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abil-genecaller.py
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#!/usr/bin/env python
import getopt
import sys
import logging
import os
import time
import ast
import gzip
import re
import tempfile
import shutil
import xml.etree.ElementTree as ET
try:
from urllib.request import urlopen, urlretrieve
except ImportError:
from urllib import urlopen, urlretrieve
import argparse
import math
from collections import defaultdict
import sys
version = """ abil-genecaller v1 (updated : March 29, 2018) """
"""
abil-genecaller free for academic users and requires permission before any
commercial or government usage use for any version of this code/algorithm.
If you are a commercial or governmental user, please contact [email protected]
for permissions.
For additional terms and conditions for government employees, see
"For Government Employees" section
LICENSE TERMS FOR stringMLST
Adopted from: https://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International Public
License
By exercising the Licensed Rights (defined below), You accept and agree to be
bound by the terms and conditions of this Creative Commons Attribution-
NonCommercial-ShareAlike 4.0 International Public License ("Public License"). To
the extent this Public License may be interpreted as a contract, You are granted
the Licensed Rights in consideration of Your acceptance of these terms and
conditions, and the Licensor grants You such rights in consideration of benefits
the Licensor receives from making the Licensed Material available under these
terms and conditions.
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derived from or based upon the Licensed Material and in which the Licensed
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For Government Employees
Definitions
"Applied Bioformatics Laboratory" and "ABiL" refer to the Applied
Bioinformatics Laboratory, a public-private partnership between IHRC Inc. and
Georgia Institute of Technology, 950 Atlantic Drive / Engineered Biosystems
Building, Room 2200 /Atlanta, GA 30332. "You" or "Your" refers to the
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restrictions within this License. This Program is provided as-is with no
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copyright or other license over the Python modules utilized by this Program.
Please refer to the license terms for each module for additional information.
The program has 3 basic modes :
mainTool: for single sample (both single and paired end)
batchTool: for multiple samples stored at a common location (both single and paired end samples)
listTool: for multiple samples with location information stored in a list (both single and paired end samples)
predict part starts here
"""
#############################################################
# Function : get_links
# Input : speciesName and schemes dict
# Output : Dict containing links to alleles and profile
# Description: Gets the URLs from pubMLST for the required
# files (alleles, profile)
#############################################################
############################################################
# Function : batchTool
# Input : Directory name, paired or single, k value
# Output : STs and allelic profiles for each FASTQ file
# Description: Processes all FASTQ files present in the input
# directory
#############################################################
def batchTool(fdir, paired, k):
fileList = []
if not dir.endswith('/'):
fdir += '/'
for inputFile in os.listdir(fdir):
if paired is True:
if inputFile.endswith('1.fastq') or inputFile.endswith('1.fq') or inputFile.endswith('1.fq.gz') or inputFile.endswith('1.fastq.gz'):
fastq1 = fdir+inputFile
fastq2 = fdir+inputFile.replace('1.', '2.')
fileList.append((fastq1, fastq2))
else:
if inputFile.endswith('.fastq') or inputFile.endswith('.fq') or inputFile.endswith('.fq.gz') or inputFile.endswith('.fastq.gz'):
fastq1 = fdir + inputFile
fileList.append(fastq1)
results = multiSampleTool(fileList, paired, k)
return results
#############################################################
# Function : listTool
# Input : List file, paired or single, k value
# Output : STs and allelic profiles for each FASTQ file
# Description: Processes all FASTQ files present in the input
# list file
#############################################################
def listTool(fList, paired, k):
fileList = []
listf = open(fList, 'r')
samples = listf.readlines()
