def best_match(SEQ1, LIST, MAX = float("inf"), IGNORE_N = 0, PRINT = 0 ):
"""finds the best match for a sequence in a list of sequences.
MAX sets the number of max number of mismatches before it moves on.
Lowering MAX increases performance.
IGNORE_N = 1 will ignore mismatches with N."""
x = []
xcount = []
y = MAX
no_exact_match = 0
#first search for exact matach
for i in range(len(LIST)):
if SEQ1 == LIST[i]:
no_exact_match = 0
return i
break
if no_exact_match:
for i in range(len(LIST)):
z = BC.mismatches(SEQ1, LIST[i], y, IGNORE_N)
if z < y:
y = z
x.append(i)
xcount.append(z)
if z == 0:
break
if len(x) > 0:
comp = "==" + str(min(xcount))
best = [a for a,b in enumerate(xcount) if eval(str(b) + comp)]
if PRINT == 1:
print SEQ1
print LIST[x[0]]
print x[best[0]], xcount[best[0]]
return x[best[0]]
else:
return -1
def calc(self, a=1, b=1, c=1):
a = int(self.entry.get())
b = int(self.entry2.get())
c = int(self.entry3.get())
final = BC.convert(a,b,c)
self.result.delete(0,END)
self.result.insert(END,final)
def calc(self, a=1, b=1, c=1):
a = int(self.entry.get())
b = int(self.entry2.get())
c = int(self.entry3.get())
final = BC.convert(a, b, c)
self.result.delete(0, END)
self.result.insert(END, final)
def test_bc(self):
poissonForm = PoissonFormulation.PoissonFormulation(2, True)
poissonBF = poissonForm.bf()
mesh = MeshFactory.MeshFactory_rectilinearMesh(poissonBF, [1.0, 1.0],
[2, 3], 4)
s = Solution.Solution_solution(mesh)
bc = BC.BC_bc()
s.setBC(bc)
#self.assertEqual(bc, s.bc())
# i want to test that what I set is equal to what I used to set it with, but
# since that won't work, I can at least test that they behave in the same way
self.assertEqual(bc.singlePointBC(0), s.bc().singlePointBC(0))
def testBC(self):
poissonForm = PoissonFormulation.PoissonFormulation(2, True)
poissonBF = poissonForm.bf()
mesh = MeshFactory.MeshFactory_rectilinearMesh(poissonBF, [1.0, 1.0],
[2, 3], 4)
soln = Solution.Solution_solution(mesh)
vf = VarFactory.VarFactory()
fv = vf.fieldVar("Hello")
testBC = BC.BC_bc()
soln.setBC(testBC)
self.assertEqual(testBC.bcsImposed(fv.ID()),
soln.bc().bcsImposed(fv.ID()))
def main():
print(
"Please select an option below: \n 1) Create test user\n 2) create user \n 0) Quit\n"
)
user_input = input()
print(user_input)
if (user_input == '1'):
test_case = BC()
# print(test_case)
elif (user_input == '2'):
create = c.create_user()
else:
print("Exiting......\n")
def testZeroMeanConstraint(self):
#Initial Test Values & Set up of Dummy variable
vf = VarFactory.VarFactory()
bc = BC.BC_bc()
testVar = vf.fieldVar("testVar", 2)
ID = testVar.ID()
bc.addZeroMeanConstraint(testVar)
#Test to see if ZeroMeanConstraint has been added correctly
self.assertTrue(bc.imposeZeroMeanConstraint(ID),
"No Zero Mean Constraint Imposed")
#Test to see if one can correctly remove ZeroMeanConstraint
bc.removeZeroMeanConstraint(ID)
self.assertFalse(bc.imposeZeroMeanConstraint(ID),
"Zero Mean Constraint not removed")
def testSinglePoint(self):
#Initial Test Values & Set up of Dummy variable
vf = VarFactory.VarFactory()
testVar = vf.fieldVar("testVar", 2)
ID = testVar.ID()
testVertex = 4294967295
testFieldID = 9
testValue = 17.1
bc = BC.BC_bc()
bc.addSinglePointBC(testFieldID, testValue)
#Test to see if Single Point BC has been added correctly
self.assertFalse(bc.bcsImposed(testFieldID),
"Single Point BC not Imposed")
self.assertTrue(bc.singlePointBC(testFieldID), "No Single Point BC")
self.assertTrue(testValue == bc.valueForSinglePointBC(testFieldID),
"Value on Single Point BC not maintained")
self.assertEquals(testVertex, bc.vertexForSinglePointBC(testFieldID),
"Vertex on Single Point BC not maintained")
def testDirichlet(self):
#Initial Test Values & Set up of Dummy variable
testSpatialFilter = SpatialFilter.SpatialFilter.allSpace()
testFunction = Function.Function.xn()
vf = VarFactory.VarFactory()
bc = BC.BC_bc()
traceVar = vf.traceVar("traceVar", 2)
ID = traceVar.ID()
a = [testSpatialFilter, testFunction]
bc.addDirichlet(traceVar, testSpatialFilter, testFunction)
#Tests to see if Dirichlet has been added correctly
self.assertTrue(
testFunction.evaluate(2, 3) == bc.getDirichletBC(ID)[1].evaluate(
2, 3), "Dirichlet BC failed")
#Maybe same thing as line 60 for spatial filter?
