def getGlobalString(signal):
signal = smoothSignal(signal, smoothParam)
signalShift, signalScale = computeNorm(signal, 0, len(signal))
signalString = computeString(signal,
0,
len(signal),
signalShift,
signalScale,
levels,
overflow=overflow)
return signalString
def getLevelStr(signal, l):
currSignal = np.array(copy.deepcopy(signal), float)
currSignal = smoothSignal(currSignal, smoothParam)
currSignalShift, currSignalScale = computeNorm(currSignal, 0,
len(currSignal))
currString = computeString(
currSignal,
0,
len(currSignal),
currSignalShift,
currSignalScale,
l,
overflow=overflow,
)
return currString
def getDictFromSequence(signal, refWindowSize, refWindowJump):
dic = {}
for winBeg in range(0, len(signal) - refWindowSize + 1, refWindowJump):
winEnd = winBeg + refWindowSize
currSignal = np.array(copy.deepcopy(signal[winBeg:winEnd]), float)
currSignal = smoothSignal(currSignal, smoothParam)
currSignalShift, currSignalScale = computeNorm(currSignal, 0,
refWindowSize)
currString = computeString(currSignal,
0,
refWindowSize,
currSignalShift,
currSignalScale,
levels,
overflow=overflow)
dic.update(buildDictionary(currString, kmerLength))
return dic
def getDictFromSequence(signal, l=False):
dic = {}
currSignal = np.array(copy.deepcopy(signal), float)
currSignal = smoothSignal(currSignal, smoothParam)
currSignalShift, currSignalScale = computeNorm(currSignal, 0,
len(currSignal))
currString = computeString(
currSignal,
0,
len(currSignal),
currSignalShift,
currSignalScale,
levels,
overflow=overflow,
)
if l == True:
return currString
return buildDictionarySpecial(currString, kmerLength)
stringToSignal(refSeq, mod, repeatSignal=repeatSignal), float)
readSignal = np.array(getSignalFromRead(posRead), dtype=float)
readSignal = readSignal[fromSignal:toSignal]
fakeSignal = []
fakeIndex = -1
while len(fakeSignal) <= toSignal:
fakeIndex = random.randint(0, len(negReadsPaths) - 1)
fakeSignal = np.array(getSignalFromRead(negReadsPaths[fakeIndex]),
dtype=float)
fakeSignal = fakeSignal[fromSignal:toSignal]
readSignal = readSignal[:workingLen]
refSignal = refSignal[:workingLen]
fakeSignal = fakeSignal[:workingLen]
readSignal = smoothSignal(readSignal, smoothParam)
refSignal = smoothSignal(refSignal, smoothParam)
fakeSignal = smoothSignal(fakeSignal, smoothParam)
readShift, readScale = computeNorm(readSignal, 0, len(readSignal))
refShift, refScale = computeNorm(refSignal, 0, len(refSignal))
fakeShift, fakeScale = computeNorm(fakeSignal, 0, len(fakeSignal))
readStrings, refStrings, fakeStrings = {}, {}, {}
for l in levels:
readStrings[l] = computeString(
readSignal,
0,
len(readSignal),
readShift,
readScale,
x.append(" ")
y.append(originalSignal[i])
#plt.plot(y)
#plt.xticks(y_pos, x, color='orange', rotation=45, fontweight='bold', horizontalalignment='right')
#plt.tick_params(labelbottom='off')
refSignal = stringToSignal(refSeq, mod, repeatSignal=repeatSignal)
refSeqHelper = []
for i in refSeq:
refSeqHelper.append(i)
for k in range(repeatSignal - 1):
refSeqHelper.append("_")
y = smoothSignal(y, 5)
refSignal = smoothSignal(refSignal, 5)
ySignalShift, ySignalScale = computeNorm(y, 0, len(y))
#y -= ySignalShift
#y /= ySignalScale
refSignalShift, refSignalScale = computeNorm(refSignal, 0, len(refSignal))
#refSignal -= refSignalShift
#refSignal /= refSignalScale
readString = computeString(y,
0,
len(y),
ySignalShift,
ySignalScale,
readSignal = np.array(getSignalFromRead(readFile)[signalFrom:signalTo],
dtype=float)
refSignal = np.array(
stringToSignal(refSeq, mod, repeatSignal=repeatSignal), float)
# fakeSignal = np.array(stringToSignal(fakeSeq, mod, repeatSignal = repeatSignal),
# float)
fakeSignal = []
fakeIndex = -1
while len(fakeSignal) <= signalTo:
fakeIndex = random.randint(0, len(negReads) - 1)
fakeSignal = np.array(getSignalFromRead(negReads[fakeIndex]),
dtype=float)
fakeSignal = fakeSignal[signalFrom:signalTo]
readSignalSm = smoothSignal(readSignal, 5)
refSignalSm = smoothSignal(refSignal, 5)
fakeSignalSm = smoothSignal(fakeSignal, 5)
readShiftSm, readScaleSm = computeNorm(readSignalSm, 0, len(readSignalSm))
