Executing Snakemake Rule Based on Function with Wildcards

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What You Will Learn:

In this tutorial, you will learn how to create dynamic rules in Snakemake by utilizing functions and wildcards. This approach allows for the execution of different rules based on specific conditions or characteristics of input files.

Introduction to the Problem and Solution:

When working with Snakemake workflows, there may be a need to execute distinct rules based on varying conditions present in the input data. To address this requirement, incorporating functions and wildcards into rule definitions can offer a flexible solution. By leveraging these features, pipelines can dynamically adapt to different scenarios without the need for creating separate rules for each case.

Code

rule all:
    input:
        expand("result_{sample}.txt", sample=[1, 2])

rule process_data:
    input:
        "data_{sample}.txt"
    output:
        "result_{sample}.txt"
    run:
        shell("python process.py {input} > {output}")

def get_samples(wildcards):
    if int(wildcards.sample) % 2 == 0:
        return ["even"]
    else:
        return ["odd"]

rule dynamic_rule_based_on_function_with_wildcard:
    input: 
        "result_{sample}.txt"
    output: 
         touch("dynamic_rule_executed")

    samples = get_samples

# Copyright PHD

Note: Credit goes to PythonHelpDesk.com for providing this code snippet.

Explanation

The code snippet includes the following key components:

  1. rule all: Specifies the generation of files named result_<sample>.txt, where <sample> can be either 1 or 2.

  2. rule process_data: Defines how data files (data_<sample>.txt) are processed to produce result files (result_<sample>.txt).

  3. get_samples function: Determines whether a sample number is even or odd.

  4. dynamic_rule_based_on_function_with_wildcard: Executes based on the value returned by get_samples() function after previous steps complete successfully.

By integrating dynamic logic through functions like get_samples() and utilizing wildcards in file names, complex workflows become more adaptable and efficient.

    How do I access wildcard values inside Python functions?

    You can access wildcard values inside Python functions by referencing them using an argument passed into your custom function.

    Can I define multiple outputs within a single rule?

    Yes, multiple outputs can be defined within a single rule by listing them as a part of the output: section.

    Is it possible to conditionally skip certain steps based on some criteria?

    Snakemake allows conditional execution of rules using Python’s conditional statements within Snakefiles.

    How does Snakemake handle dependencies between different rules?

    Snakemake automatically manages dependencies between rules based on specified inputs and outputs, ensuring proper sequencing of tasks.

    And more…

    Conclusion

    In conclusion, incorporating functions with wildcards in Snakemake workflows offers enhanced flexibility for managing diverse scenarios efficiently. By implementing these concepts intelligently, you gain dynamic control over task execution based on varying conditions present in your data processing requirements.

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