self.assertTrue(
testFunction.evaluate(4, 3) ==
bc.getSpatiallyFilteredFunctionForDirichletBC(ID).evaluate(4, 3),
"Dirichlet Spatially Filtered Funtion failed")
def testExporter(self):
#Initial Test Values & Set Up Dummy Variables
poissonForm = PoissonFormulation.PoissonFormulation(2, True)
poissonBF = poissonForm.bf(
) #ToDo Give the VarFactory a field & test variable
testMesh = MeshFactory.MeshFactory_rectilinearMesh(
poissonBF, [1.2, 1.4], [2, 3], 2)
testFunction = Function.Function.xn()
testFunction2 = Function.Function.yn()
testVector = [testFunction, testFunction2]
testVector2 = ["function1", "function2"]
testBC = BC.BC_bc()
testSolutionPtr = Solution.Solution_solution(testMesh)
testExport = HDF5Exporter.HDF5Exporter(testMesh, "output", ".")
#Tests exportFunction using definition #1
testExport.exportFunction(testFunction, "function", 0)
#Tests exportFunction using definition #2
testExport.exportFunction(testVector, testVector2, 0)
#Tests exportSolution
testExport.exportSolution(testSolutionPtr, 0)
def linear_equation_system(
Rwx, Rwy, Rwz, Tg, Tyz, Pg,
P): # Generates coefficient matrix A and constant matrix C
# WALL BOUNDARY CONDITIONS ARE NOT IMPOSED IN THIS FUNCTION
a = I.a
b = I.b
c = I.c
A = np.zeros([a * b * c, a * b * c])
C = np.zeros([a * b * c, 1])
for index in range(0, np.size(C)):
i, j, k = find.find_equation_id(index)
# print("i j k",i,j,k)
i = int(i)
j = int(j)
k = int(k)
if (j != 0 and j != b - 1 and k != 0
and k != c - 1): # except boundary walls
if (np.mod(j, 4) == 1 and np.mod(k, 2) == 1): # Hot channel
# print("Hot channel")
# print("Node of balance",i,j,k)
# print(index)
C11 = 1 / (Rwy + Rc(Tg[i, j, k], Pg[i, j, k], i, j, k))
C12 = 1 / (Rwy + Rc(Tg[i, j, k], Pg[i, j, k], i, j, k))
C21 = 1 / (Rwz + Rc(Tg[i, j, k], Pg[i, j, k], i, j, k))
C22 = 1 / (Rwz + Rc(Tg[i, j, k], Pg[i, j, k], i, j, k))
C01 = -C11 - C21 + I.m_channel * find.Cp(
Tg[i, j, k], Pg[i, j, k], i, j, k)
C02 = -C11 - C21 - I.m_channel * find.Cp(
Tg[i, j, k], Pg[i, j, k], i, j, k)
A[index, find.find_index(i, j - 1, k)] = C11 # Tg j-1 term
A[index, find.find_index(i, j + 1, k)] = C12 # Tg j+1 term
A[index, find.find_index(i, j, k - 1)] = C21 # Tg k-1 term
A[index, find.find_index(i, j, k + 1)] = C22 # Tg k+1 term
if (i == 0): # Ti term is hot in BC
C[index, 0] = -I.T_hot_in * C01 # BC = Thot in
A[index,
find.find_index(i + 1, j, k)] = C02 # Tyz i+1 term
else: # interior
A[index, find.find_index(i, j, k)] = C01 #Tyz i term
A[index,
find.find_index(i + 1, j, k)] = C02 # Tyz i+1 term
#end of Hot channel
#############################################################################################
#Cold Channel
if (np.mod(j, 4) == 3 and np.mod(k, 2) == 1): # Cold channel
C11 = 1 / (Rwy + Rc(Tg[i, j, k], Pg[i, j, k], i, j, k))
C12 = 1 / (Rwy + Rc(Tg[i, j, k], Pg[i, j, k], i, j, k))
C21 = 1 / (Rwz + Rc(Tg[i, j, k], Pg[i, j, k], i, j, k))
C22 = 1 / (Rwz + Rc(Tg[i, j, k], Pg[i, j, k], i, j, k))
C01 = -C11 - C21 - I.m_channel * find.Cp(
Tg[i, j, k], Pg[i, j, k], i, j, k)
C02 = -C11 - C21 + I.m_channel * find.Cp(
Tg[i, j, k], Pg[i, j, k], i, j, k)
A[index, find.find_index(i, j - 1, k)] = C11 # Tg j-1 term
A[index, find.find_index(i, j + 1, k)] = C12 # Tg j+1 term
A[index, find.find_index(i, j, k - 1)] = C21 # Tg k-1 term
A[index, find.find_index(i, j, k + 1)] = C22 # Tg k+1 term
if (i == a - 1): # Ti-1 term is adjusted - Cold outlet
A[index, find.find_index(i, j, k)] = C01 #Tyz i term
C[index,
0] = -I.T_cold_in * C02 #Cold in BC-> Tyz i+1 term
else: # interior
