.. _`bio/dada2/sample-inference`:

DADA2_SAMPLE_INFERENCE
======================


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`DADA2 <https://benjjneb.github.io/dada2/index.html>`_
Inferring sample composition using dada2 ``dada`` function. Optional parameters are documented in the `manual <https://www.bioconductor.org/packages/release/bioc/manuals/dada2/man/dada2.pdf#dada>`_  and the function is introduced in the dedicated tutorial `section <https://benjjneb.github.io/dada2/tutorial.html#sample-inference>`_.



Example
-------

This wrapper can be used in the following way:

.. code-block:: python

    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:
            "v3.0.1/bio/dada2/sample-inference"

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

When running with

.. code-block:: bash

    snakemake --use-conda

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


Software dependencies
---------------------

* ``bioconductor-dada2=1.28.0``

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



Params
------

* ``optional arguments for ``dada()``, please provide them as python ``key=value`` pairs``: 




Authors
-------

* Charlie Pauvert


Code
----

.. code-block:: R

    # __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()


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