def main():
readslist = []
readslist2 = []
input = "/Users/Xin/Desktop/IC_project/output/rpoB_output/ICW_rpoB.fasta"
output0 = "read_counts.csv"
output = open("ICW_rpoB_nopaired.fasta", 'w')
reads_tag ='_2:N:0:5'
try:
f0 = open(input, 'r')
print("Open success!")
except IOError:
print ("no such file!")
for line in f0:
tmp0 = re.search("^\>(M00704:49:000000000-AFW6D[\d\:]+)",line)
if tmp0:
read = tmp0.group(1)
readslist.append(read)
print("Number of the reads in the list is ", len(readslist))
f0.close()
df_reads = pd.DataFrame(readslist, columns = ['read'])
read_counts = df_reads['read'].value_counts()
read_counts.to_csv(output0)
f= open(input, 'r')
with open("/Users/Xin/Desktop/IC_project/output/rpoB_output/read_counts.csv", 'r') as csvfile:
f1 = csv.DictReader(csvfile, delimiter = ",", fieldnames = ['read','count'])
for row in f1:
if int(row['count']) == 2:
readslist2.append(row['read']+reads_tag)
subset = Subsampling()
subset.exclude(f, readslist2, output)
def main():
input1dir = input('Reads collections: ')
input2dir = input('Reads filter: ')
outputdir = input('Output file: ')
output = open(outputdir, 'w')
try:
all_reads = open(input1dir, 'r')
except IOError:
print ("no such file!")
readslist = []
with open(input2dir, 'r') as inputfile:
f = csv.DictReader(inputfile, delimiter =",", fieldnames=['reads','genus'])
for row in f:
readslist.append(row['reads']) # all the reads
print("total reads in filter list:", len(readslist))
subset = Subsampling()
subset.exclude(all_reads, readslist, output)
def main():
genuslist = []
readlist = []
inputfiledir1 = "/Users/Xin/Desktop/IC_project/output/Jan222016/resource_tables/ICC_DS2_2_unmapped_genus_count.csv"
inputfiledir2 = "/Users/Xin/Desktop/IC_project/output/Jan222016/resource_tables/ICC_DS2_2_unmapped_taxa.csv"
inputfiledir3 = "/Users/Xin/Desktop/IC_project/output/ICC_DS2_CLC_mapping_output/ICC_DS2_2_CLC_unmapped.fa"
outputfiledir = "/Users/Xin/Desktop/IC_project/output/Feb032016/ICC_DS2_2_unmapped_genus.fa"
outputfile = open(outputfiledir, 'w')
seq = open(inputfiledir3, 'r')
genus = pd.read_csv(inputfiledir1, names=["taxa", "count"], header=None)
read_taxa = pd.read_csv(inputfiledir2, names=["num", "read","id","taxa"], header=None)
for row in genus["taxa"]:
genuslist.append(row)
for i in range(0,len(read_taxa["taxa"])):
tmp = read_taxa["taxa"][i]
if tmp in genuslist:
readlist.append(read_taxa["read"][i])
subset = Subsampling()
subset.include(seq, readlist, outputfile)
def main(argv):
if len(argv[1:]) == 3:
input1dir = argv[1]
input2dir = argv[2]
outputdir = argv[3]
else:
print("Three arguements are needed!!")
output = open(outputdir, 'w')
try:
all_reads = open(input1dir, 'r')
except IOError:
print ("no such file!")
readslist = []
with open(input2dir, 'r') as inputfile:
f = csv.DictReader(inputfile, delimiter =",", fieldnames=['reads','genus'])
for row in f:
readslist.append(row['reads']) # all the reads
print("total reads in filter list:", len(readslist))
subset = Subsampling()
subset.exclude(all_reads, readslist, output)