for sample in samples:
if paired is True:
s = sample.strip().split()
fastq1 = s[0]
try:
fastq2 = s[1]
except IndexError:
print("Error: Paired end files should be whitespace/tab seperated")
exit(0)
fileList.append((fastq1, fastq2))
else:
fastq1 = sample.rstrip()
fileList.append(fastq1)
results = multiSampleTool(fileList, paired, k)
return results
#############################################################
# Function : multiSampleTool
# Input : List of files to process, paired or single, k value
# Output : STs and allelic profiles for each FASTQ file
# Description: Processes all FASTQ files present in the input list
#############################################################
def multiSampleTool(fileList, paired, k):
results = {}
for sample in fileList:
if paired is True:
fastq1 = sample[0]
fastq2 = sample[1]
else:
fastq1 = sample
fastq2 = None
results = singleSampleTool(fastq1, fastq2, paired, k, results)
return results
#############################################################
# Function : singleSampleTool
# Input : fastq file 1 and 2, paired or single, k value, output dictionary
# Output : STs and allelic profiles for each FASTQ file
# Description: Processes both FASTQ files passed to the function
#############################################################
def singleSampleTool(fastq1, fastq2, paired, k, results):
if paired is True:
fileName = fastq1.split('/')[-1].split('.')[0][:-1]
else:
fileName = fastq1.split('/')[-1].split('.')[0]
if reads is True:
readFileName = fileName + '_reads.fq'
global readFile
readFile = open(readFileName, 'w+')
if paired is True:
msg = "singleSampleTool : " + fastq1 + ' and ' + fastq2
else:
msg = "singleSampleTool : " + fastq1
logging.debug(msg)
global alleleCount
alleleCount = {}
t1 = time.time()
if paired is True:
logging.debug("singleSampleTool : paired True")
logging.debug("singleSampleTool : fastq1 start")
singleFileTool(fastq1, k)
logging.debug("singleSampleTool : fastq1 done")
logging.debug("singleSampleTool : fastq2 start")
singleFileTool(fastq2, k)
logging.debug("singleSampleTool : fastq2 done")
if alleleCount == {}:
string = "No k-mer matches were found for the sample " + fastq1 + " and "+ fastq2 + ". Probable cause of the error: low quality data/too many N's in the data"
logging.error("singleSampleTool : " + string)
print(string)
# exit(0)
profileCount = alleleCount
else:
logging.debug("singleSampleTool : paired False")
logging.debug("singleSampleTool : fastq start")
singleFileTool(fastq1, k)
profileCount = alleleCount
logging.debug("singleSampleTool : fastq done")
if alleleCount == 0:
string = "No k-mer matches were found for the sample " + fastq1 + ". Probable cause of the error: low quality data/too many N's in the data"
logging.error("singleSampleTool : " + string)
print(string)
logging.debug("singleSampleTool : weightedProfile start")
weightedProfile = weightedProf(profileCount, weightDict)
logging.debug("singleSampleTool : weightedProfile finished")
logging.debug("singleSampleTool : getMaxCount start")
finalProfile = getMaxCount(weightedProfile, fileName)
logging.debug("singleSampleTool : getMaxCount end")
st = 0
if profileFile != '':
logging.debug("singleSampleTool : findST start")
st = findST(finalProfile, stProfile)
logging.debug("singleSampleTool : findST end")
if reads is True:
readFile.close()
t3 = time.time()
finalProfile['ST'] = st
finalProfile['t'] = t3-t1
results[fileName] = finalProfile
return results
#############################################################
# Function : singleFileTool
# Input : fastq file, k value
# Output : Edits a global dictionary - results
# Description: Processes the single fastq file
#############################################################
def singleFileTool(fastq, k):
msg = "singleFileTool :" + fastq
logging.debug(msg)
if os.path.isfile(fastq):
logging.debug("singleFileTool : fastq")
non_overlapping_window = 1
finalProfile = {}
t1 = time.time()
fileExplorer(fastq, k, non_overlapping_window)
t3 = time.time()
else:
msg = "File does not exist: " + fastq
logging.error("singleFileTool : msg")
print(msg)
def fileExplorer(file, k, non_overlapping_window):
if file.endswith('.gz'):
if sys.version_info[0] == 3:
f = gzip.open(file, 'rt')
else:
f = gzip.open(file, 'rb')
else:
f = open(file)
msg = "fileExplorer :" + file
logging.debug(msg)
lines = f.readlines()
i = 1
n_reads = 0
try:
if len(lines[1]) < k:
m1 = "Read length " + len(lines[1])+" for file " + file + " smaller than " + k
print(m1)
print("Skipping to next file.")