A[index, find.find_index(i, j, k)] = C01 #Tyz i term
A[index,
find.find_index(i + 1, j, k)] = C02 # Tyz i+1 term
#end of cold channel
#############################################################################################
#Wall nodes
if (np.mod(j, 2) == 0 and np.mod(k, 2) == 1): # Type 1 Solid node
C01 = 1 / (2 * Rwx)
C02 = 1 / (2 * Rwx)
C11 = 0.5 / (Rwy +
Rc(Tg[i, j - 1, k], Pg[i, j - 1, k], i, j - 1, k))
C12 = 0.5 / (Rwy +
Rc(Tg[i, j + 1, k], Pg[i, j + 1, k], i, j + 1, k))
C21 = 1 / (2 * Rwz)
C22 = 1 / (2 * Rwz)
if (i == 0): # Hot in BC
if (
np.mod(j + 1, 4) == 1
): # hot channet at j+1 and cold at j-1 Hot in BC at i,j+1
C0 = -C02 - 2 * C11 - 2 * C12 - C21 - C22
A[index, find.find_index(i, j, k)] = C0 #i,j,k
A[index, find.find_index(i + 1, j, k)] = C02 #i+1,j,k
A[index, find.find_index(i, j, k - 1)] = C21 #i,j,k-1
A[index, find.find_index(i, j, k + 1)] = C22 #i,j,k+1
A[index, find.find_index(i, j - 1, k)] = C11 #i,j-1,k
A[index, find.find_index(i + 1, j - 1, k)] = C11
A[index, find.find_index(i + 1, j + 1, k)] = C12
C[index, 0] = -I.T_hot_in * C12
elif (np.mod(
j - 1,
4) == 1): # Hot channel at j-1 Hot in BC at i,j-1
C0 = -C02 - 2 * C11 - 2 * C12 - C21 - C22
A[index, find.find_index(i, j, k)] = C0
A[index, find.find_index(i + 1, j, k)] = C02
A[index, find.find_index(i, j, k - 1)] = C21
A[index, find.find_index(i, j, k + 1)] = C22
A[index, find.find_index(i + 1, j - 1, k)] = C11
A[index, find.find_index(i, j + 1, k)] = C12
A[index, find.find_index(i + 1, j + 1, k)] = C12
C[index, 0] = -I.T_hot_in * C11
elif (i == a - 1): # Cold in BC
if (
np.mod(j + 1, 4) == 1
): # hot channet at j+1 and cold at j-1 Cold in BC at i+1,j-1
C0 = -C02 - 2 * C11 - 2 * C12 - C21 - C22
A[index, find.find_index(i, j, k)] = C0
A[index, find.find_index(i - 1, j, k)] = C01
A[index, find.find_index(i, j, k - 1)] = C21
A[index, find.find_index(i, j, k + 1)] = C22
A[index, find.find_index(i, j + 1, k)] = C12
A[index, find.find_index(i + 1, j + 1, k)] = C12
A[index, find.find_index(i, j - 1, k)] = C11
C[index, 0] = -I.T_cold_in * C11
elif (np.mod(j - 1, 4) == 1
): # Hot channel at j-1 Cold in BC at i+1,j+1
C0 = -C02 - 2 * C11 - 2 * C12 - C21 - C22
A[index, find.find_index(i, j, k)] = C0
A[index, find.find_index(i - 1, j, k)] = C01
A[index, find.find_index(i, j, k - 1)] = C21
A[index, find.find_index(i, j, k + 1)] = C22
A[index, find.find_index(i, j + 1, k)] = C12
A[index, find.find_index(i, j - 1, k)] = C11
A[index, find.find_index(i + 1, j - 1, k)] = C11
C[index, 0] = -I.T_cold_in * C12
else:
C0 = -C02 - C01 - 2 * C11 - 2 * C12 - C21 - C22
A[index, find.find_index(i, j, k)] = C0
A[index, find.find_index(i - 1, j, k)] = C01
A[index, find.find_index(i + 1, j, k)] = C02
A[index, find.find_index(i, j, k - 1)] = C21
A[index, find.find_index(i, j, k + 1)] = C22
A[index, find.find_index(i, j + 1, k)] = C12
A[index, find.find_index(i + 1, j + 1, k)] = C12
A[index, find.find_index(i, j - 1, k)] = C11
A[index, find.find_index(i + 1, j - 1, k)] = C11
if (np.mod(j, 2) == 0 and np.mod(k, 2) == 0): # Type 2 Solid node
C01 = 1 / (2 * Rwx)
C02 = 1 / (2 * Rwx)
C11 = 1 / (2 * Rwy)
C12 = 1 / (2 * Rwy)
C21 = 1 / (2 * Rwz)
C22 = 1 / (2 * Rwz)
if (i == 0):
C0 = -C02 - C11 - C12 - C21 - C22
A[index, find.find_index(i, j, k)] = C0
A[index, find.find_index(i + 1, j, k)] = C02
A[index, find.find_index(i, j, k - 1)] = C21
A[index, find.find_index(i, j, k + 1)] = C22
A[index, find.find_index(i, j + 1, k)] = C12
A[index, find.find_index(i, j - 1, k)] = C11
elif (i == a - 1):
C0 = -C01 - C11 - C12 - C21 - C22
