DADA2_SAMPLE_INFERENCE

DADA2 Inferring sample composition using dada2 dada function. Optional parameters are documented in the manual and the function is introduced in the dedicated tutorial section.

Example

This wrapper can be used in the following way:

rule dada2_sample_inference:
    input:
    # Dereplicated (aka unique) sequences of the sample
        derep="uniques/{fastq}.RDS",
        err="results/dada2/model_1.RDS" # Error model
    output:
        "denoised/{fastq}.RDS" # Inferred sample composition
    # Even though this is an R wrapper, use named arguments in Python syntax
    # here, to specify extra parameters. Python booleans (`arg1=True`, `arg2=False`)
    # and lists (`list_arg=[]`) are automatically converted to R.
    # For a named list as an extra named argument, use a python dict
    #   (`named_list={name1=arg1}`).
    #params:
    #    verbose=True
    log:
        "logs/dada2/sample-inference/{fastq}.log"
    threads: 1 # set desired number of threads here
    wrapper:
        "0.72.0/bio/dada2/sample-inference"

Note that input, output and log file paths can be chosen freely. When running with

snakemake --use-conda

the software dependencies will be automatically deployed into an isolated environment before execution.

Software dependencies

  • bioconductor-dada2==1.16

Input/Output

Input:

  • derep: RDS file with the dereplicated sequences
  • err: RDS file with the error model

Output:

  • RDS file with the stored inferred sample composition

Authors

  • Charlie Pauvert

Code

# __author__ = "Charlie Pauvert"
# __copyright__ = "Copyright 2020, Charlie Pauvert"
# __email__ = "cpauvert@protonmail.com"
# __license__ = "MIT"

# Snakemake wrapper for inferring sample composition using dada2 dada function.

# Sink the stderr and stdout to the snakemake log file
# https://stackoverflow.com/a/48173272
log.file<-file(snakemake@log[[1]],open="wt")
sink(log.file)
sink(log.file,type="message")

library(dada2)

# Prepare arguments (no matter the order)
args<-list(
           derep = readRDS(snakemake@input[["derep"]]),
           err = readRDS(snakemake@input[["err"]]),
           multithread = snakemake@threads
           )
# Check if extra params are passed
if(length(snakemake@params) > 0 ){
       # Keeping only the named elements of the list for do.call()
       extra<-snakemake@params[ names(snakemake@params) != "" ]
       # Add them to the list of arguments
       args<-c(args, extra)
} else{
    message("No optional parameters. Using default parameters from dada2::dada()")
}

# Learn errors rates for both read types
inferred_composition<-do.call(dada, args)

# Store the inferred sample composition as RDS files
saveRDS(inferred_composition, snakemake@output[[1]],compress = T)

# Proper syntax to close the connection for the log file
# but could be optional for Snakemake wrapper
sink(type="message")
sink()