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.. include:: ../../global.inc
.. include:: manual_chapter_numbers.inc
.. _new_manual.transform.code:
##############################################################################################################
|new_manual.introduction.chapter_num|: Python Code for Transforming data in a pipeline with ``@transform``
##############################################################################################################
.. seealso::
* :ref:`Manual Table of Contents <new_manual.table_of_contents>`
* :ref:`@transform syntax in detail <decorators.transform>`
* Back to |new_manual.transform.chapter_num|: :ref:`Transforming data in a pipeline with @transform <new_manual.transform>`
*******************************************
Your first Ruffus script
*******************************************
.. code-block:: python
#
# The starting data files would normally exist beforehand!
# We create some empty files for this example
#
starting_files = [("a.1.fastq", "a.2.fastq"),
("b.1.fastq", "b.2.fastq"),
("c.1.fastq", "c.2.fastq")]
for ff_pair in starting_files:
open(ff_pair[0], "w")
open(ff_pair[1], "w")
from ruffus import *
#
# STAGE 1 fasta->sam
#
@transform(starting_files, # Input = starting files
suffix(".1.fastq"), # suffix = .1.fastq
".sam") # Output suffix = .sam
def map_dna_sequence(input_files,
output_file):
# remember there are two input files now
ii1 = open(input_files[0])
ii2 = open(input_files[1])
oo = open(output_file, "w")
#
# STAGE 2 sam->bam
#
@transform(map_dna_sequence, # Input = previous stage
suffix(".sam"), # suffix = .sam
".bam") # Output suffix = .bam
def compress_sam_file(input_file,
output_file):
ii = open(input_file)
oo = open(output_file, "w")
#
# STAGE 3 bam->statistics
#
@transform(compress_sam_file, # Input = previous stage
suffix(".bam"), # suffix = .bam
".statistics", # Output suffix = .statistics
"use_linear_model") # Extra statistics parameter
def summarise_bam_file(input_file,
output_file,
extra_stats_parameter):
"""
Sketch of real analysis function
"""
ii = open(input_file)
oo = open(output_file, "w")
pipeline_run()
************************************
Resulting Output
************************************
::
>>> pipeline_run()
Job = [[a.1.fastq, a.2.fastq] -> a.sam] completed
Job = [[b.1.fastq, b.2.fastq] -> b.sam] completed
Job = [[c.1.fastq, c.2.fastq] -> c.sam] completed
Completed Task = map_dna_sequence
Job = [a.sam -> a.bam] completed
Job = [b.sam -> b.bam] completed
Job = [c.sam -> c.bam] completed
Completed Task = compress_sam_file
Job = [a.bam -> a.statistics, use_linear_model] completed
Job = [b.bam -> b.statistics, use_linear_model] completed
Job = [c.bam -> c.statistics, use_linear_model] completed
Completed Task = summarise_bam_file
|