A[index, find.find_index(i, j, k)] = C0
A[index, find.find_index(i - 1, j, k)] = C01
A[index, find.find_index(i, j, k - 1)] = C21
A[index, find.find_index(i, j, k + 1)] = C22
A[index, find.find_index(i, j + 1, k)] = C12
A[index, find.find_index(i, j - 1, k)] = C11
else:
C0 = -C01 - C02 - C11 - C12 - C21 - C22
A[index, find.find_index(i, j, k)] = C0
A[index, find.find_index(i - 1, j, k)] = C01
A[index, find.find_index(i + 1, j, k)] = C02
A[index, find.find_index(i, j, k - 1)] = C21
A[index, find.find_index(i, j, k + 1)] = C22
A[index, find.find_index(i, j + 1, k)] = C12
A[index, find.find_index(i, j - 1, k)] = C11
if (np.mod(j, 2) == 1 and np.mod(k, 2) == 0): # Type 3 Solid node
C01 = 1 / (2 * Rwx)
C02 = 1 / (2 * Rwx)
C11 = 1 / (2 * Rwy)
C12 = 1 / (2 * Rwy)
C21 = 0.5 / (Rwz +
Rc(Tg[i, j, k - 1], Pg[i, j, k - 1], i, j, k - 1))
C22 = 0.5 / (Rwz +
Rc(Tg[i, j, k + 1], Pg[i, j, k + 1], i, j, k + 1))
if (i == 0): # Hot in BC
if (
np.mod(j, 4) == 1
): # hot channel at j and cold at j-1, j+1-> Hot in BC at i,k-1 k+1
C0 = -C02 - C11 - C12 - 2 * C21 - 2 * C22
A[index, find.find_index(i, j, k)] = C0 #i,j,k
A[index, find.find_index(i + 1, j, k)] = C02 #i+1,j,k
A[index, find.find_index(i, j - 1, k)] = C11 #i,j-1,k
A[index, find.find_index(i, j + 1, k)] = C12 #i,j+1,k
A[index,
find.find_index(i + 1, j, k - 1)] = C21 #i+1,j,k-1
A[index,
find.find_index(i + 1, j, k + 1)] = C22 #i+1,j,k+1
C[index, 0] = -I.T_hot_in * (C21 + C22)
elif (np.mod(
j,
4) == 3): # Cold channet at j and hot at j-1, j+1
C0 = -C02 - C11 - C12 - 2 * C21 - 2 * C22
A[index, find.find_index(i, j, k)] = C0 #i,j,k
A[index, find.find_index(i + 1, j, k)] = C02 #i+1,j,k
A[index, find.find_index(i, j - 1, k)] = C11 #i,j-1,k
A[index, find.find_index(i, j + 1, k)] = C12 #i,j+1,k
A[index, find.find_index(i + 1, j, k -
1)] = C21 #Tyz i+1,j,k-1
A[index, find.find_index(i + 1, j, k +
1)] = C22 #Tyz i+1,j,k+1
A[index,
find.find_index(i, j, k - 1)] = C21 #Tyz i,j,k-1
A[index,
find.find_index(i, j, k + 1)] = C22 #Tyz i+,j,k+1
elif (i == a - 1): # Cold in BC
if (np.mod(j, 4) == 1): # hot channet at j
C0 = -C01 - C11 - C12 - 2 * C21 - 2 * C22
A[index, find.find_index(i, j, k)] = C0 #ijk
A[index, find.find_index(i - 1, j, k)] = C01 #i-1,j,k
A[index, find.find_index(i, j - 1, k)] = C11 #i,j-1,k
A[index, find.find_index(i, j + 1, k)] = C12 #i,j+1,k
A[index, find.find_index(i, j, k - 1)] = C21 #i,j,k-1
A[index, find.find_index(i, j, k + 1)] = C22 #i,j,k+1
A[index,
find.find_index(i + 1, j, k - 1)] = C21 #i+1,j,k-1
A[index,
find.find_index(i + 1, j, k + 1)] = C22 #i+1,j,k+1
elif (np.mod(j, 4) == 3
): # Cold channel at j Cold in BC at i+1,k-1,+1
C0 = -C01 - C11 - C12 - 2 * C21 - 2 * C22
A[index, find.find_index(i, j, k)] = C0
A[index, find.find_index(i - 1, j, k)] = C01
A[index, find.find_index(i, j + 1, k)] = C12
A[index, find.find_index(i, j - 1, k)] = C11
A[index, find.find_index(i, j, k - 1)] = C21
A[index, find.find_index(i, j, k + 1)] = C22
C[index, 0] = -I.T_cold_in * (C21 + C22)
else:
C0 = -C02 - C01 - C11 - C12 - 2 * C21 - 2 * C22
A[index, find.find_index(i, j, k)] = C0
A[index, find.find_index(i - 1, j, k)] = C01
A[index, find.find_index(i + 1, j, k)] = C02
A[index, find.find_index(i, j, k - 1)] = C21
A[index, find.find_index(i, j, k + 1)] = C22
A[index, find.find_index(i + 1, j, k + 1)] = C22
A[index, find.find_index(i + 1, j, k - 1)] = C21
A[index, find.find_index(i, j + 1, k)] = C12
A[index, find.find_index(i, j - 1, k)] = C11
A, C = BC.adiabatic_wall_BC(A, C, Rwx, Rwy, Rwz, Tg, Tyz, Pg, P)
