comments

Snakefile

@@ -13,28 +13,34 @@ import argparse, subprocess
 container: "docker://gepdocker/gep_dockerimage:latest"
 configfile: "configuration/config.yaml"
 
+### LOAD IN RESOURCES CONFIG  ###
 with open(config['resources'], 'r') as f:
 	resource = yaml.safe_load(f)
 
+### GET BASENAME FOR READS WILDCARDS ###
 def getBasename4Reads(path):
 	base=os.path.basename(path)
 	return os.path.splitext(base)[0]
 
-
+### CHECK IF INPUT IS GZIPPED ###
 def gzipped_or_not(path):
 	trueORfalse=path.endswith('.gz')
 	return trueORfalse
 
+### CHECK IF HIC AND/OR ALT_ASM FILES ARE GIVEN, OR VALUE IS NONE  ###
 def FILE_present_or_not(path):
 	if path == 'None':
 		return False
 	return True
 
+
+### CHECK IF GENOME_SIZE IS PROVIDED, OR VALUE IS AUTO ###
 def genomeSize_auto_or_not(given_size):
 	if given_size == 'auto':
 		return 0
 	return given_size
 
+
 def addUniqueLibraryID(library):
 	string2Add=library + "_1"
 
@@ -51,18 +57,10 @@ if set(['sample', 'Library_R1', 'Library_R2', 'meryl_kmer_size', 'trim10X', 'tri
 	samples['readCounter'] = samples.groupby(['sample']).cumcount()+1
 	samples['readCounter'] = samples['readCounter'].astype(str)
 	samples['readCounter'] = samples['sample'] + "_LibraryPair" + samples['readCounter']
-	# samples=samples.reset_index()
-	# trim10x_table = samples[samples['trim10X'] == "True"]
-	# trim10x_table=trim10x_table.set_index(['sample','readCounter'])
-	# notrim10xwithAdapt= samples[(samples['trim10X'] == "False") & (samples['trimAdapters'] == "True") ]
-	# notrim10xwithAdapt=notrim10xwithAdapt.set_index(['sample','readCounter'])
-	# notrim10xorAdapt= samples[(samples['trim10X'] == "False") & (samples['trimAdapters'] == "False") ]
-	# notrim10xorAdapt=notrim10xorAdapt.set_index(['sample','readCounter'])
-	# d10xtrim = {}
+
 	samples['10xtrimorNot'] = np.where(samples['trim10X'] == "True", "10xTrimmed", "not10xTrimmed")
 	samples['AdpaterTrimorNot'] = np.where(samples['trimAdapters'] == "True", "AdaptTrimmed", "notAdaptTrimmed")
-	# for i in samples['sample'].unique():
-	# 	d10xtrim[i] = [samples['10xtrimorNot'][j] for j in samples[samples['sample']==i].index]
+
 	dictSamples=samples[['sample','meryl_kmer_size', '10xtrimorNot','AdpaterTrimorNot']]
 	dictSamples=dictSamples.set_index(['sample']).T.to_dict('list')
 
@@ -72,14 +70,7 @@ if set(['sample', 'Library_R1', 'Library_R2', 'meryl_kmer_size', 'trim10X', 'tri
 	testDictQC=testDictQC.set_index(['sample']).T.to_dict('list')
 
 	trimAdapters = samples[samples['trimAdapters'] == "True"]
-	# dAdaptertrim = {}
-	# for i in trimAdapters['sample'].unique():
-	# 	dAdaptertrim[i] = [trimAdapters['readCounter'][j] for j in trimAdapters[trimAdapters['sample']==i].index]
-	#
-	# runQC = samples[samples['fastQC'] == "True"]
-	# drunQCtrim = {}
-	# for i in runQC['sample'].unique():
-	# 	drunQCtrim[i] = [runQC['readCounter'][j] for j in runQC[runQC['sample']==i].index]
+
 	dictReadCounter = {}
 	for i in samples['sample'].unique():
 		dictReadCounter[i] = [samples['readCounter'][j] for j in samples[samples['sample']==i].index]
@@ -118,9 +109,7 @@ elif set(['sample', 'hifi_reads', 'meryl_kmer_size','trimSMRTbell', 'fastQC']).i
 	samples['readCounter'] = samples['readCounter'].astype(str)
 	samples['readCounter'] = samples['sample'] + "_Library" + samples['readCounter']
 	samples['smrtornot'] = np.where(samples['trimSMRTbell'] == "True", "smrtTrimmed", "notsmrtTrimmed")
-	# samplesDict=samples.set_index('sample').T.to_dict('list')
 
-	# samples=samples.reset_index()
 	dictSamples=samples[['sample','meryl_kmer_size', 'smrtornot']]
 	dictSamples=dictSamples.drop_duplicates('sample', keep='first')
 	dictSamples=dictSamples.set_index(['sample']).T.to_dict('list')
@@ -129,42 +118,10 @@ elif set(['sample', 'hifi_reads', 'meryl_kmer_size','trimSMRTbell', 'fastQC']).i
 	testDictQC=samples[['sample', 'smrtornot', 'fastQC']]
 	testDictQC = testDictQC[testDictQC['fastQC'] == "True"]
 
