Counts the number of reads in samples — read

This function counts the number of reads in samples present in the specified folder. Useful if you don't have the info (e.g. generated by stacks process_radtags), and you want to check the distribution in the number of reads between samples.

read_counter(
  path.samples,
  recursive = FALSE,
  strata = NULL,
  plot.reads = TRUE,
  write = TRUE,
  parallel.core = parallel::detectCores() - 1
)

Arguments

path.samples	(character, path) Path of folder containing the samples to count reads
recursive	(logical) Should the listing recurse into the directory? e.g. when `path.samples` contains nested folders with FQ files. Default: `recursive = FALSE`.
strata	(optional) The strata file is a tab delimited file with 2 columns headers: `INDIVIDUALS` and `STRATA`. The `STRATA` column can be any hierarchical grouping. To create a strata file see individuals2strata. If you have already run stacks on your data, the strata file is similar to a stacks population map file, make sure you have the required column names (`INDIVIDUALS` and `STRATA`). Note: Make sure that the fastq file names (without extension) match the INDIVIDUALS column in the strata file. With default, figures are generated without strata grouping. Default: `strata = NULL`.
plot.reads	With default `plot.reads = TRUE`, the distribution and boxplot figures are generated and written in the directory.
write	With default `write = TRUE`, the data frame with read counts and figures are is written in the working directory.
parallel.core	(optional) The number of core for parallel computing. By default: `parallel.core = parallel::detectCores() - 1`.

Value

a list with a data frame with the sample id and the number of reads. If option to generate figures was selected, the list also returns 2 figures (see example below)

Examples

if (FALSE) {
library(stackr)
# To run this function, bioconductor \code{ShortRead} package is necessary:
source("http://bioconductor.org/biocLite.R")
biocLite("ShortRead")

# Using OpenMP threads
nthreads <- .Call(ShortRead:::.set_omp_threads, 1L)
on.exit(.Call(ShortRead:::.set_omp_threads, nthreads))

# with defaults
read.info <- stackr::read_counter(path.samples = "corals")

# to extract info from the list
reads = read.info$reads
reads.distribution <- read.info$reads.distribution
reads.boxplot <- read.info$reads.boxplot

# If the default figures saved were not good, save with new width and height
# the histogram
ggplot2::ggsave(
filename = "reads.distribution.pdf",
plot = reads.distribution,
width = 15, height = 15,
dpi = 600, units = "cm", useDingbats = FALSE, limitsize = FALSE)

# the boxplot
ggplot2::ggsave(
filename = "reads.boxplot.pdf",
plot = reads.boxplot,
width = 15, height = 15,
dpi = 600, units = "cm", useDingbats = FALSE, limitsize = FALSE)
}