return (A, C)
nd=nd,
VF_model=1,
LS_model=LS_model,
Closure_0_model=Closure_0_model,
Closure_1_model=Closure_1_model,
epsFact_density=epsFact_density,
stokes=False,
useVF=useVF,
useRBLES=useRBLES,
useMetrics=useMetrics,
eb_adjoint_sigma=1.0,
forceStrongDirichlet=ns_forceStrongDirichlet,
turbulenceClosureModel=ns_closure)
setBC = BC.boundaryConditions()
def getDBC_p(x,flag):
BCType = "pDirichlet"
if flag == boundaryTags['top']:
return outflowPressure
if flag == boundaryTags['left']:
return None
if flag == boundaryTags['right']:
return outflowPressure
if flag == boundaryTags['bottom']:
return setBC.freeSlip(BCType)
def getDBC_u(x,flag):
BCType = "uDirichlet"
def parse_fastq_by_multitag(directory, f_gzipped_fastqfile, r_gzipped_fastqfile,
q = "fastq",
f_seqtag_length = 8,
r_seqtag_length = 8,
f_multitag_length = 6,
r_multitag_length = 6,
f_lintag_length = 38,
r_lintag_length = 38,
f_spacer_length = 43, #distance to first barcode in forward read (ignoring the length the thie multitag and the seqtag)
r_spacer_length = 29, #distance second barcode in reverse read (ignoring the length the thie multitag and the seqtag)
min_qs = 30, #the minimum avareage quality score for both lineage tags
lintag_grep_filter1 ='\D*?(.ACC|T.CC|TA.C|TAC.)\D{4,7}?AA\D{4,7}?AA\D{4,7}?TT\D{4,7}?(.TAA|A.AA|AT.A|ATA.)\D*', #first barcode
lintag_grep_filter2 ='\D*?(.ACC|T.CC|TA.C|TAC.)\D{4,7}?AA\D{4,7}?TT\D{4,7}?TT\D{4,7}?(.TAA|A.AA|AT.A|ATA.)\D*', #second barcode
clip_ends = 1, #logical of whether or not to clip the front and back ends off of lintag1 and lintag2
lintag1_front_clipper = '(.ACC|T.CC|TA.C|TAC.)', #only report lintag1 after this sequence
lintag2_front_clipper = '(.ACC|T.CC|TA.C|TAC.)', #only report lintag2 after this sequence
lintag1_rear_clipper = '(.TAA|A.AA|AT.A|ATA.)', #only report lintag1 before this sequence, this must be the COMPLIMENT of the true sequence
lintag2_rear_clipper = '(.TAA|A.AA|AT.A|ATA.)', #only report lintag2 before this sequence, this must be the COMPLIMENT of the true sequence
multitags = ["TAGCTTGCGTAC", "CGATGTGAGACG"], #concatenated multiplexing tags from the first and second reads that uniquely identify a sample, currently must have 2 or more multitags
write_multitags = False): #write multitags to file
"""
Parses a F and R gzipped FastQ files and saves the UMIs, multiplexing tags, and barcodes
Removes reeads where the mean quality score for each lineage tag is not greater than min_qs
Removes reeads where both lineage tags do not match the regular expression
"""
from Bio import SeqIO
import os
import gzip
import numpy
import BC
import re
from itertools import izip
os.chdir(directory)
print("Loading " + f_gzipped_fastqfile + " and " + r_gzipped_fastqfile + " and parsing")
print( "Saving the combined forward and reverse sequencing tags as seqtag.txt")
print( "Saving the combined forward and reverse multiplexing tags as multitag.txt")
print( "Saving the first lineage tag as lintag1.txt")
print( "Saving the first lineage tag as lintag2.txt")
#assign boundries
f_boundries = (0, f_seqtag_length , f_multitag_length + f_seqtag_length,
f_multitag_length + f_seqtag_length + f_spacer_length,
f_multitag_length + f_seqtag_length + f_spacer_length + f_lintag_length)
r_boundries = (0, r_seqtag_length , r_multitag_length + r_seqtag_length,
r_multitag_length + r_seqtag_length + r_spacer_length,
r_multitag_length + r_seqtag_length + r_spacer_length + r_lintag_length)
#open files for writing
#reads that sort to a multiplexing tag
for i in multitags:
