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#!/usr/bin/env python
"""
intermediate_example.py
This script takes N pairs of input file pairs
(with the suffices .gene and .gwas)
and runs them against M sets of simulation data
(with the suffix .simulation)
A summary per input file pair is then produced
In pseudo-code:
STEP_1:
for n_file in NNN_pairs_of_input_files:
for m_file in MMM_simulation_data:
[n_file.gene,
n_file.gwas,
m_file.simulation] -> n_file.m_file.simulation_res
STEP_2:
for n_file in NNN_pairs_of_input_files:
n_file.*.simulation_res -> n_file.mean
"""
import os, sys
exe_path = os.path.split(os.path.abspath(sys.argv[0]))[0]
from ruffus import *
from time import sleep
import random
from itertools import izip
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# options
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from optparse import OptionParser
parser = OptionParser(version="%prog 1.0")
parser.add_option("-t", "--target_tasks", dest="target_tasks",
action="append",
default = ["statistical_summary"],
metavar="JOBNAME",
type="string",
help="Target task(s) of pipeline.")
parser.add_option("-f", "--forced_tasks", dest="forced_tasks",
action="append",
default = list(),
metavar="JOBNAME",
type="string",
help="Pipeline task(s) which will be included even if they are up to date.")
parser.add_option("-j", "--jobs", dest="jobs",
default=5,
metavar="jobs",
type="int",
help="Specifies the number of jobs (commands) to run simultaneously.")
parser.add_option("-g", "--gene_data_dir", dest="gene_data_dir",
default="%s/data_for_intermediate_example/genes" % exe_path,
metavar="PATH",
type="string",
help="Directory with gene data [*.genes / *.gwas].")
parser.add_option("-s", "--simulation_data_dir", dest="simulation_data_dir",
default="%s/data_for_intermediate_example/simulation" % exe_path,
metavar="PATH",
type="string",
help="Directory with simulation data [*.simulation].")
parser.add_option("-w", "--working_dir", dest="working_dir",
default="/working_dir",
metavar="PATH",
type="string",
help="Working directory.")
parser.add_option("-v", "--verbose", dest = "verbose",
action="store_true", default=False,
help="Do not echo to shell but only print to log.")
parser.add_option("-D", "--dependency", dest="dependency_file",
metavar="FILE",
type="string",
help="Print a dependency graph of the pipeline that would be executed "
"to FILE, but do not execute it.")
parser.add_option("-F", "--dependency_graph_format", dest="dependency_graph_format",
metavar="FORMAT",
type="string",
default = 'svg',
help="format of dependency graph file. Can be 'ps' (PostScript), "+
"'svg' 'svgz' (Structured Vector Graphics), " +
"'png' 'gif' (bitmap graphics) etc ")
parser.add_option("-n", "--just_print", dest="just_print",
action="store_true", default=False,
help="Print a description of the jobs that would be executed, "
"but do not execute them.")
