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Run Salmon Quantification

Source: R/salmon_utils.R
salmon_quant.Rd

Perform transcript quantification using Salmon's selective-alignment-based mode from raw RNA-seq reads.

Usage

salmon_quant(
  input_r1,
  input_r2 = NULL,
  index_path = "salmon_index",
  output_dir = "quant_output",
  num_threads = 8,
  num_gibbs = 30,
  min_score_fraction = "0.65",
  env_name = "salmon-env"
)

Arguments

input_r1

Path to the FASTQ file for read 1 (or single-end reads).

input_r2

Optional path to the FASTQ file for read 2 (paired-end reads).

index_path

Path to the Salmon index directory (default is "salmon_index").

output_dir

Directory to save the quantification output (default is "quant_output").

num_threads

Number of threads to use (default is 8).

num_gibbs

Number of Gibbs samples (inferential replicates) drawn per sample (default is 30). They quantify how well each transcript abundance is determined by the reads and are used by add_uncertainty() and by swish; 30 is enough for those summaries, and more only costs time and disk space. Set it to 0 to skip them.

min_score_fraction

Minimum score fraction for alignments (default is "0.65").

env_name

Name of the conda environment with Salmon installed (default is "salmon-env").

Value

processx style output list.

Details

The command enables the sequence, GC and positional bias corrections, allows dovetailing mates and soft-clipped overhangs, writes the equivalence classes with their weights (--dumpEq --dumpEqWeights) and draws num_gibbs Gibbs samples (aux_info/bootstrap/) so that inferential replicates are available for swish. Selective alignment and the variational Bayes optimiser are Salmon defaults and are not passed explicitly; Salmon 2 quantifies deterministically (identical output for any thread count). Single-end reads are passed with --unmatedReads.