.. _`bio/tximport`:

TXIMPORT
========


.. image:: https://img.shields.io/github/issues-pr/snakemake/snakemake-wrappers/bio/tximport?label=version%20update%20pull%20requests
   :target: https://github.com/snakemake/snakemake-wrappers/pulls?q=is%3Apr+is%3Aopen+label%3Abio/tximport

Import and summarize transcript-level estimates for both transcript-level
and gene-level analysis.



Example
-------

This wrapper can be used in the following way:

.. code-block:: python

    rule tximport:
        input:
            quant = expand("quant/A/quant.sf")
            # Optional transcript/gene links as described in tximport
            # tx2gene = /path/to/tx2gene
        output:
            txi = "txi.RDS"
        params:
            extra = "type='salmon', txOut=TRUE"
        wrapper:
            "v3.0.1/bio/tximport"

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.


Notes
-----

Add any tximport options in the params, they will be transmitted through the
R wrapper. Supplementary options will cause unknown parameters error.


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

* ``bioconductor-tximport=1.28.0``
* ``r-readr=2.1.4``
* ``r-jsonlite=1.8.7``

Input/Output
------------
**Input:**

* A list of paths to count data

**Output:**

* A tximport RDS object




Authors
-------

* Thibault Dayris


Code
----

.. code-block:: R

    #!/bin/R

    # Loading library
    base::library("tximport");   # Perform actual count importation in R
    base::library("readr");      # Read faster!
    base::library("jsonlite");   # Importing inferential replicates

    # Cast input paths as character to avoid errors
    samples_paths <- sapply(               # Sequentially apply
      snakemake@input[["quant"]],          # ... to all quantification paths
      function(quant) as.character(quant)  # ... a cast as character
    );

    # Collapse path into a character vector
    samples_paths <- base::paste0(samples_paths, collapse = '", "');

    # Building function arguments
    extra <- base::paste0('files = c("', samples_paths, '")');

    # Check if user provided optional transcript to gene table
    if ("tx_to_gene" %in% names(snakemake@input)) {
      tx2gene <- readr::read_tsv(snakemake@input[["tx_to_gene"]]);
      extra <- base::paste(
        extra,                 # Foreward existing arguments
        ", tx2gene = ",        # Argument name
        "tx2gene"              # Add tx2gene to parameters
      );
    }

    # Add user defined arguments
    if ("extra" %in% names(snakemake@params)) {
      if (snakemake@params[["extra"]] != "") {
        extra <- base::paste(
          extra,                       # Foreward existing parameters
          snakemake@params[["extra"]], # Add user parameters
          sep = ", "                   # Field separator
        );
      }
    }


    print(extra);
    # Perform tximport work
    txi <- base::eval(                        # Evaluate the following
      base::parse(                            # ... parsed expression
        text = base::paste0(
          "tximport::tximport(", extra, ");"  # ... of tximport and its arguments
        )
      )
    );

    # Save results
    base::saveRDS(                       # Save R object
      object = txi,                      # The txi object
      file = snakemake@output[["txi"]]   # Output path is provided by Snakemake
    );


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