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# imports
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import StringIO
import re
import operator
import sys
from collections import defaultdict
import glob
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# Functions
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#_________________________________________________________________________________________
#
# get gene gwas file pairs
#
#_________________________________________________________________________________________
def get_gene_gwas_file_pairs( ):
"""
Helper function to get all *.gene, *.gwas from the direction specified
in --gene_data_dir
Returns
file pairs with both .gene and .gwas extensions,
corresponding roots (no extension) of each file
"""
gene_files = glob.glob(os.path.join(options.gene_data_dir, "*.gene"))
gwas_files = glob.glob(os.path.join(options.gene_data_dir, "*.gwas"))
common_roots = set(map(lambda x: os.path.splitext(os.path.split(x)[1])[0], gene_files))
common_roots &=set(map(lambda x: os.path.splitext(os.path.split(x)[1])[0], gwas_files))
common_roots = list(common_roots)
p = os.path; g_dir = options.gene_data_dir
file_pairs = [[p.join(g_dir, x + ".gene"), p.join(g_dir, x + ".gwas")] for x in common_roots]
return file_pairs, common_roots
#_________________________________________________________________________________________
#
# get simulation files
#
#_________________________________________________________________________________________
def get_simulation_files( ):
"""
Helper function to get all *.simulation from the direction specified
in --simulation_data_dir
Returns
file with .simulation extensions,
corresponding roots (no extension) of each file
"""
simulation_files = glob.glob(os.path.join(options.simulation_data_dir, "*.simulation"))
simulation_roots =map(lambda x: os.path.splitext(os.path.split(x)[1])[0], simulation_files)
return simulation_files, simulation_roots
#88888888888888888888888888888888888888888888888888888888888888888888888888888888888888888
# Main logic
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# get help string
f =StringIO.StringIO()
parser.print_help(f)
helpstr = f.getvalue()
(options, remaining_args) = parser.parse_args()
working_dir = options.working_dir
#_________________________________________________________________________________________
#
# Step 1:
#
# for n_file in NNN_pairs_of_input_files:
# for m_file in MMM_simulation_data:
#
# [n_file.gene,
# n_file.gwas,
# m_file.simulation] -> working_dir/n_file.m_file.simulation_res
#
#_________________________________________________________________________________________
def generate_simulation_params ():
"""
Custom function to generate
file names for gene/gwas simulation study
"""
simulation_files, simulation_file_roots = get_simulation_files()
gene_gwas_file_pairs, gene_gwas_file_roots = get_gene_gwas_file_pairs()
for sim_file, sim_file_root in izip(simulation_files, simulation_file_roots):
for (gene, gwas), gene_file_root in izip(gene_gwas_file_pairs, gene_gwas_file_roots):
result_file = "%s.%s.simulation_res" % (gene_file_root, sim_file_root)
result_file_path = os.path.join(working_dir, "simulation_results", result_file)
yield [gene, gwas, sim_file], result_file_path, gene_file_root, sim_file_root, result_file
#
# mkdir: makes sure output directories exist before task
#
@follows(mkdir(options.working_dir, os.path.join(working_dir, "simulation_results")))
@files(generate_simulation_params)
def gwas_simulation(input_files, result_file_path, gene_file_root, sim_file_root, result_file):
"""
Dummy calculation of gene gwas vs simulation data
Normally runs in parallel on a computational cluster
"""
(gene_file,
gwas_file,
simulation_data_file) = input_files
simulation_res_file = open(result_file_path, "w")
simulation_res_file.write("%s + %s -> %s\n" % (gene_file_root, sim_file_root, result_file))
#_________________________________________________________________________________________
#
# Step 2:
#
# Statistical summary per gene/gwas file pair
#
# for n_file in NNN_pairs_of_input_files:
# working_dir/simulation_results/n.*.simulation_res
# -> working_dir/n.mean
#
#_________________________________________________________________________________________
def generate_statistical_summary_params():
"""
Custom function to summarising simulation results files per gene / gwas file pair
"""
gene_gwas_file_pairs, gene_gwas_file_roots = get_gene_gwas_file_pairs()
for (gene, gwas), gene_file_root in izip(gene_gwas_file_pairs, gene_gwas_file_roots):
result_glob_spec = "%s.*.simulation_res" % (gene_file_root)
result_files = glob.glob(os.path.join(working_dir, "simulation_results", result_glob_spec))
summary_file = os.path.join(working_dir, gene_file_root + ".mean")
yield result_files, summary_file
@follows(gwas_simulation)
@files(generate_statistical_summary_params)
@posttask(lambda : sys.stdout.write("\nAll finished: hooray!!!\n"))
def statistical_summary (result_files, summary_file):
"""
Simulate statistical summary
"""
summary_file = open(summary_file, "w")
for f in result_files:
summary_file.write(open(f).read())
sleep(1)
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#
# print pipeline or run pipeline
#
if options.just_print:
pipeline_printout(sys.stdout, options.target_tasks, options.forced_tasks, long_winded=True)
elif options.dependency_file:
graph_printout ( open(options.dependency_file, "w"),
options.dependency_graph_format,
options.target_tasks,
options.forced_tasks)
else:
pipeline_run(options.target_tasks, options.forced_tasks, multiprocess = options.jobs)
|