vars()[i+'_seqtag'] = open(directory + i + '_seqtag.txt', 'w')
vars()[i+'_lintag1'] = open(directory + i + '_lintag1.txt', 'w')
vars()[i+'_lintag2'] = open(directory + i + '_lintag2.txt', 'w')
if write_multitags: vars()[i+'_multitag'] = open(directory + i + '_multitag.txt', 'w')
#reads that do not sort to a multiplexing tag
unmatched_seqtag = open(directory + 'unmatched_seqtag.txt', 'w')
unmatched_lintag1 = open(directory + 'unmatched_lintag1.txt', 'w')
unmatched_lintag2 = open(directory + 'unmatched_lintag2.txt', 'w')
unmatched_multitag = open(directory + 'unmatched_multitag.txt', 'w')
#open files for reading by SeqIO
f_file = SeqIO.parse(gzip.open(directory + f_gzipped_fastqfile, "rU"), q)
r_file = SeqIO.parse(gzip.open(directory + r_gzipped_fastqfile, "rU"), q)
#eliminate low quality reads and reads that don't pass a quality filter, optionally clip off ends of lintags
# sort by multiplexing tags
quality_reads = 0
total_reads = 0
for f, r in izip(f_file, r_file):
fq = f.letter_annotations["phred_quality"]
rq = r.letter_annotations["phred_quality"]
total_reads = total_reads + 1
if numpy.mean(fq[f_boundries[3]:f_boundries[4]]) > min_qs and numpy.mean(rq[r_boundries[3]:r_boundries[4]]) > min_qs:
#checks that the quality scores of forward and reverse lintags are OK
#print "quality ok"
fr = str(f.seq)
#print fr
rr = str(r.seq)
#print rr
if BC.grep(fr[f_boundries[3]:f_boundries[4]], lintag_grep_filter1) and BC.grep(rr[r_boundries[3]:r_boundries[4]], lintag_grep_filter2):
#checks the both lineage tags meet the regular expression filter
#print "grep ok"
quality_reads = quality_reads + 1 #these are reads where both lintags pass the quality and grep filters
#next, find the closest matching multitag
m = fr[f_boundries[1]:f_boundries[2]] + rr[r_boundries[1]:r_boundries[2]] #the concatintated multiplexing tag
#print m
j = BC.best_match(m, multitags, MAX = (f_multitag_length + r_multitag_length + 1)/3) #best matched multiplexing tag
#print j
if j > -1:
tm = BC.mismatches(m, multitags[j]) #distance to this tag
else:
tm = 1000
if tm < (f_multitag_length + r_multitag_length + 1)/4: #A multitag match has been found
ftag = fr[f_boundries[3]:f_boundries[4]]
rtag = rr[r_boundries[3]:r_boundries[4]]
if(clip_ends):
fstart = re.search(lintag1_front_clipper, ftag).span()[1]
fend = re.search(lintag1_rear_clipper, ftag[::-1]).span()[1]*-1
if fend == 0: fend = len(ftag)
ftag = ftag[fstart:fend]
rstart = re.search(lintag2_front_clipper, rtag).span()[1]
rend = re.search(lintag2_rear_clipper, rtag[::-1]).span()[1]*-1
if rend == 0: rend = len(rtag)
rtag = rtag[rstart:rend]
vars()[multitags[j]+'_lintag1'].write(ftag + '\n')
vars()[multitags[j]+'_lintag2'].write(rtag + '\n')
vars()[multitags[j]+'_seqtag'].write(fr[f_boundries[0]:f_boundries[1]] + rr[r_boundries[0]:r_boundries[1]] + '\n')
if write_multitags: vars()[multitags[j]+'_multitag'].write(fr[f_boundries[1]:f_boundries[2]] + rr[r_boundries[1]:r_boundries[2]] + '\n')
#if (len(fr[f_boundries[1]:f_boundries[2]] + rr[r_boundries[1]:r_boundries[2]]) < 12
#or len(fr[f_boundries[0]:f_boundries[1]] + rr[r_boundries[0]:r_boundries[1]]) < 16
#or len(ftag) < 20
#or len(rtag) < 20):
# print rea
# print "match to " + multitags[j]
# print "multitag = " + fr[f_boundries[1]:f_boundries[2]] + rr[r_boundries[1]:r_boundries[2]] + " " + str(len(fr[f_boundries[1]:f_boundries[2]] + rr[r_boundries[1]:r_boundries[2]]))
# print "seqtag = " + fr[f_boundries[0]:f_boundries[1]] + rr[r_boundries[0]:r_boundries[1]] + " " + str(len(fr[f_boundries[0]:f_boundries[1]] + rr[r_boundries[0]:r_boundries[1]]))
# print "lintag1 = " + ftag + " " + str(len(ftag))
# print "lintag2 = " + rtag + " " + str(len(rtag))
# break
else:
