diff --git a/workflow/conf/biohpc.config b/workflow/conf/biohpc.config
index da1209423786bce5c7cb745e043a97136226bcd0..c43f8e0d85733142342c9c6ca44886f6d448f6ad 100644
--- a/workflow/conf/biohpc.config
+++ b/workflow/conf/biohpc.config
@@ -35,6 +35,11 @@ process {
module = ['python/3.6.1-2-anaconda']
executor = 'local'
}
+ $poolAndPsuedoReads {
+ module = ['python/3.6.1-2-anaconda']
+ executor = 'local'
+ cpus = 32
+ }
}
params {
diff --git a/workflow/main.nf b/workflow/main.nf
index e04236a1f4913c40aed881805666ba32b8d61e41..fa205e6a4cf4bd967a03541a3ee345ccfb7461b5 100644
--- a/workflow/main.nf
+++ b/workflow/main.nf
@@ -10,6 +10,7 @@ params.designFile = "$baseDir/../test_data/design_ENCSR238SGC_SE.txt"
params.genome = 'GRCm38'
params.genomes = []
params.bwaIndex = params.genome ? params.genomes[ params.genome ].bwa ?: false : false
+params.cutoffRatio = 1.2
// Check inputs
if( params.bwaIndex ){
@@ -30,6 +31,7 @@ readsList = Channel
// Define regular variables
pairedEnd = params.pairedEnd
designFile = params.designFile
+cutoffRatio = params.cutoffRatio
process checkDesignFile {
@@ -276,3 +278,32 @@ process defineExpDesignFiles {
"""
}
+
+
+// Make Experiment design files to be read in for downstream analysis
+process poolAndPsuedoReads {
+
+ publishDir "$baseDir/output/design", mode: 'copy'
+
+ input:
+
+ file experimentObjs
+
+ output:
+
+ file '*.tsv' into experimentPoolObjs
+
+ script:
+
+ if (pairedEnd) {
+ """
+ python3 $baseDir/scripts/pool_and_psuedoreplicate.py -t $experimentObjs -p -c cutoffRatio
+ """
+ }
+ else {
+ """
+ python3 $baseDir/scripts/pool_and_psuedoreplicate.py -t $experimentObjs -c cutoffRatio
+ """
+ }
+
+}
diff --git a/workflow/scripts/pool_and_psuedoreplicate.py b/workflow/scripts/pool_and_psuedoreplicate.py
new file mode 100644
index 0000000000000000000000000000000000000000..cb604ace3fc0e5da362bec334fbdf39a14379074
--- /dev/null
+++ b/workflow/scripts/pool_and_psuedoreplicate.py
@@ -0,0 +1,277 @@
+#!/usr/bin/env python3
+
+'''Generate pooled and pseudoreplicate from data.'''
+
+import argparse
+import utils
+import logging
+import pandas as pd
+import numpy as np
+import os
+
+EPILOG = '''
+For more details:
+ %(prog)s --help
+'''
+
+# SETTINGS
+
+logger = logging.getLogger(__name__)
+logger.addHandler(logging.NullHandler())
+logger.propagate = False
+logger.setLevel(logging.INFO)
+
+
+def get_args():
+ '''Define arguments.'''
+
+ parser = argparse.ArgumentParser(
+ description=__doc__, epilog=EPILOG,
+ formatter_class=argparse.RawDescriptionHelpFormatter)
+
+ parser.add_argument('-d', '--design',
+ help="The design file to make experiemnts (tsv format).",
+ required=True)
+
+ parser.add_argument('-p', '--paired',
+ help="True/False if paired-end or single end.",
+ default=False,
+ action='store_true')
+
+ parser.add_argument('-c', '--cutoff',
+ help="Cutoff ratio used for choosing controls.",
+ default=1.2)
+
+ args = parser.parse_args()
+ return args
+
+
+def check_replicates(design):
+ '''Check the number of replicates for the experiment.'''
+
+ no_rep = design.shape[0]
+
+ return no_rep
+
+
+def check_controls(design):
+ '''Check the number of controls for the experiment.'''
+
+ no_controls = len(design.control_tag_align.unique())
+
+ return no_controls
+
+
+def get_read_count_ratio(design):
+ '''Get the ratio of read counts for unique controls.'''
