def dinuclShuffle(s, alph=alphabet.dna()):
# check we can actually shuffle it
if len(s) <= 2:
return s
# determine how to end the sequence
edgeList = eulerian(s, alph)
# turn the sequence into lists of following symbols
symIList = computeList(s, alph)
# remove last edges from each vertex list, shuffle, then add back
# the removed edges at end of vertex lists.
for [x, y] in edgeList:
symIList[x].remove(y)
for x in range(len(symIList)):
random.shuffle(symIList[x])
for [x, y] in edgeList:
symIList[x].append(y)
#construct the eulerian path
prevSymI = alph.getIndex(s[0])
L = [alph.getSymbol(prevSymI)]
for i in range(len(s) - 2):
symI = symIList[prevSymI].pop(0)
L.append(alph.getSymbol(symI))
prevSymI = symI
symI = alph.getIndex(s[-1])
L.append(alph.getSymbol(symI))
return "".join(L)
def dinuclShuffle(s, alph = alphabet.dna()):
# check we can actually shuffle it
if len(s) <= 2:
return s
# determine how to end the sequence
edgeList = eulerian(s, alph)
# turn the sequence into lists of following symbols
symIList = computeList(s, alph)
# remove last edges from each vertex list, shuffle, then add back
# the removed edges at end of vertex lists.
for [x,y] in edgeList:
symIList[x].remove(y)
for x in range(len(symIList)):
random.shuffle(symIList[x])
for [x,y] in edgeList:
symIList[x].append(y)
#construct the eulerian path
prevSymI = alph.getIndex(s[0])
L = [alph.getSymbol(prevSymI)]
for i in range(len(s)-2):
symI = symIList[prevSymI].pop(0)
L.append(alph.getSymbol(symI))
prevSymI = symI
symI = alph.getIndex(s[-1])
L.append(alph.getSymbol(symI))
return "".join(L)
def main():
pos_seq_file_name = None # no positive sequence file specified
neg_seq_file_name = None # no negative sequence file specified
alphabet_file_name = None
refine = False
given_only = False
#
# get command line arguments
#
usage = """USAGE:
%s [options]
-w <word> word (required)
-p <file_name> positive sequences FASTA file name (required)
-n <file_name> negative sequences FASTA file name (required)
-a <file_name> alphabet definition file
-r refine consensus by branching search
(distance 1 steps; beam size = 1).
-h print this usage message
Compute the Hamming distance from <word> to each FASTA sequence
in the positive and negative files. Apply Fisher's Exact test to
each distance.
<word> may contain ambiguous characters.
""" % (sys.argv[0])
# no arguments: print usage
if len(sys.argv) == 1:
print(usage, file=sys.stderr)
sys.exit(1)
# parse command line
i = 1
while i < len(sys.argv):
arg = sys.argv[i]
if (arg == "-w"):
i += 1
try:
word = sys.argv[i]
except:
print(usage, file=sys.stderr)
sys.exit(1)
elif (arg == "-p"):
i += 1
try:
pos_seq_file_name = sys.argv[i]
except:
print(usage, file=sys.stderr)
sys.exit(1)
elif (arg == "-n"):
i += 1
try:
neg_seq_file_name = sys.argv[i]
except:
print(usage, file=sys.stderr)
sys.exit(1)
elif (arg == "-a"):
i += 1
try:
alphabet_file_name = sys.argv[i]
except:
print(usage, file=sys.stderr)
sys.exit(1)
elif (arg == "-r"):
try:
refine = True
except:
print(usage, file=sys.stderr)
sys.exit(1)
elif (arg == "-h"):
print(usage, file=sys.stderr)
sys.exit(1)
else:
print(usage, file=sys.stderr)
sys.exit(1)
i += 1
# check that required arguments given
if (pos_seq_file_name == None or neg_seq_file_name == None):
print(usage, file=sys.stderr)
sys.exit(1)
# keep track of time
start_time = time.time()
# read alphabet
alph = None
if alphabet_file_name != None:
alph = alphabet.loadFromFile(alphabet_file_name)
else:
alph = alphabet.dna()
# read sequences
print("Reading sequences...", file=sys.stderr)
pos_seqs = get_strings_from_seqs(
sequence.readFASTA(pos_seq_file_name, alph))
neg_seqs = get_strings_from_seqs(
sequence.readFASTA(neg_seq_file_name, alph))
#print >> sys.stderr, "Computing Hamming enrichment..."