logging.debug(m1)
return 0
except Exception:
m2 = "Check fastq file " + file
print(m2)
logging.debug(m2)
return 0
start = int((len(lines[1])-k)//2)
end = int((len(lines[1])-k)//2)
yesRead = False
for line in lines:
if i % 4 == 0 and yesRead:
readFile.write(line)
if i % 4 != 3:
yesRead = False
if i%4 == 1:
head = line
if i%4 == 2:
s1 = str(line[start:k+start])
sn_1 = str(line[-k-end:-end]).rstrip()
if s1 in kmerDict[k]:
n_reads += 1
goodReads(line, k, non_overlapping_window)
if reads is True:
readFile.write(head)
readFile.write(line)
readFile.write('+\n')
yesRead = True
i += 1
#############################################################
# Function : goodReads
# Input : sequence read, k, step size
# Output : Edits the count of global variable alleleCount
# Description: Increment the count for each k-mer match
#############################################################
def goodReads(read, k, non_overlapping_window):
n = 0
line = read.rstrip()
while n+k <= len(line):
s = str(line[n:n+k])
if s in kmerDict[k]:
for probLoc in kmerDict[k][s]:
if probLoc not in alleleCount:
alleleCount[probLoc] = {}
a = kmerDict[k][s][probLoc]
for allele in a:
allele = allele.rstrip()
if allele in alleleCount[probLoc]:
alleleCount[probLoc][allele] += 1
else:
alleleCount[probLoc][allele] = 1
n += non_overlapping_window
#############################################################
# Function : weightedProf
# Input : allele count global var, weight factors
# Output/Desc: Normalizes alleleCount by weight factor
#############################################################
def weightedProf(alleleCount, weightDict):
logging.debug("weightedProf")
weightedDict = {}
for loc in alleleCount:
weightedDict[loc] = {}
for allele in alleleCount[loc]:
if loc in weightDict:
if allele in weightDict[loc]:
weightedDict[loc][allele] = (alleleCount[loc][allele] / weightDict[loc][allele])
else:
weightedDict[loc][allele] = alleleCount[loc][allele]
else:
weightedDict[loc][allele] = alleleCount[loc][allele]
return weightedDict
#############################################################
# Function : getMaxCount
# Input : allele counts
# Output : allelic profile and ST
# Description: Finds the alleles with maximum counts and
# generates the allelic profile and ST
#############################################################
def getMaxCount(alleleCount, fileName):
logging.debug("getMaxCount")
max_n = {}
secondMax = {}
maxSupport = {}
secondSupport = {}
finalProfileCount = {}
num = ''
for loc in alleleCount:
n = 0
m = 0
for num in alleleCount[loc]:
if alleleCount[loc][num] >= n:
m = n
n = alleleCount[loc][num]
if n-m < fuzzy:
alleleCount[loc][num] = str(alleleCount[loc][num])+'*'
max_n[loc] = str(n)+'*'
else:
max_n[loc] = n
secondMax[loc] = m
for loc in alleleCount:
maxSupport[loc] = {}
secondSupport[loc] = {}
num_max = []
num_max2 = []
compare = float(re.sub("\*$", "", str(max_n[loc])))
for num in alleleCount[loc]:
if alleleCount[loc][num] == compare:
if "\*" in str(max_n[loc]):
insert = num + '*'
num_max.append(insert)
else:
num_max.append(num)
maxSupport[loc][num] = max_n[loc]
if alleleCount[loc][num] == secondMax[loc]:
num_max2.append(num)
secondSupport[loc][num] = secondMax[loc]
try:
finalProfileCount[loc] = num_max[0]
except LookupError:
finalProfileCount[loc] = '0'
msgs = "Max Support :" + fileName + " : " + str(maxSupport)
logging.debug(msgs)
msgs = "Second Max Support :" + fileName + " : " + str(secondSupport)
logging.debug(msgs)
return finalProfileCount
#############################################################
# Function : findST
# Input : allelic profile for one sample and profiles for all STs
# Output : ST number, or 0 if no ST match was found
# Description: Finds the ST number which best matches the given sample profile.
#############################################################
def findST(finalProfile, stProfile):
if not stProfile:
return 0
oneProfile = next(iter(stProfile.values()))