+
+ controls = design.control_tag_align.unique()
+ control_dict = {}
+ for con in controls:
+ no_reads = utils.count_lines(con)
+ control_dict[con] = no_reads
+
+ control_matrix = {c: control_dict for c in controls}
+ control_df = pd.DataFrame.from_dict(control_matrix)
+
+ control_ratio = control_df.divide(list(control_dict.values()), axis=0)
+ return control_ratio
+
+
+def pool(tag_files, outfile, paired):
+ '''Pool files together.'''
+
+ if paired:
+ file_extension = 'bedpe.gz'
+ else:
+ file_extension = 'bedse.gz'
+
+ pooled_filename = outfile + file_extension
+
+ # Merge files
+ out, err = utils.run_pipe([
+ 'gzip -dc %s' % (' '.join(tag_files)),
+ 'gzip -cn'],
+ outfile=pooled_filename)
+
+ return pooled_filename
+
+
+def self_psuedoreplication(tag_file, prefix, reps, paired):
+ '''Make n number of self-psuedoreplicates equivlent to reps.'''
+
+ # Get total number of reads
+ no_lines = utils.count_lines(tag_file)
+
+ # Number of lines to split into
+ lines_per_rep = round(no_lines/reps)
+
+ # Make an array of number of psuedoreplicatesfile names
+ pseudoreplicate_dict = {r: prefix + '.pr' + str(r) + '.bedse.tagAlign.gz'
+ for r in list(range(0, reps))}
+
+ # Shuffle and split file into equal parts
+ # by using the input to seed shuf we ensure multiple runs with the same
+ # input will produce the same output
+ # Produces two files named splits_prefix0n, n=1,2
+
+ splits_prefix = 'temp_split'
+
+ out, err = utils.run_pipe([
+ 'gzip -dc %s' % (tag_file),
+ 'shuf --random-source=%s' % (tag_file),
+ 'split -d -l %d - %s' % (lines_per_rep, splits_prefix)])
+
+ # Convert read pairs to reads into standard tagAlign file
+
+ for i, index in enumerate(list(range(0, reps))):
+ steps = ['cat %s' % (splits_prefix + index)]
+ if paired:
+ steps.extend([r"""awk 'BEGIN{OFS="\t"}{printf "%s\t%s\t%s\tN\t1000\t%s\n%s\t%s\t%s\tN\t1000\t%s\n",$1,$2,$3,$9,$4,$5,$6,$10}'"""])
+ steps.extend(['gzip -cn'])
+ out, err = utils.run_pipe(steps, outfile=pseudoreplicate_dict[i])
+ os.remove(splits_prefix + index)
+
+ return pseudoreplicate_dict
+
+
+def main():
+ args = get_args()
+ paired = args.paired
+ design = args.design
+ cutoff_ratio = args.cutoff_ratio
+
+ # Create a file handler
+ handler = logging.FileHandler('experiment_generation.log')
+ logger.addHandler(handler)
+
+ # Read files as dataframes
+ design_df = pd.read_csv(design, sep='\t')
+
+ # Get current directory to build paths
+ cwd = os.getwd()
+
+ # Check Number of replicates and replicates
+ no_reps = check_replicates(design_df)
+ no_unique_controls = check_controls(design_df)
+
+ if no_reps == 1:
+ logger.info("No other replicate specified "
+ "so processing as an unreplicated experiment.")
+ replicated = False
+
+ else:
+ logger.info("Multiple replicates specified"
+ "so processing as a replicated experiment.")
+ replicated = True
+
+ if no_unique_controls == 1 and replicated:
+ logger.info("Only a single control was specified"
+ "so using same control for replicates, pool and psuedoreplicates.")
