def main() :
util = w2lib.Week2Library()
description = '''\
Generate the contigs from a collection of reads (with imperfect coverage).
Input File format :
---------------------------------------
ATG
ATG
TGT
TGG
CAT
GGA
GAT
AGA
Expected output :
---------------------------------------
AGA ATG ATG CAT GAT TGGA TGT
'''
args = util.create_parser(__file__, description)
dataset_path = "{}/real_dataset.txt".format(DATASET_DIR)
# Default to the dataset folder, if not provided
if not args.file : args.file = dataset_path
# Read from dataset file
with open(args.file, 'r') as f :
contents = f.readlines()
kmers = [_.strip() for _ in contents]
result = generateContigs(kmers)
print(" ".join(result))
def main() :
util = w2lib.Week2Library()
description = '''\
Given adjacency list, it will reconstruct and output the Eulerian path.
Input File format :
---------------------------------------
4
CTTA
ACCA
TACC
GGCT
GCTT
TTAC
Expected output :
---------------------------------------
GGCTTACCA
'''
args = util.create_parser(__file__, description)
dataset_path = "{}/real_dataset.txt".format(DATASET_DIR)
# Default to the dataset folder, if not provided
if not args.file : args.file = dataset_path
# Read from dataset file
with open(args.file, 'r') as f :
k = f.readline()
kmers = [_.strip() for _ in f.readlines()]
genome = stringReconstruction(int(k), kmers)
print(genome)
def main():
util = w2lib.Week2Library()
description = '''\
Given a kmer length, it will create all binary combinations with that length.
(ex. k=3, 000, 001, 010, 011, 100, 101, 110, 111)
It then takes the kmer, and construct a cycle that covers all of kmers to
construct the universal circular string.
Input File format :
---------------------------------------
4
Expected output :
---------------------------------------
0000110010111101
'''
args = util.create_parser(__file__, description)
dataset_path = "{}/real_dataset.txt".format(DATASET_DIR)
# Default to the dataset folder, if not provided
if not args.file: args.file = dataset_path
# Read from dataset file
with open(args.file, 'r') as f:
k = f.readline().strip()
circular_string = universalCircularString(int(k))
print(circular_string)
def main():
util = w2lib.Week2Library()
description = '''\
Given adjacency list, it will reconstruct and output the Eulerian path.
Input File format :
---------------------------------------
1 -> 2
2 -> 3
3 -> 4,5
6 -> 7
7 -> 6
Expected output :
---------------------------------------
1 -> 2 -> 3
3 -> 4
3 -> 5
7 -> 6 -> 7
'''
args = util.create_parser(__file__, description)
dataset_path = "{}/real_dataset.txt".format(DATASET_DIR)
# Default to the dataset folder, if not provided
if not args.file: args.file = dataset_path
# Read from dataset file
with open(args.file, 'r') as f:
contents = f.readlines()
# Format into adjacency list
adj_dict = {}
for content in contents:
row = content.split("->")
left_node = row[0].strip()
right_node = row[1].strip().split(",")
adj_dict[left_node] = right_node
paths = maximalNonBranchingPaths(adj_dict)
for path in paths:
print(" -> ".join(path))
def main() :
util = w2lib.Week2Library()
description = '''\
Given adjacency list, it will reconstruct and output the Eulerian cycle.
Input File format :
---------------------------------------
0 -> 3
1 -> 0
2 -> 1,6
3 -> 2
4 -> 2
5 -> 4
6 -> 5,8
7 -> 9
8 -> 7
9 -> 6
Expected output :
---------------------------------------
6->8->7->9->6->5->4->2->1->0->3->2->6
'''
args = util.create_parser(__file__, description)
dataset_path = "{}/real_dataset.txt".format(DATASET_DIR)
# Default to the dataset folder, if not provided
if not args.file : args.file = dataset_path
adjacency_dict = {}
# Read from dataset file
with open(args.file, 'r') as f :
rows = f.readlines()
for row in rows :
row = row.replace(" ", "").strip().split("->")
adjacency_dict[row[0]] = [r for r in row[1].split(",")]
cycle = eulerCycle(adjacency_dict)
print("->".join(cycle))
def main():
util = w2lib.Week2Library()
description = '''\
Given k-length, distance of the paired reads, and the paired reads itself,
it will try to align the paired reads to reconstruct the full string.
Input File format :
---------------------------------------
4 2
GACC|GCGC
ACCG|CGCC
CCGA|GCCG
CGAG|CCGG
GAGC|CGGA
Expected output :
---------------------------------------
GACCGAGCGCCGGA
'''
args = util.create_parser(__file__, description)
dataset_path = "{}/real_dataset.txt".format(DATASET_DIR)
# Default to the dataset folder, if not provided
if not args.file: args.file = dataset_path
# Read from dataset file
with open(args.file, 'r') as f:
k, d = f.readline().strip().split(" ")
contents = f.readlines()
paired_reads = []
for _ in contents:
reads = _.split("|")
read1 = reads[0].strip()
read2 = reads[1].strip()
paired_reads.append([read1, read2])
text = stringSpelledByGappedPatterns(int(k), int(d), paired_reads)
print(text)
def main() :
util = w2lib.Week2Library()
description = '''\
Given adjacency list, it will reconstruct and output the Eulerian path.
Input File format :
---------------------------------------
4 2
GAGA|TTGA
TCGT|GATG
CGTG|ATGT
TGGT|TGAG
GTGA|TGTT
GTGG|GTGA
TGAG|GTTG
GGTC|GAGA
GTCG|AGAT
Expected output :
---------------------------------------
GTGGTCGTGAGATGTTGA
'''
args = util.create_parser(__file__, description)
dataset_path = "{}/real_dataset.txt".format(DATASET_DIR)
# Default to the dataset folder, if not provided
if not args.file : args.file = dataset_path
# Read from dataset file
with open(args.file, 'r') as f :
k, d = f.readline().strip().split(" ")
contents = f.readlines()
paired_reads = [_.strip() for _ in contents]
text = stringReconstructionFromReadPairs(int(k), int(d), paired_reads)
print(text)