diff --git a/workflow/main.nf b/workflow/main.nf
index 29391c42541e2b36e2015359ba237da6859cfce6..f96063110812e0b17032310cbf6a8d4b7de95b2e 100644
--- a/workflow/main.nf
+++ b/workflow/main.nf
@@ -354,7 +354,7 @@ process callPeaksMACS {
peaksDesign = experimentPeaks
.map{ sampleId, peak, fcSignal, pvalueSignal, experimentId, biosample, factor, treatment, replicate, controlId ->
"$sampleId\t$peak\t$fcSignal\t$pvalueSignal\t$experimentId\t$biosample\t$factor\t$treatment\t$replicate\t$controlId\n"}
- .collectFile(name:'design_peak.tsv', seed:"sample_id\tpeak\txcor\tfcSignal\tpvalueSignal\texperiment_id\tbiosample\tfactor\ttreatment\treplicate\tcontrol_id\n", storeDir:"$baseDir/output/design")
+ .collectFile(name:'design_peak.tsv', seed:"sample_id\tpeaks\tfc_signal\tpvalue_signal\texperiment_id\tbiosample\tfactor\ttreatment\treplicate\tcontrol_id\n", storeDir:"$baseDir/output/design")
// Calculate Consensus Peaks
process consensusPeaks {
diff --git a/workflow/scripts/overlap_peaks.py b/workflow/scripts/overlap_peaks.py
index 6ea2f0e3b848f20313c58688af3cd160366a9b28..7a27e948d558ae4e8c0ef9abddea920050fd5d42 100644
--- a/workflow/scripts/overlap_peaks.py
+++ b/workflow/scripts/overlap_peaks.py
@@ -2,9 +2,12 @@
'''Generate naive overlap peak files and design file for downstream processing.'''
+import os
import argparse
import logging
+import shutil
import pandas as pd
+import utils
EPILOG = '''
For more details:
@@ -72,7 +75,7 @@ def update_design(design):
logger.info("Adding peaks column.")
- design = design.assign(peak = "", peak_caller = 'bed')
+ design = design.assign(peak='', peak_caller='bed')
return design
@@ -84,17 +87,17 @@ def overlap(experiment, design):
# Output File names
peak_type = 'narrowPeak'
- overlapping_peaks_fn = '%s.replicated.%s' %(experiment, peak_type)
- rejected_peaks_fn = '%s.rejected.%s' %(experiment, peak_type)
+ overlapping_peaks_fn = '%s.replicated.%s' % (experiment, peak_type)
+ rejected_peaks_fn = '%s.rejected.%s' % (experiment, peak_type)
# Intermediate File names
- overlap_tr_fn = 'replicated_tr.%s' %(peak_type)
- overlap_pr_fn = 'replicated_pr.%s' %(peak_type)
+ overlap_tr_fn = 'replicated_tr.%s' % (peak_type)
+ overlap_pr_fn = 'replicated_pr.%s' % (peak_type)
# Assign Pooled and Psuedoreplicate peaks
- pool_peaks = design.loc[design.replicate == 'pooled', 'peak']
- pr1_peaks = design.loc[design.replicate == '1_pr', 'peak']
- pr2_peaks = design.loc[design.replicate == '2_pr', 'peak']
+ pool_peaks = design.loc[design.replicate == 'pooled', 'peaks'].values[0]
+ pr1_peaks = design.loc[design.replicate == '1_pr', 'peaks'].values[0]
+ pr2_peaks = design.loc[design.replicate == '2_pr', 'peaks'].values[0]
# Remove non true replicate rows
not_replicates = ['1_pr', '2_pr', 'pooled']
@@ -102,14 +105,14 @@ def overlap(experiment, design):
true_rep_peaks = design_true_reps.peaks.unique()
# Find overlaps
- awk_command = r"""awk 'BEGIN{FS="\t";OFS="\t"}{s1=$3-$2; s2=$13-$12; if (($21/s1 >= 0.5) || ($21/s2 >= 0.5)) {print $0}}'"""
- cut_command = 'cut -f 1-10'
+ awk_command = r"""awk 'BEGIN{FS="\t";OFS="\t"}{s1=$3-$2; s2=$13-$12; if (($21/s1 >= 0.5) || ($21/s2 >= 0.5)) {print $0}}'"""
+ cut_command = 'cut -f 1-10'
# Find pooled peaks that overlap Rep1 and Rep2
# where overlap is defined as the fractional overlap
# with any one of the overlapping peak pairs >= 0.5
- steps_true = ['intersectBed -wo -a %s -b %s' %(pool_peaks, true_rep_peaks[0]),