# The gene names in finalProfile may not exactly match those in stProfile. To deal with this,
# each finalProfile gene is associated with the best matching gene in the ST profiles.
finalGeneToSTGene = {}
profileGenes = list(oneProfile.keys())
for finalGene in list(finalProfile.keys()):
if finalGene in profileGenes: # exact match is preferable
finalGeneToSTGene[finalGene] = finalGene
else: # failing an exact match, look for a case-sensitive containment
for profileGene in profileGenes:
if finalGene in profileGene:
finalGeneToSTGene[finalGene] = profileGene
break
if finalGene not in finalGeneToSTGene: # if there's still no match, try a case-insensitive containment
for profileGene in profileGenes:
if finalGene.lower() in profileGene.lower():
finalGeneToSTGene[finalGene] = profileGene
break
if finalGene not in finalGeneToSTGene:
print("ERROR: gene names in config file do not match gene names in profile file")
exit(0)
transformedFinalProfile = {}
for gene, allele in finalProfile.items():
allele = re.sub("\*", "", allele)
transformedFinalProfile[finalGeneToSTGene[gene]] = allele
# Check to see if the dictionary is empty, if so then means no allele were found at all
if bool(transformedFinalProfile) is False:
return 0
# Find the best matching ST, considering only the genes in the sample's profile. This is to
# allow for superfluous columns in the ST profile.
logging.debug("findST")
for stNum, profile in stProfile.items():
if all(x in list(profile.items()) for x in list(transformedFinalProfile.items())):
return stNum
return 0
#############################################################
# Function : loadModule
# Input : k value and prefix of the DB file
# Output : Updates the DB dictionary variables
# Description: Used in loading the DB as set of variables
# by calling other functions
#############################################################
def loadModule(k, dbPrefix):
global dbFile
dbFile = dbPrefix+'_'+str(k)+'.txt'
global weightFile
weightFile = dbPrefix+'_weight.txt'
global profileFile
profileFile = dbPrefix+'_profile.txt'
global kmerDict
kmerDict = {}
kmerDict[k] = loadKmerDict(dbFile)
global weightDict
weightDict = loadWeightDict(weightFile)
global stProfile
stProfile = loadSTfromFile(profileFile)
#############################################################
# Function : loadSTfromFile
# Input : profile definition file
# Output : Updates the DB dictionary variables
# Description: Used in loading the DB as set of variables
#############################################################
def loadSTfromFile(profileF):
with open(profileF, 'r') as definitionFile:
st = {}
index = {}
lines = definitionFile.readlines()
heads = lines[0].rstrip().split('\t')
for locus in heads:
index[locus] = heads.index(locus)
for line in lines:
pro = line.rstrip().split('\t')
l = {}
for locus in heads[1:]:
try:
l[locus] = pro[index[locus]]
except LookupError:
logging.debug("ERROR while loading ST")
pass
st[pro[0]] = l
return st
#############################################################
# Function : loadKmerDict
# Input : DB prefix
# Output : Updates the DB dictionary variables
# Description: Used in loading the DB as set of variables
#############################################################
def loadKmerDict(dbFile):
kmerTableDict = {}
with open(dbFile, 'r') as kmerTableFile:
lines = kmerTableFile.readlines()
for line in lines:
array = line.rstrip().rsplit('\t')
kmerTableDict[array[0]] = {}
kmerTableDict[array[0]][array[1]] = array[2][1:-1].rsplit(',')
return kmerTableDict
#############################################################
# Function : loadWeightDict
# Input : Weight file prefix
# Output : Updates the DB dictionary variables
# Description: Used in loading the DB as set of variables
#############################################################
def loadWeightDict(weightFile):
weightDict = {}
with open(weightFile, 'r') as weightTableFile:
lines = weightTableFile.readlines()
for line in lines:
array = line.rstrip().rsplit('\t')
try:
(loc, allele) = array[0].replace('-','_').rsplit('_',1)
except ValueError:
print("Error : Allele name in locus file should be seperated by '_' or '-'")
exit(0)
if loc not in weightDict:
weightDict[loc] = {}
weightDict[loc][allele] = float(array[1])
return weightDict
#############################################################
