Overview

Teaching: 15 min
Exercises: 0 min
Questions
  • How can I define rules to operate on similar files?

Objectives
  • Write Snakemake pattern rules.

Our Snakefile still has a ton of repeated content. The rules for each .dat file all do the same thing for the part. We can replace these rules with a single pattern rule which can be used to build any .dat file from a .txt file in books/:

rule count_words:
    input: 	
        wc='wordcount.py',
        book='books/{file}.txt'
    output: '{file}.dat'
    shell: 	'python {input.wc} {input.book} {output}'

{file} is another arbitrary wildcard, that we can use as a placeholder for any generic book to analyze. Note that we don’t have to use {file} as the name of our wildcard - it can be anything we want!

This rule can be interpreted as: “In order to build a file named [something].dat (the target) find a file named books/[that same something].txt (the dependency) and run wordcount.py [the dependency] [the target].”

snakemake clean
# use the -p option to show that it is running things correctly!
snakemake -p dats   

We should see the same output as before. Note that we can still use snakemake to build individual .dat targets as before, and that our new rule will work no matter what stem is being matched.

snakemake -p sierra.dat

which gives the output below:

Provided cores: 1
Rules claiming more threads will be scaled down.
Job counts:
	count	jobs
	1	count_words
	1

rule count_words:
    input: wordcount.py, books/sierra.txt
    output: sierra.dat
    jobid: 0
    wildcards: file=sierra

python wordcount.py books/sierra.txt sierra.dat
Finished job 0.
1 of 1 steps (100%) done

Using wildcards

Our arbitrary wildcards like {file} can only be used in input: and output: fields. It cannot be used in actions.

Our Snakefile is now much shorter and cleaner:

# generate summary table
rule zipf_test:
    input:  'zipf_test.py', 'abyss.dat', 'last.dat', 'isles.dat'
    output: 'results.txt'
    shell:  'python {input[0]} {input[1]} {input[2]} {input[3]} > {output}'

rule dats:
     input:
         'isles.dat', 'abyss.dat', 'last.dat'

# delete everything so we can re-run things
rule clean:
    shell:  'rm -f *.dat results.txt'

# count words in one of our "books"
rule count_words:
    input: 	
        wc='wordcount.py',
        book='books/{file}.txt'
    output: '{file}.dat'
    shell: 	'python {input.wc} {input.book} {output}'

Key Points