, n = Inf, sort.by = "PValue")
  write.table(top, file = top_out[i], row.names = FALSE, sep = "\t", quote = FALSE)

  link_name <- paste0("edgeR_", sanitise_basename(contrast_data[i]), ".tsv")
  link_addr <- paste0("edgeR_", sanitise_basename(contrast_data[i]), ".tsv")
  link_data <- rbind(link_data, c(link_name, link_addr))

  # Plot MD (log ratios vs mean difference) using limma package
  pdf(md_pdf[i])
  limma::plotMD(res,

    xlab = "Average Expression", ylab = "logFC"
  )

  abline(h = 0, col = "grey", lty = 2)

  link_name <- paste0("MD Plot_", sanitise_basename(contrast_data[i]), ".pdf")
  link_addr <- paste0("mdplot_", sanitise_basename(contrast_data[i]), ".pdf")
  link_data <- rbind(link_data, c(link_name, link_addr))
  invisible(dev.off())

  png(md_png[i], height = 600, width = 600)
  limma::plotMD(res,

    xlab = "Average Expression", ylab = "logFC"
  )

  abline(h = 0, col = "grey", lty = 2)

  img_name <- paste0("MD Plot_", sanitise_basename(contrast_data[i]), ".png")
  img_addr <- paste0("mdplot_", sanitise_basename(contrast_data[i]), ".png")
  image_data <- rbind(image_data, c(img_name, img_addr))
  invisible(dev.off())
}
sig_diff <- data.frame(Up = up_count, Flat = flat_count, Down = down_count)
row.names(sig_diff) <- contrast_data