-	# testDictQC=testDictQC.drop_duplicates('sample', keep='first')
+
 	testDictQC=testDictQC.set_index(['sample']).T.to_dict('list')
 
-	# runQC = samples[samples['fastQC'] == "True"]
-	#
-	# drunQCtrim = {}
-	# for i in runQC['sample'].unique():
-	# 	drunQCtrim[i] = [runQC['readCounter'][j] for j in runQC[runQC['sample']==i].index]
-	#
-	# runQC=runQC.set_index(['sample','readCounter'])
-	#
-	#
-	# trimSMRTbell=samples.loc[samples['trimSMRTbell'] == "True"]
-	# dtrimSMRTbell = {}
-	# for i in trimSMRTbell['sample'].unique():
-	# 	dtrimSMRTbell[i] = [trimSMRTbell['readCounter'][j] for j in trimSMRTbell[trimSMRTbell['sample']==i].index]
-	# trimSMRTbell=trimSMRTbell.set_index(['sample','readCounter'])
-	# notrimSMRTbell = samples[samples['trimSMRTbell'] == "False"]
-	# notrimSMRTbell=notrimSMRTbell.set_index(['sample','readCounter'])
-
-
-	# dsmrtornot = {}
-	# dfsmrtornot=samples.drop_duplicates('smrtornot', keep='first')
-	#
-	# for i in samples['sample'].unique():
-	# 	dsmrtornot[i] = [dfsmrtornot['smrtornot'][j] for j in dfsmrtornot[dfsmrtornot['sample']==i].index]
-
-	# for i in samples['sample'].unique():
-	# 	dsmrtornot[i] = [samples['smrtornot'][j] for j in samples[samples['sample']==i].index]
-	#
-	#
 
-	# dkmerSize = {}
-	# dkmerDups=samples.drop_duplicates('meryl_kmer_size', keep='first')
-	# for i in samples['sample'].unique():
-	# 	dkmerSize[i] = [dkmerDups['meryl_kmer_size'][j] for j in dkmerDups[dkmerDups['sample']==i].index]
 	dictReadCounter = {}
 	for i in samples['sample'].unique():
 		dictReadCounter[i] = [samples['readCounter'][j] for j in samples[samples['sample']==i].index]
@@ -244,11 +201,13 @@ elif set(['ID',	'ASM_LEVEL', 'PRI_asm', 'ALT_asm',	'merylDB',	'merylDB_kmer', 'g
 	dictSamples=samples.T.to_dict('list')
 
 	ruleAllQCFiles=[]
-	ruleAll=expand(os.path.join(config['Results'],"1_evaluation/{asmID}/06_keyResults/{asmID}_aggregatedResults.tsv"), asmID=list(dictSamples.keys())),\
-	 		os.path.join(config['Results'],"1_evaluation/finalResults/Combined_Results_FULLTABLE.tsv"), \
+	ruleAll=expand(os.path.join(config['Results'],"1_evaluation/{asmID}/KEY_RESULTS/{asmID}_aggregatedResults.tsv"), asmID=list(dictSamples.keys())),\
+	 		os.path.join(config['Results'],"1_evaluation/finalResults/TABLE_OF_RESULTS.tsv"), \
 			os.path.join(config['Results'],"1_evaluation/finalResults/FULL_REPORT.pdf")
 
 
+###  DOWNLOAD BUSCO LINEAGE (IF IT DOESN'T ALREADY EXIST)  ####
+
 	args_o=os.path.join(workflow.basedir, "buscoLineage")
 	args_l=config['busco5Lineage']
 	checkLineagePath=args_o + "/" + args_l + "_odb10"
@@ -298,11 +257,6 @@ elif set(['ID',	'ASM_LEVEL', 'PRI_asm', 'ALT_asm',	'merylDB',	'merylDB_kmer', 'g
 		else:
 			raise ValueError("Error - could not identify lineage please check busco site for a correct prefix")
 
-
-			# os.path.join(config['Results'],"1_evaluation/finalResults/FULL_Report_PDF.pdf"), 			\
-			# os.path.join(config['Results'],"1_evaluation/finalResults/FULL_TABLE_PDF.pdf"),				\
-			# os.path.join(config['Results'],"1_evaluation/finalResults/FullTableCOLOUREDheatmap.pdf"),	\
-			# os.path.join(config['Results'],"1_evaluation/finalResults/FullTableGRADIENTheatmap.pdf")
 else:
 	raise ValueError('Sample Sheet for not recognised. Please make sure you are using the correct sample sheet')
 
@@ -314,13 +268,13 @@ else:
 if "Results" not in config:
 	config["Results"] = "results"
 
-report: "report/workflow.rst"
+
 
 include: whichRule
 
 
-inputs = ruleAllQCFiles, ruleAll
+final_target_outputs = ruleAllQCFiles, ruleAll
 
 rule all:
 	input:
-		inputs
+		final_target_outputs