diff --git a/workflow/main.nf b/workflow/main.nf index db15eb3f581596f427cbacd634d05257a9e93255..75a25de909ce153c559bc4f39e626b097af48f36 100644 --- a/workflow/main.nf +++ b/workflow/main.nf @@ -371,10 +371,9 @@ process consensusPeaks { file '*.replicated.*' into consensusPeaks file '*.rejected.*' into rejectedPeaks - file("design_diffPeaks.csv") into designDiffPeaks - file("design_annotatePeaks.tsv") into designAnnotatePeaks - file("design_annotatePeaks.tsv") into designMotifSearch - file("unqiue_experiments.csv") into uniqueExperiments + file 'design_diffPeaks.csv' into designDiffPeaks + file 'design_annotatePeaks.tsv' into designAnnotatePeaks, designMotifSearch + file 'unique_experiments.csv' into uniqueExperiments script: @@ -386,8 +385,7 @@ process consensusPeaks { // Define channel to find number of unique experiments noUniqueExperiments = Channel - .from(uniqueExperiments) - .readLines() + .from(uniqueExperiments.readLines()) .size() // Annotate Peaks @@ -423,10 +421,9 @@ process diffPeaks { output: - file "design_diffpeak_annotatePeaks.tsv" into diffPeaksDesignAnnotatePeaks - file "design_diffpeak_annotatePeaks.tsv" into diffPeaksDesignMeme - file "*_diffbind.bed" into diffPeaks - file "*_diffbind.csv" into diffPeaksCounts + file 'design_diffpeak_annotatePeaks.tsv' into diffPeaksDesignAnnotatePeaks, diffPeaksDesignMeme + file '*_diffbind.bed' into diffPeaks + file '*_diffbind.csv' into diffPeaksCounts file '*.pdf' into diffPeaksStats file 'normcount_peaksets.txt' into normCountPeaks diff --git a/workflow/scripts/overlap_peaks.py b/workflow/scripts/overlap_peaks.py index bb7b53dccf03512a32d9b178f4a91fa04c6dbcc7..ad0d57ed80a5b1669350e2cae0cd775ab7be61ad 100644 --- a/workflow/scripts/overlap_peaks.py +++ b/workflow/scripts/overlap_peaks.py @@ -213,7 +213,7 @@ def main(): # Write the unique conditions unique_experiments = pd.Series(design_diff['Condition'].unique) - unique_experiments.to_csv('unqiue_experiments.csv') + unique_experiments.to_csv('unique_experiments.csv') if __name__ == '__main__':