refShiftSm, refScaleSm = computeNorm(refSignalSm, 0, len(refSignalSm))
fakeShiftSm, fakeScaleSm = computeNorm(fakeSignalSm, 0, len(fakeSignalSm))
readString2Sm = computeString(
readSignalSm,
0,
len(readSignalSm),
readShiftSm,
readScaleSm,
levels,
overflow=0.25,
)
refString2Sm = computeString(refSignalSm,
readCounter += 1
if strand == 1:
refSeq = str(Fasta(refFilePath)[ctg][fromRef:toRef])
else:
refSeq = str(-Fasta(refFilePath)[ctg][fromRef:toRef])
refSignal = np.array(
stringToSignal(refSeq, mod, repeatSignal=repeatSignal), float)
readSignal = np.array(getSignalFromRead(posRead), dtype=float)
readSignal = readSignal[fromSignal:toSignal]
readSignal = readSignal[:workingLen]
refSignal = refSignal[:workingLen]
readSignalSm = smoothSignal(readSignal, smoothParam)
refSignalSm = smoothSignal(refSignal, smoothParam)
readShift, readScale = computeNorm(readSignal, 0, len(readSignal))
readShiftSm, readScaleSm = computeNorm(readSignalSm, 0, len(readSignalSm))
refShift, refScale = computeNorm(refSignal, 0, len(refSignal))
refShiftSm, refScaleSm = computeNorm(refSignalSm, 0, len(refSignalSm))
readStrings, readStringsSm, refStrings, refStringsSm = {}, {}, {}, {}
for l in levels:
readStrings[l] = computeString(
readSignal,
0,
len(readSignal),
readShift,
if aln.q_en - aln.q_st > 0.95 * len(readFastq)
and aln.strand == 1
and aln.ctg == workingContig
]
if len(hits) != 1:
continue
hit = hits[0]
refPosition = hit.r_st / len(ref[hit.ctg])
print(f"I am in ctg {hit.ctg} in around {refPosition}")
if hit.strand == 1:
refSeq = str(ref[hit.ctg][hit.r_st : hit.r_en])
refSignal = stringToSignal(refSeq, mod, repeatSignal)
refSignal = smoothSignal(refSignal, smoothParam)
#refShift, refScale = computeNorm(refSignal, 0, len(refSignal))
refShift, refScale = globalNorms[hit.ctg][0], globalNorms[hit.ctg][1]
refString = computeString(
refSignal, 0, len(refSignal), refShift, refScale, level, overflow=overflow,
)
refString = refString[5:-5]
readSignal = getSignalFromRead(sample)
readSignalLen = len(readSignal)
readSignal = readSignal[readSignalBeg:readSignalEnd]
readString = getLevelString(readSignal, smoothParam, level, overflow)
found = None
for i in range(len(storeContig[hit.ctg]) - len(refString) + 1):
w = storeContig[hit.ctg][i : i + len(refString)]
refSignal = stringToSignal(refSeq, mod, repeatSignal=repeatSignal) refSignal = np.array(refSignal, dtype=float) readSignal = np.array(readSignal, dtype=float) refSignal -= np.mean(refSignal) readSignal -= np.mean(readSignal) refSignal /= np.std(refSignal) readSignal /= np.std(readSignal) refSignal[refSignal > 2.0] = 2.0 readSignal[readSignal < -2.0] = -2.0 refSignalAvg = smoothSignal(refSignal, smoothParam) readSignalAvg = smoothSignal(readSignal, smoothParam) refSignalMed = smoothSignalMed(refSignal, smoothParam) readSignalMed = smoothSignalMed(readSignal, smoothParam) f, (ax1, ax2, ax3) = plt.subplots(3, 2) ax1[0].plot(range(len(refSignal)), refSignal) ax1[1].plot(range(len(readSignal)), readSignal) ax2[0].plot(range(len(refSignalAvg)), refSignalAvg) ax2[1].plot(range(len(readSignalAvg)), readSignalAvg) ax3[0].plot(range(len(refSignalMed)), refSignalMed) ax3[1].plot(range(len(readSignalMed)), readSignalMed) ax1[0].set_ylim(bottom=-2.2, top=2.2) ax1[1].set_ylim(bottom=-2.2, top=2.2)
from signalHelper import stringToSignal
from signalHelper import smoothSignal, computeNorm, computeString
ref = Fasta(refFilePath)
mod = KmerModel.load_from_hdf5(kmerModelFilePath)
for contig in ref:
refSeqPos = str(contig[:])
refSeqNeg = str(contig[:].complement)
refSignalPos = np.array(
stringToSignal(refSeqPos, mod, repeatSignal=repeatSignal), float)
refSignalNeg = np.array(
stringToSignal(refSeqNeg, mod, repeatSignal=repeatSignal), float)
refSignalPos = smoothSignal(refSignalPos, smoothParam)
refSignalNeg = smoothSignal(refSignalNeg, smoothParam)
refSignalPosShift, refSignalPosScale = computeNorm(refSignalPos, 0,
len(refSignalPos))
refSignalNegShift, refSignalNegScale = computeNorm(refSignalNeg, 0,
len(refSignalNeg))
for l in levels:
refStringPos = computeString(
refSignalPos,
0,
len(refSignalPos),
refSignalPosShift,
refSignalPosScale,
l,