+ steps_true = ['intersectBed -wo -a %s -b %s' % (pool_peaks, true_rep_peaks[0]),
awk_command,
cut_command,
'sort -u']
@@ -119,44 +122,45 @@ def overlap(experiment, design):
if len(true_rep_peaks) > 1:
for true_peak in true_rep_peaks[1:]:
- steps_true.extend(['intersectBed -wo -a stdin -b %s' %(true_peak),
- awk_command,
- cut_command,
- 'sort -u'])
+ steps_true.extend(['intersectBed -wo -a stdin -b %s' % (true_peak),
+ awk_command,
+ cut_command,
+ 'sort -u'])
out, err = utils.run_pipe(steps_true, outfile=overlap_tr_fn)
- print "%d peaks overlap with both true replicates" %(utils.count_lines(overlap_tr_fn))
+ print("%d peaks overlap with both true replicates" %
+ (utils.count_lines(overlap_tr_fn)))
# Find pooled peaks that overlap PseudoRep1 and PseudoRep2
# where overlap is defined as the fractional overlap
# with any one of the overlapping peak pairs >= 0.5
- steps_pseudo = ['intersectBed -wo -a %s -b %s' %(pool_peaks, pr1_peaks),
+ steps_pseudo = ['intersectBed -wo -a %s -b %s' % (pool_peaks, pr1_peaks),
awk_command,
cut_command,
'sort -u',
- 'intersectBed -wo -a stdin -b %s' %(pr2_peaks),
+ 'intersectBed -wo -a stdin -b %s' % (pr2_peaks),
awk_command,
cut_command,
'sort -u']
out, err = utils.run_pipe(steps_pseudo, outfile=overlap_pr_fn)
- print "%d peaks overlap with both pooled pseudoreplicates" \
- % (utils.count_lines(overlap_pr_fn))
-
- # Make union of peak lists
- out, err = utils.run_pipe([
- 'cat %s %s' %(overlap_tr_fn, overlap_pr_fn),
- 'sort -u'
- ], overlapping_peaks_fn)
- print "%d peaks overlap with true replicates or with pooled pseudorepliates" \
- % (utils.count_lines(overlapping_peaks_fn))
-
- # Make rejected peak list
- out, err = utils.run_pipe([
- 'intersectBed -wa -v -a %s -b %s' %(pool_peaks, overlapping_peaks_fn)
- ], rejected_peaks_fn)
- print "%d peaks were rejected" %(utils.count_lines(rejected_peaks_fn))
+ print("%d peaks overlap with both pooled pseudoreplicates"
+ % (utils.count_lines(overlap_pr_fn)))
+
+ # Make union of peak lists
+ out, err = utils.run_pipe([
+ 'cat %s %s' % (overlap_tr_fn, overlap_pr_fn),
+ 'sort -u'
+ ], overlapping_peaks_fn)
+ print("%d peaks overlap with true replicates or with pooled pseudorepliates"
+ % (utils.count_lines(overlapping_peaks_fn)))
+
+ # Make rejected peak list
+ out, err = utils.run_pipe([
+ 'intersectBed -wa -v -a %s -b %s' % (pool_peaks, overlapping_peaks_fn)
+ ], rejected_peaks_fn)
+ print("%d peaks were rejected" % (utils.count_lines(rejected_peaks_fn)))
# Remove temporary files
os.remove(overlap_tr_fn)
@@ -168,14 +172,14 @@ def overlap(experiment, design):
def main():
args = get_args()
design = args.design
- files = args.design
+ files = args.files
# Create a file handler
handler = logging.FileHandler('consensus_peaks.log')
logger.addHandler(handler)
# Read files as dataframes
- design_peaks_df = pd.read_csv(design, sep='\t')
+ design_peaks_df = pd.read_csv('../design/design_peak.tsv', sep='\t')
design_files_df = pd.read_csv(files, sep='\t')
# Make a design file for
@@ -184,7 +188,7 @@ def main():
# Find consenus overlap peaks for each experiment
for experiment, df_experiment in design_peaks_df.groupby('experiment_id'):
replicated_peak = overlap(experiment, df_experiment)
- design_diff.loc[design_diff.experiment_id == experiment, "peaks"] = replicated_peak
+ design_diff.loc[design_diff.experiment_id == experiment, "peak"] = replicated_peak
# Write out file
design_diff.columns = ['SampleID',