#(dist, log_pvalue, p, P, n, N, aln) = get_best_hamming_alignment(word, pos_seqs, neg_seqs, alph, given_only)
if refine:
(best_word,
best_log_pvalue) = refine_consensus(word, pos_seqs, neg_seqs, alph,
given_only)
else:
best_word = word
print("Computing Hamming alignment...", file=sys.stderr)
(dist, log_pvalue, p, P, n, N,
aln) = get_best_hamming_alignment(best_word, pos_seqs, neg_seqs, alph,
given_only)
pv_string = sprint_logx(log_pvalue, 1, _pv_format)
nsites = len(aln)
print("[", p, P, n, N, dist, "]", file=sys.stderr)
print(
"Best ZOOPs alignment has %d sites / %d at distance %d with p-value %s"
% (nsites, P, dist, pv_string),
file=sys.stderr)
print_meme_header(alph)
print_meme_motif(best_word, nsites, pv_string, aln, alph)
# print elapsed time
end_time = time.time()
elapsed = end_time - start_time
print("elapsed time: %.2f seconds" % elapsed, file=sys.stderr)
print("#elapsed time: %.2f seconds" % elapsed, file=sys.stdout)
def main():
#
# defaults
#
file_name = None
alphabet_file_name = None
seed = 1
copies = 1
#
# get command line arguments
#
usage = """USAGE:
%s [options]
-f <filename> file name (required)
-t <tag> added to shuffled sequence names
-s <seed> random seed; default: %d
-c <n> make <n> shuffled copies of each sequence; default: %d
-a <filename> alphabet file to use non-DNA alphabets
-h print this usage message
Note that fasta-shuffle-letters also supports dinucleotide shuffling and is faster.
""" % (sys.argv[0], seed, copies)
# no arguments: print usage
if len(sys.argv) == 1:
print(usage, file=sys.stderr)
sys.exit(1)
tag = ""
# parse command line
i = 1
while i < len(sys.argv):
arg = sys.argv[i]
if (arg == "-f"):
i += 1
try:
file_name = sys.argv[i]
except:
print(usage, file=sys.stderr)
sys.exit(1)
elif (arg == "-t"):
i += 1
try:
tag = sys.argv[i]
except:
print(usage, file=sys.stderr)
sys.exit(1)
elif (arg == "-s"):
i += 1
try:
seed = int(sys.argv[i])
except:
print(usage, file=sys.stderr)
sys.exit(1)
elif (arg == "-c"):
i += 1
try:
copies = int(sys.argv[i])
except:
print(usage, file=sys.stderr)
sys.exit(1)
elif (arg == "-a"):
i += 1
try:
alphabet_file_name = sys.argv[i]
except:
print(usage, file=sys.stderr)
sys.exit(1)
elif (arg == "-h"):
print(usage, file=sys.stderr)
sys.exit(1)
else:
print("Unknown command line argument: " + arg, file=sys.stderr)
sys.exit(1)
i += 1
# check that required arguments given
if (file_name == None):
print(usage, file=sys.stderr)
sys.exit(1)
# get the alphabet, defaulting to DNA if it is not provided
if alphabet_file_name != None:
alph = alphabet.loadFromFile(alphabet_file_name)
else:
alph = alphabet.dna()
random.seed(seed)
# read sequences
seqs = sequence.readFASTA(file_name, alph)
for s in seqs:
seq = s.getString()
name = s.getName()
for i in range(copies):
shuffledSeq = dinuclShuffle(seq, alph)
if (copies == 1):
print(">%s\n%s" % (name + tag, shuffledSeq), file=sys.stdout)
else:
print(">%s_%d\n%s" % (name + tag, i, shuffledSeq),
file=sys.stdout)
def main():
#
# defaults
#
file_name = None
alphabet_file_name = None
seed = 1
copies = 1
#
# get command line arguments
#
usage = """USAGE:
%s [options]
-f <filename> file name (required)
-t <tag> added to shuffled sequence names
-s <seed> random seed; default: %d
-c <n> make <n> shuffled copies of each sequence; default: %d
-a <filename> alphabet file to use non-DNA alphabets
-h print this usage message
Note that fasta-shuffle-letters also supports dinucleotide shuffling and is faster.
