runSalmon: Run Salmon on FASTQ files to quantify feature abundance

In dynverse/scaterlegacy: Single-cell analysis toolkit for gene expression data in R

Description

Run the abundance quantification tool Salmon on a set of FASTQ files. Requires Salmon (https://combine-lab.github.io/salmon/) to be installed and a Salmon transcript index must have been generated prior to using this function. See the Salmon website for installation and basic usage instructions.

Usage

runSalmon(targets_file, transcript_index, single_end = FALSE,
  output_prefix = "output", lib_type = "A", n_processes = 2,
  n_thread_per_process = 4, n_bootstrap_samples = 0, seqBias = TRUE,
  gcBias = TRUE, posBias = FALSE, allowOrphans = FALSE,
  advanced_opts = NULL, verbose = TRUE, dry_run = FALSE,
  salmon_cmd = "salmon")

Arguments

targets_file	character string giving the path to a tab-delimited text file with either 2 columns (single-end reads) or 3 columns (paired-end reads) that gives the sample names (first column) and FastQ file names (column 2 and if applicable 3). The file is assumed to have column headers, although these are not used.
transcript_index	character string giving the path to the Salmon index to be used for the feature abundance quantification.
single_end	logical, are single-end reads used, or paired-end reads?
output_prefix	character string giving the prefix for the output folder that will contain the Salmon results. The default is "output" and the sample name (column 1 of targets_file) is appended (preceded by an underscore).
lib_type	scalar, indicating RNA-seq library type. See Salmon documentation for details. Default is "A", for automatic detection.
n_processes	integer giving the number of processes to use for parallel Salmon jobs across samples. The package parallel is used. Default is 2 concurrent processes.
n_thread_per_process	integer giving the number of threads for Salmon to use per process (to parallelize Salmon for a given sample). Default is 4.
n_bootstrap_samples	integer giving the number of bootstrap samples that Salmon should use (default is 0). With bootstrap samples, uncertainty in abundance can be quantified.
seqBias	logical, should Salmon's option be used to model and correct abundances for sequence specific bias? Default is TRUE.
gcBias	logical, should Salmon's option be used to model and correct abundances for GC content bias? Requires Salmon version 0.7.2 or higher. Default is TRUE.
posBias	logical, should Salmon's option be used to model and correct abundances for positional biases? Requires Salmon version 0.7.3 or higher. Default is FALSE.
allowOrphans	logical, Consider orphaned reads as valid hits when performing lightweight-alignment. This option will increase sensitivity (allow more reads to map and more transcripts to be detected), but may decrease specificity as orphaned alignments are more likely to be spurious. For more details see Salmon documentation.
advanced_opts	character scalar supplying list of advanced option arguments to apply to each Salmon call. For details see Salmon documentation or type salmon quant --help-reads at the command line.
verbose	logical, should timings for the run be printed?
dry_run	logical, if TRUE then a list containing the Salmon commands that would be run and the output directories is returned. Can be used to read in results if Salmon is run outside an R session or to produce a script to run outside of an R session.
salmon_cmd	(optional) string giving full command to use to call Salmon, if simply typing "salmon" at the command line does not give the required version of Salmon or does not work. Default is simply "salmon". If used, this argument should give the full path to the desired Salmon binary.

Details

A Salmon transcript index can be built from a FASTA file: salmon index [arguments] FASTA-file. See the Salmon documentation for further details. This simple wrapper does not give access to all nuances of Salmon usage. For finer-grained usage of Salmon please run it at the command line - results can still be read into R with readSalmonResults.

Value

A list containing three elements for each sample for which feature abundance has been quantified: (1) salmon_call, the call used for Salmon, (2) salmon_log the log generated by Salmon, and (3) output_dir the directory in which the Salmon results can be found.

Examples

## Not run: 
## If in Salmon's 'test' directory, then try these calls:
## Generate 'targets.txt' file:
write.table(data.frame(Sample="sample1", File1="reads_1.fastq.gz", File2="reads_1.fastq.gz"),
 file="targets.txt", quote=FALSE, row.names=FALSE, sep="\t")
Salmon_log <- runSalmon("targets.txt", "transcripts.idx", single_end=FALSE,
         output_prefix="output", verbose=TRUE, n_bootstrap_samples=10,
         dry_run = FALSE)

## End(Not run)

dynverse/scaterlegacy documentation built on Feb. 17, 2020, 5:07 a.m.