ftag = fr[f_boundries[3]:f_boundries[4]]
rtag = rr[r_boundries[3]:r_boundries[4]]
if(clip_ends):
fstart = re.search(lintag1_front_clipper, ftag).span()[1]
fend = re.search(lintag1_rear_clipper, ftag[::-1]).span()[1]*-1
if fend == 0: fend = len(ftag)
ftag = ftag[fstart:fend]
rstart = re.search(lintag2_front_clipper, rtag).span()[1]
rend = re.search(lintag2_rear_clipper, rtag[::-1]).span()[1]*-1
if rend == 0: rend = len(rtag)
rtag = rtag[rstart:rend]
unmatched_lintag1.write(ftag + '\n')
unmatched_lintag2.write(rtag + '\n')
unmatched_seqtag.write(fr[f_boundries[0]:f_boundries[1]] + rr[r_boundries[0]:r_boundries[1]] +'\n')
unmatched_multitag.write(fr[f_boundries[1]:f_boundries[2]] + rr[r_boundries[1]:r_boundries[2]] +'\n')
#if (len(fr[f_boundries[1]:f_boundries[2]] + rr[r_boundries[1]:r_boundries[2]]) < 12
#or len(fr[f_boundries[0]:f_boundries[1]] + rr[r_boundries[0]:r_boundries[1]]) < 16
#or len(ftag) < 20
#or len(rtag) < 20):
# print rea
# print "match to " + multitags[j]
# print "multitag = " + fr[f_boundries[1]:f_boundries[2]] + rr[r_boundries[1]:r_boundries[2]] + " " + str(len(fr[f_boundries[1]:f_boundries[2]] + rr[r_boundries[1]:r_boundries[2]]))
# print "seqtag = " + fr[f_boundries[0]:f_boundries[1]] + rr[r_boundries[0]:r_boundries[1]] + " " + str(len(fr[f_boundries[0]:f_boundries[1]] + rr[r_boundries[0]:r_boundries[1]]))
# print "lintag1 = " + ftag + " " + str(len(ftag))
# print "lintag2 = " + rtag + " " + str(len(rtag))
# break
print ( str(quality_reads) + " out of " + str(total_reads) +" reads passed grep and quality filters")
for i in multitags:
vars()[str(i)+'_seqtag'].close()
vars()[str(i)+'_lintag1'].close()
vars()[str(i)+'_lintag2'].close()
if write_multitags: vars()[str(i)+'_multitag'].close()
unmatched_seqtag.close()
unmatched_lintag1.close()
unmatched_lintag2.close()
unmatched_multitag.close()
f_file.close()
r_file.close()
def parse_fastq(directory, f_gzipped_fastqfile, r_gzipped_fastqfile,
q = "fastq", #the type of fastq file coming off of the sequencer
f_seqtag_length = 8, #the length of the sequencing tag on the first read (UMI1)
r_seqtag_length = 8, #the length of the sequencing tag on the second read (UMI2)
f_multitag_length = 6, #the length of the multiplexing tag on the first read
r_multitag_length = 6, #the length of the multiplexing tag on the second read
f_lintag_length = 38, #the length of the lineage tag on the first read (first barcode)
r_lintag_length = 38, #the length of the lineage tag on the second read (second barcode)
f_spacer_length = 43, #distance to first barcode in forward read (ignoring the length the thie multitag and the seqtag)
r_spacer_length = 29, #distance second barcode in reverse read (ignoring the length the thie multitag and the seqtag)
min_qs = 30, #the minimum avareage quality score for both lineage tags
lintag_grep_filter1 ='\D*?(.ACC|T.CC|TA.C|TAC.)\D{4,7}?AA\D{4,7}?AA\D{4,7}?TT\D{4,7}?(.TAA|A.AA|AT.A|ATA.)\D*', #first barcode
lintag_grep_filter2 ='\D*?(.ACC|T.CC|TA.C|TAC.)\D{4,7}?AA\D{4,7}?TT\D{4,7}?TT\D{4,7}?(.TAA|A.AA|AT.A|ATA.)\D*', #second barcode
clip_ends = 1, #logical of whether or not to clip the front and back ends off of lintag1 and lintag2
lintag1_front_clipper = '(.ACC|T.CC|TA.C|TAC.)', #only report lintag1 after this sequence
lintag2_front_clipper = '(.ACC|T.CC|TA.C|TAC.)', #only report lintag2 after this sequence