# Function : loadConfig
# Input : config file path from getopts
# Output : Updates configDict
# Description: Used to find allele fasta files for getCoverage
#############################################################
def loadConfig(config):
global configDict
configDict = {}
with open(config) as configFile:
lines = configFile.readlines()
head = ''
for line in lines:
if line.rstrip() == '':
continue
if line.rstrip() == '[loci]':
head = 'loci'
configDict[head] = {}
elif line.rstrip() == '[profile]':
head = 'profile'
configDict[head] = {}
else:
arr = line.strip().split()
configDict[head][arr[0]] = arr[1]
for head in configDict:
for element in configDict[head]:
if not os.path.isfile(configDict[head][element]):
print("ERROR: %s file does not exist at %s" % (element, configDict[head][element]))
exit(0)
return configDict
#############################################################
# Function : getCoverage
# Input : results dictionary
# Output : Updates results to include coverage info
#############################################################
def getCoverage(results):
global resCov
resCov = {}
tmpdir = tempfile.mkdtemp()
genelen = {}
for sample in results:
resCov[sample] = {}
spadesCmd = "spades.py --only-assembler -s " + sample + "_reads.fq " + "-k 53 -o " + sample + " > /dev/null"
spadesLog = "Assembling alleles for sample:\t" + sample
logging.debug(spadesLog)
sys.stderr.write(spadesLog + '\n')
try:
os.system(spadesCmd)
except:
spadesErr = "Building assemly failed"
logging.error(spadesErr)
sys.stderr.write(spadesErr + "\n")
if not batch:
exit()
else:
continue
src = "./" + sample + "/scaffolds.fasta"
dest = "./" + sample + ".fasta"
try:
shutil.copyfile(src,dest)
except IOError as e:
cpErr = "Could not copy " + sample + "/scaffolds.fasta\nPlease check the spades.log in " + sample + "/\nThe most likely cause of this error is no assembly could be produced\nbecause not enough reads were selected\n"
logging.error(cpErr)
sys.stderr.write(cpErr)
if not batch:
exit()
else:
continue
else:
shutil.rmtree(sample, ignore_errors=True)
file = tmpdir +'/'+ sample + '.fasta'
bed = tmpdir +'/'+ sample + '.bed'
sortedFile = tmpdir +'/'+ sample + '.sorted'
covOut = tmpdir +'/'+ sample + '.out'
bgOut = tmpdir +'/'+ sample + '.bg'
with open(file, 'w') as tmpFasta:
with open(bed, 'w') as bedFile:
for gene in configDict['loci']:
if gene in results[sample]:
genes = Fasta(configDict['loci'][gene])
allele = gene+'-'+ str(results[sample][gene])
tmpFasta.write('>'+gene+'\n')
bedFile.write(gene+'\t0\t'+str(len(genes[allele]))+'\n')
genelen[gene] = len(genes[allele])
for line in genes[allele]:
tmpFasta.write(str(line)+'\n')
else:
logging.errror(gene + " not found in sample")
sys.stderr.write(gene + " not found in sample")
results[sample][gene] = "NotFound"
cmdIndex = "bwa index %s 2>/dev/null"%(file)
os.system(cmdIndex)
readBWA = sample+'_reads.fq'
cmdBwaMem = "bwa mem %s %s 2>/dev/null| samtools view -uS - | samtools sort - -o %s"%(file, readBWA, sortedFile)
os.system(cmdBwaMem)
cmdCov = "bedtools coverage -a %s -b %s > %s"%(bed, sortedFile, covOut)
os.system(cmdCov)
with open(covOut, 'r') as cov:
for line in cov.readlines():
records = line.rstrip().rsplit('\t')
gene = records[0]
geneCov = float(records[6]) * 100
results[sample][gene] = results[sample][gene] + " (" + str("%.2f" % geneCov) + ")"
aln = {}
cmdBg = "bedtools genomecov -d -ibam %s > %s"%(sortedFile, bgOut)
os.system(cmdBg)
# lastline = open(bgOut, "r").readlines()[-1]
all_content = defaultdict(list)
with open(bgOut, 'r') as bedgraph:
for line in bedgraph:
line = line.rstrip()
line_content = line.split("\t")
gene_name = line_content[0]
all_content[gene_name].append([line_content[1], line_content[2]])
for gene in all_content:
all_depths = list()
for line in all_content[gene]:
all_depths.append(line[1])
mean_value = mean(all_depths)
sd = stdev(all_depths, mean_value)
# threshold_upper = mean_value + 2*sd
threshold_lower = mean_value - 3*sd
counter = 0
# Uncomment the next line to see gene, mean_value, and thresholds
# print "{}\t{}\t{}\t{}".format(gene, mean_value, threshold_upper, threshold_lower)
covLog = sample + ".log"
with open(covLog, 'w') as logfile:
for line in all_content[gene]:
if (int(line[1]) <= threshold_lower):
if counter == 0:
logfile.write("The outliers for {} are:\nPosition\tDepth\n".format(gene))
counter += 1
logfile.write("{}\t{}\n".format(line[0], line[1]))