""" % (sys.argv[0], seed, copies)
# no arguments: print usage
if len(sys.argv) == 1:
print(usage, file=sys.stderr); sys.exit(1)
tag = ""
# parse command line
i = 1
while i < len(sys.argv):
arg = sys.argv[i]
if (arg == "-f"):
i += 1
try: file_name = sys.argv[i]
except: print(usage, file=sys.stderr); sys.exit(1)
elif (arg == "-t"):
i += 1
try: tag = sys.argv[i]
except: print(usage, file=sys.stderr); sys.exit(1)
elif (arg == "-s"):
i += 1
try: seed = int(sys.argv[i])
except: print(usage, file=sys.stderr); sys.exit(1)
elif (arg == "-c"):
i += 1
try: copies = int(sys.argv[i])
except: print(usage, file=sys.stderr); sys.exit(1)
elif (arg == "-a"):
i += 1
try: alphabet_file_name = sys.argv[i]
except: print(usage, file=sys.stderr); sys.exit(1)
elif (arg == "-h"):
print(usage, file=sys.stderr); sys.exit(1)
else:
print("Unknown command line argument: " + arg, file=sys.stderr)
sys.exit(1)
i += 1
# check that required arguments given
if (file_name == None):
print(usage, file=sys.stderr); sys.exit(1)
# get the alphabet, defaulting to DNA if it is not provided
if alphabet_file_name != None:
alph = alphabet.loadFromFile(alphabet_file_name)
else:
alph = alphabet.dna()
random.seed(seed)
# read sequences
seqs = sequence.readFASTA(file_name, alph)
for s in seqs:
seq = s.getString()
name = s.getName()
for i in range(copies):
shuffledSeq = dinuclShuffle(seq, alph)
if (copies == 1):
print(">%s\n%s" % (name+tag, shuffledSeq), file=sys.stdout)
else:
print(">%s_%d\n%s" % (name+tag, i, shuffledSeq), file=sys.stdout)
def main():
pos_seq_file_name = None # no positive sequence file specified
neg_seq_file_name = None # no negative sequence file specified
alphabet_file_name = None
refine = False
given_only = False
#
# get command line arguments
#
usage = """USAGE:
%s [options]
-w <word> word (required)
-p <file_name> positive sequences FASTA file name (required)
-n <file_name> negative sequences FASTA file name (required)
-a <file_name> alphabet definition file
-r refine consensus by branching search
(distance 1 steps; beam size = 1).
-h print this usage message
Compute the Hamming distance from <word> to each FASTA sequence
in the positive and negative files. Apply Fisher's Exact test to
each distance.
<word> may contain ambiguous characters.
""" % (sys.argv[0])
# no arguments: print usage
if len(sys.argv) == 1:
print(usage, file=sys.stderr); sys.exit(1)
# parse command line
i = 1
while i < len(sys.argv):
arg = sys.argv[i]
if (arg == "-w"):
i += 1
try: word = sys.argv[i]
except: print(usage, file=sys.stderr); sys.exit(1)
elif (arg == "-p"):
i += 1
try: pos_seq_file_name = sys.argv[i]
except: print(usage, file=sys.stderr); sys.exit(1)
elif (arg == "-n"):
i += 1
try: neg_seq_file_name = sys.argv[i]
except: print(usage, file=sys.stderr); sys.exit(1)
elif (arg == "-a"):
i += 1
try: alphabet_file_name = sys.argv[i]
except: print(usage, file=sys.stderr); sys.exit(1)
elif (arg == "-r"):
try: refine = True
except: print(usage, file=sys.stderr); sys.exit(1)
elif (arg == "-h"):
print(usage, file=sys.stderr); sys.exit(1)
else:
print(usage, file=sys.stderr); sys.exit(1)
i += 1
# check that required arguments given
if (pos_seq_file_name == None or neg_seq_file_name == None):
print(usage, file=sys.stderr); sys.exit(1)
# keep track of time
start_time = time.time()
# read alphabet
alph = None
if alphabet_file_name != None:
alph = alphabet.loadFromFile(alphabet_file_name)
else:
alph = alphabet.dna()
# read sequences
print("Reading sequences...", file=sys.stderr)
pos_seqs = get_strings_from_seqs(sequence.readFASTA(pos_seq_file_name, alph))
neg_seqs = get_strings_from_seqs(sequence.readFASTA(neg_seq_file_name, alph))
#print >> sys.stderr, "Computing Hamming enrichment..."
#(dist, log_pvalue, p, P, n, N, aln) = get_best_hamming_alignment(word, pos_seqs, neg_seqs, alph, given_only)
if refine:
(best_word, best_log_pvalue) = refine_consensus(word, pos_seqs, neg_seqs, alph, given_only)
else:
best_word = word
print("Computing Hamming alignment...", file=sys.stderr)
(dist, log_pvalue, p, P, n, N, aln) = get_best_hamming_alignment(best_word, pos_seqs, neg_seqs, alph, given_only)
pv_string = sprint_logx(log_pvalue, 1, _pv_format)
nsites = len(aln)
print("[", p, P, n, N, dist, "]", file=sys.stderr)
print("Best ZOOPs alignment has %d sites / %d at distance %d with p-value %s" % (nsites, P, dist, pv_string), file=sys.stderr)
print_meme_header(alph)
print_meme_motif(best_word, nsites, pv_string, aln, alph)
# print elapsed time
end_time = time.time()
elapsed = end_time - start_time
print("elapsed time: %.2f seconds" % elapsed, file=sys.stderr)
print("#elapsed time: %.2f seconds" % elapsed, file=sys.stdout)
