Datasets:
thisisanshgupta
/
Pycode

Dataset card Data Studio Files Community
text
stringlengths
0
828
topcore = sorted(resultdict.items(), key=operator.itemgetter(1), reverse=True)
# If there are no results, populate negative results
if not resultdict:
sample[analysistype].blastresults = 'NA'
# If results, add a string of the best number of hits, and a string of the total number of genes
# This is currently 1013. If this changes, I may re-implement a dynamic method of determining
# this value
else:
sample[analysistype].blastresults[topcore[0][0]] = (str(topcore[0][1]), str(1013))
except FileNotFoundError:
sample[analysistype].blastresults = 'NA'
return metadata"
84,"def reporter(metadata, analysistype, reportpath):
""""""
Create the core genome report
:param metadata: type LIST: List of metadata objects
:param analysistype: type STR: Current analysis type
:param reportpath: type STR: Absolute path to folder in which the reports are to be created
:return:
""""""
header = 'Strain,ClosestRef,GenesPresent/Total,\n'
data = str()
for sample in metadata:
try:
if sample[analysistype].blastresults != 'NA':
if sample.general.closestrefseqgenus == 'Listeria':
# Write the sample name, closest ref genome, and the # of genes found / total # of genes
closestref = list(sample[analysistype].blastresults.items())[0][0]
coregenes = list(sample[analysistype].blastresults.items())[0][1][0]
# Find the closest reference file
try:
ref = glob(os.path.join(sample[analysistype].targetpath, '{fasta}*'
.format(fasta=closestref)))[0]
except IndexError:
# Replace underscores with dashes to find files
closestref = closestref.replace('_', '-')
ref = glob(os.path.join(sample[analysistype].targetpath, '{fasta}*'
.format(fasta=closestref)))[0]
# Determine the number of core genes present in the closest reference file
totalcore = 0
for _ in SeqIO.parse(ref, 'fasta'):
totalcore += 1
# Add the data to the object
sample[analysistype].targetspresent = coregenes
sample[analysistype].totaltargets = totalcore
sample[analysistype].coreresults = '{cg}/{tc}'.format(cg=coregenes,
tc=totalcore)
row = '{sn},{cr},{cg}/{tc}\n'.format(sn=sample.name,
cr=closestref,
cg=coregenes,
tc=totalcore)
# Open the report
with open(os.path.join(sample[analysistype].reportdir,
'{sn}_{at}.csv'.format(sn=sample.name,
at=analysistype)), 'w') as report:
# Write the row to the report
report.write(header)
report.write(row)
data += row
else:
sample[analysistype].targetspresent = 'NA'
sample[analysistype].totaltargets = 'NA'
sample[analysistype].coreresults = 'NA'
except KeyError:
sample[analysistype].targetspresent = 'NA'
sample[analysistype].totaltargets = 'NA'
sample[analysistype].coreresults = 'NA'
with open(os.path.join(reportpath, 'coregenome.csv'), 'w') as report:
# Write the data to the report
report.write(header)
report.write(data)"
85,"def annotatedcore(self):
""""""
Calculates the core genome of organisms using custom databases
""""""
logging.info('Calculating annotated core')
# Determine the total number of core genes
self.total_core()
# Iterate through all the samples, and process all Escherichia
for sample in self.metadata:
if sample.general.bestassemblyfile != 'NA':
# Create a set to store the names of all the core genes in this strain
sample[self.analysistype].coreset = set()
if sample.general.referencegenus == 'Escherichia':
# Add the Escherichia sample to the runmetadata
self.runmetadata.samples.append(sample)
# Parse the BLAST report
try:
report = sample[self.analysistype].report
self.blastparser(report=report,
sample=sample,
fieldnames=self.fieldnames)
except KeyError:
sample[self.analysistype].coreset = list()
# Create the report
self.reporter()"
86,"def total_core(self):
""""""
Determine the total number of core genes present
""""""