+ single_control = True
+ else:
+ logger.info("Will merge only unique controls for pooled")
+ single_control = False
+
+ # Pool the controls for checking
+ if not single_control:
+ control_df = get_read_count_ratio(design_df)
+ control_files = design_df.control_tag_align.unique()
+ pool_control = pool(control_files, "pool_control", paired)
+ else:
+ pool_control = design_df.control_tag_align.unique()[0]
+
+ # Psuedoreplicate and update design accordingly
+ if not replicated:
+
+ # Duplicate rows and update for pool and psuedoreplicates
+ experiment_id = design_df.at[0, 'experiment_id']
+ replicate = design_df.at[0, 'replicate']
+ design_new_df = design_df.loc[np.repeat(design_df.index, 4)].reset_index()
+ design_new_df.set_value(1, 'sample_id', experiment_id + '_pr')
+ design_new_df.set_value(1, 'replicate', '1_pr')
+ design_new_df.set_value(2, 'sample_id', experiment_id + '_pr')
+ design_new_df.set_value(2, 'replicate', '2_pr')
+ design_new_df.set_value(3, 'sample_id', experiment_id + '_pooled')
+ design_new_df.set_value(3, 'sample_id', experiment_id + '_pooled')
+
+ # Make 2 self psuedoreplicates
+ self_pseudoreplicates_dict = {}
+ for rep, tag_file in zip(design_df['replicate'], design_df['tag_align']):
+ replicate_prefix = experiment_id + '_' + rep
+ self_pseudoreplicates_dict = \
+ self_psuedoreplication(tag_file, replicate_prefix, 2, paired)
+
+ # Update design to include new self pseudo replicates
+ for rep, pseudorep_file in self_pseudoreplicates_dict.items():
+ path_to_file = cwd + '/' + pseudorep_file
+ replicate = rep + 1
+ design_new_df.loc[replicate, 'tag_align'] = path_to_file
+
+ else:
+ # Make pool of replicates
+ replicate_files = design_df.tag_align.unique()
+ experiment_id = design_df.at[0, 'experiment_id']
+ pool_experiment = pool(replicate_files, experiment_id + "_pooled", paired)
+
+ # Make self psuedoreplicates equivalent to number of replicates
+ pseudoreplicates_dict = {}
+ for rep, tag_file in zip(design_df['replicate'], design_df['tag_align']):
+ replicate_prefix = experiment_id + '_' + rep
+ pr_dict = self_psuedoreplication(tag_file, replicate_prefix, no_reps, paired)
+ pseudoreplicates_dict[rep] = pr_dict
+
+ # Merge self psuedoreplication for each true replicate
+ pseudoreplicates_df = pd.DataFrame.from_dict(pseudoreplicates_dict)
+ pool_pseudoreplicates_dict = {}
+ for index, row in pseudoreplicates_df.iterrows():
+ replicate_id = index + 1
+ pr_filename = experiment_id + ".pr" + replicate_id + '.bedse.gz'
+ pool_replicate = pool(row, pr_filename, False)
+ pool_pseudoreplicates_dict[replicate_id] = pool_replicate
+
+ design_new_df = design_df
+ # Check controls against cutoff_ratio
+ # if so replace with pool_control
+ path_to_pool_control = cwd + '/' + pool_control
+ if control_df[control_df > cutoff_ratio].values.any():
+ logger.info("Number of reads in controls differ by " +
+ " > factor of %f. Using pooled controls." % (cutoff_ratio))
+ design_new_df['control_tag_align'] = path_to_pool_control
+ else:
+ for index, row in design_new_df.iterrows():
+ exp_no_reads = utils.count_lines(row['tag_align'])
+ con_no_reads = utils.count_lines(row['control_tag_align'])
+ if con_no_reads < exp_no_reads:
+ logger.info("Fewer reads in control than experiment." +
+ "Using pooled controls for replicate %s."
+ % row['replicate'])
+ design_new_df.loc[index, 'control_tag_align'] = \
+ path_to_pool_control
+
+ # Add in pseudo replicates
+ tmp_metadata = design_new_df.loc[0].copy()
+ tmp_metadata['control_tag_align'] = path_to_pool_control
+ for rep, pseudorep_file in pool_pseudoreplicates_dict.items():
+ tmp_metadata['sample_id'] = experiment_id + '_pr' + rep
+ tmp_metadata['replicate'] = rep + '_pr'
+ tmp_metadata['xcor'] = 'Calculate'
+ path_to_file = cwd + '/' + pseudorep_file
+ tmp_metadata['tag_align'] = path_to_file
+ design_new_df = design_new_df.append(tmp_metadata)
+
+ # Add in pool experiment
+ tmp_metadata['sample_id'] = experiment_id + '_pooled'
+ tmp_metadata['replicate'] = 'pooled'
+ tmp_metadata['xcor'] = 'Calculate'