lintag1_rear_clipper = '(.ATA|A.TA|AA.A|AAT.)', #only report lintag1 before this sequence, this must be the COMPLIMENT of the true sequence
lintag2_rear_clipper = '(.ATA|A.TA|AA.A|AAT.)'):#only report lintag1 before this sequence, this must be the COMPLIMENT of the true sequence
"""
Parses a F and R gzipped FastQ files and saves the UMIs, multiplexing tags, and barcodes
Removes reeads where the mean quality score for each lineage tag is not greater than min_qs
Removes reeads where both lineage tags do not match the regular expression
"""
from Bio import SeqIO
import os
import gzip
import numpy
import BC
import re
from itertools import izip
os.chdir(directory)
print("Loading " + f_gzipped_fastqfile + " and " + r_gzipped_fastqfile + " and parsing")
print( "Saving the combined forward and reverse sequencing tags as seqtag.txt")
print( "Saving the combined forward and reverse multiplexing tags as multitag.txt")
print( "Saving the first lineage tag as lintag1.txt")
print( "Saving the first lineage tag as lintag2.txt")
#assign boundries
f_boundries = (0, f_seqtag_length , f_multitag_length + f_seqtag_length,
f_multitag_length + f_seqtag_length + f_spacer_length,
f_multitag_length + f_seqtag_length + f_spacer_length + f_lintag_length)
r_boundries = (0, r_seqtag_length , r_multitag_length + r_seqtag_length,
r_multitag_length + r_seqtag_length + r_spacer_length,
r_multitag_length + r_seqtag_length + r_spacer_length + r_lintag_length)
#open files for writing
seqtag = open(directory + '_seqtag.txt', 'w')
multitag = open(directory + '_multitag.txt', 'w')
lintag1 = open(directory + '_lintag1.txt', 'w')
lintag2 = open(directory + '_lintag2.txt', 'w')
#open files for reading by SeqIO
f_file = SeqIO.parse(gzip.open(directory + f_gzipped_fastqfile, "rU"), q)
r_file = SeqIO.parse(gzip.open(directory + r_gzipped_fastqfile, "rU"), q)
#eliminate low quality reads and reads that don't pass a quality filter, optionally clip off ends of lintags
quality_reads = 0
total_reads = 0
for f, r in izip(f_file, r_file):
fq = f.letter_annotations["phred_quality"]
rq = r.letter_annotations["phred_quality"]
total_reads = total_reads + 1
if numpy.mean(fq[f_boundries[3]:f_boundries[4]]) > min_qs and numpy.mean(rq[r_boundries[3]:r_boundries[4]]) > min_qs: #checks that the quality scores of forward and reverse lintags are OK
fr = str(f.seq)
rr = str(r.seq)
if BC.grep(fr[f_boundries[3]:f_boundries[4]], lintag_grep_filter1) and BC.grep(rr[r_boundries[3]:r_boundries[4]], lintag_grep_filter2):
#checks the both lineage tags meet the regular expression filter
quality_reads = quality_reads + 1
seqtag.write(fr[f_boundries[0]:f_boundries[1]] + rr[r_boundries[0]:r_boundries[1]] +'\n')
multitag.write(fr[f_boundries[1]:f_boundries[2]] + rr[r_boundries[1]:r_boundries[2]] +'\n')
ftag = fr[f_boundries[3]:f_boundries[4]]
rtag = rr[r_boundries[3]:r_boundries[4]]
if (clip_ends):
fstart = re.search(lintag1_front_clipper, ftag).span()[1]
fend = re.search(lintag1_rear_clipper, ftag[::-1]).span()[1]*-1
if fend == 0: fend = len(ftag)
ftag = ftag[fstart:fend]
rstart = re.search(lintag2_front_clipper, rtag).span()[1]
rend = re.search(lintag2_rear_clipper, rtag[::-1]).span()[1]*-1
if rend == 0: rend = len(rtag)
rtag = rtag[rstart:rend]
lintag1.write(ftag + '\n')
lintag2.write(rtag + '\n')
print ( str(quality_reads) + " out of " + str(total_reads) +" reads passed grep and quality filters")
seqtag.close()
multitag.close()
lintag1.close()
lintag2.close()
f_file.close()
r_file.close()