logfile.close()
mkdbCmd = "makeblastdb -dbtype nucl -in " + file + " -out " + tmpdir + "/blastdb > /dev/null"
try:
os.system(mkdbCmd)
except:
sys.stderr.write("Could not build blastdb. Continuing but results may be wrong\n")
pass
blastCmd = "blastn -db " + tmpdir + "/blastdb -query " + sample + ".fasta -outfmt '6 qseqid sseqid bitscore pident sseq sstrand qcovshsp length slen qstart qend qlen' | sort -k 3 -g > " + tmpdir + "/blast.out 2> /dev/null"
try:
os.system(blastCmd)
except:
sys.stderr.write("blastn failed. Continuing, but gene names will be wrong\n")
pass
blastOut = tmpdir + "/blast.out"
outfile = open(sample + '.fasta','w')
with open(blastOut, 'r') as blastres:
for line in blastres.readlines():
cols = line.split()
if len(cols) < 11:
print("BLAST output does not have the 11 columns expected")
exit()
if cols[5] == "minus":
out = reverseComplement(cols[4])
else:
out = cols[4]
perCov = 100.00 * (float(cols[6])/float(cols[7]))
if perCov > 100:
perCov = 100.00
resCov[sample][cols[1]] = cols[3]
outfile.write(">%s|%s|PercentID=%.2f|Coverage=%.2f\n%s\n"%(cols[1],cols[0],float(cols[3]),perCov,out))
outfile.close()
shutil.rmtree(tmpdir)
#############################################################
# Function : mean
# Input : List of numbers
# Output : Returns the mean of the data.
# Description: Function for calculating the mean of an input list.
#############################################################
def mean(number_list):
n = len(number_list)
if n < 1:
raise ValueError('mean requires at least one data point')
total = 0
for i in number_list:
total += int(i)
return total/n
#############################################################
# Function : stdev
# Input : List of numbers, mean
# Output : Returns the standard deviation of the data.
# Description: Function for calculating the standard deviation of an input list.
#############################################################
def stdev(number_list, x_bar):
mean_diff = 0
for number in number_list:
mean_diff += (int(number) - x_bar)**2
return math.sqrt(mean_diff/(len(number_list) - 1))
#############################################################
# Function : printResults
# Input : results, output file, overwrite?
# Output : Prints on the screen or in a file
# Description: Prints the results in the format asked by the user
#############################################################
def printResults(results, output_filename, overwrite, timeDisp):
if output_filename != None:
if overwrite is False:
outfile = open(output_filename, "a")
else:
outfile = open(output_filename, "w")
heading = "Sample"
for head in sorted(configDict['loci']):
heading += '\t' + head
if output_filename != None:
outfile.write(heading)
outfile.write('\n')
else:
print(heading)
for s in results:
sample = s
# for l in sorted(results[s]):
for l in sorted( configDict['loci']):
if l == 'ST' or l == 't':
continue
elif l in resCov[s]:
sample += "\t" + resCov[s][l]
else:
sample += "\tNotFound"
# if results[s]['ST'] == 1:
# sample += results[s][l] + "WT"
# else:
# sample += results[s][l] = "Resistant"
if output_filename != None:
outfile.write(sample)
outfile.write('\n')
else:
print(sample)
"""Predict part ends here"""
"""Build DB part starts"""
"""Returns the reverse complement of the sequence"""
def reverseComplement(seq):
seqU = seq.upper()
seq_dict = {'A':'T', 'T':'A', 'G':'C', 'C':'G', 'Y':'R', 'R':'Y', 'S':'S', 'W':'W', 'K':'M', 'M':'K', 'N':'N'}
try:
return "".join([seq_dict[base] for base in reversed(seqU)])
except Exception:
strn = "Reverse Complement Error:" + seqU
logging.debug(strn)
pass
#############################################################
# Function : getFastaDict
# Input : locus file name
# Output : dictionary with all the allele sequences
# Description: Stores each allele sequence in a dictionary
#############################################################
def getFastaDict(fullLocusFile):
logging.debug("Create Fasta Dict")
logging.debug(fullLocusFile)
fastaFile = open(fullLocusFile, 'r').read()
entries = [x for x in fastaFile.split('>') if len(x) != 0]
fastaDict = {}
for entry in entries:
key = [x for x in entry.split('\n')[0].split() if len(x) != 0][0]
sequence = ''.join(entry.split('\n')[1:]).rstrip()
fastaDict[key] = {'sequence':sequence}
return fastaDict
#############################################################