+ path_to_file = cwd + '/' + pool_experiment
+ tmp_metadata['tag_align'] = path_to_file
+ design_new_df = design_new_df.append(tmp_metadata)
+
+ # Write out new dataframe
+ design_new_df.to_csv(experiment_id + '_ppr.tsv',
+ header=True, sep='\t', index=False)
+
+
+if __name__ == '__main__':
+ main()
diff --git a/workflow/scripts/utils.py b/workflow/scripts/utils.py
index 5162646d56b5281a88cd7195dba784865cffe7f8..11c4170a00153f4c2b20dce03706e529231cb294 100644
--- a/workflow/scripts/utils.py
+++ b/workflow/scripts/utils.py
@@ -53,3 +53,22 @@ def strip_extensions(filename, extensions):
basename = basename.rpartition(extension)[0] or basename
return basename
+
+
+def count_lines(filename):
+ from magic import from_file
+ compressed_mimetypes = [
+ "application/x-compress",
+ "application/x-bzip2",
+ "application/x-gzip"
+ ]
+ mime_type = from_file(fname, mime=True)
+ if mime_type in compressed_mimetypes:
+ catcommand = 'gzip -dc'
+ else:
+ catcommand = 'cat'
+ out, err = run_pipe([
+ '%s %s' % (catcommand, fname),
+ 'wc -l'
+ ])
+ return int(out)
diff --git a/workflow/tests/test_experiment_design.py b/workflow/tests/test_experiment_design.py
index 508dbb12f7588a41622aff7eca1d58a4bc31a1ac..bfbd3c01148fb2e31e40f0ddcf25a4f208b92caa 100644
--- a/workflow/tests/test_experiment_design.py
+++ b/workflow/tests/test_experiment_design.py
@@ -30,7 +30,10 @@ def test_check_update_controls_tag(design_tag):
def test_experiment_design_single_end():
- assert os.path.exists(os.path.join(test_output_path, 'ENCSR238SGC.tsv'))
+ design_file = os.path.join(test_output_path, 'ENCSR238SGC.tsv')
+ assert os.path.exists(design_file)
+ design_df = pd.read_csv(design_file, sep="\t")
+ assert design_df.shape[0] == 2
def test_experiment_design_paired_end():
diff --git a/workflow/tests/test_pool_and_psuedoreplicate.py b/workflow/tests/test_pool_and_psuedoreplicate.py
new file mode 100644
index 0000000000000000000000000000000000000000..fa09952ec15d9d33ef5a53d2c3d027ec4c885fea
--- /dev/null
+++ b/workflow/tests/test_pool_and_psuedoreplicate.py
@@ -0,0 +1,67 @@
+#!/usr/bin/env python3
+
+import pytest
+import pandas as pd
+from io import StringIO
+import pool_and_psuedoreplicate
+
+test_output_path = os.path.dirname(os.path.abspath(__file__)) + \
+ '/../output/design/'
+
+DESIGN_STRING = """sample_id\ttag_align\txcor\tbiosample\tfactor\ttreatment\treplicate\tcontrol_tag_align
+A_1\tA_1.bedse.gz\tA_1.cc.qc\tLiver\tH3K27ac\tNone\t1\tB_1.bedse.gz
+A_2\tA_2.bedse.gz\tA_2.cc.qc\tLiver\tH3K27ac\tNone\t2\tB_2.bedse.gz
+"""
+
+
+@pytest.fixture
+def design_experiment():
+ design_file = StringIO(DESIGN_STRING)
+ design_df = pd.read_csv(design_file, sep="\t")
+ return design_df
+
+
+@pytest.fixture
+def design_experiment_2(design_experiment):
+ # Drop Replicate A_2
+ design_df = design_experiment.drop(design_experiment.index[1])
+ return design_df
+
+
+@pytest.fixture
+def design_experiment_3(design_experiment):
+ # Update second control to be same as first
+ design_experiment.loc[1, 'control_tag_align'] = 'B_1.bedse.gz'
+ return design_experiment
+
+
+def test_check_replicates(design_experiment):
+ no_reps = pool_and_psuedoreplicate.check_replicates(design_experiment)
+ assert no_reps == 2
+
+
+def test_check_replicates_single(design_experiment_2):
+ no_reps = pool_and_psuedoreplicate.check_replicates(design_experiment_2)
+ assert no_reps == 1
+
+
+def test_check_controls(design_experiment):
+ no_controls = pool_and_psuedoreplicate.check_controls(design_experiment)
+ assert no_controls == 2
+
+
+def test_check_controls_single(design_experiment_3):
+ no_controls = pool_and_psuedoreplicate.check_controls(design_experiment_3)
+ assert no_controls == 1
+
+
+def test_pool_and_psuedoreplicate_single_end():
+ design_file = os.path.join(test_output_path, 'ENCSR238SGC_ppr.tsv')
+ assert os.path.exists(design_file)
+ design_df = pd.read_csv(design_file, sep="\t")
+ assert design_df.shape[0] == 5
+
+
+def test_experiment_design_paired_end():
+ # Do the same thing for paired end data
+ pass