45 lines
1.5 KiB
Python
45 lines
1.5 KiB
Python
from Bio.motifs import create
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from Bio.SeqIO import parse
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from numpy.random import random
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from tensorflow.io import TFRecordWriter
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from tensorflow.train import BytesList, Example, Feature, Features, FloatList
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def generate_example(sequence, weight_matrix):
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schema = {
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"sequence": Feature(bytes_list=BytesList(value=[sequence.encode()])),
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"A_counts": Feature(float_list=FloatList(value=[weight_matrix["A"][0]])),
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"C_counts": Feature(float_list=FloatList(value=[weight_matrix["C"][0]])),
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"G_counts": Feature(float_list=FloatList(value=[weight_matrix["G"][0]])),
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"T_counts": Feature(float_list=FloatList(value=[weight_matrix["T"][0]])),
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}
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example = Example(features=Features(feature=schema))
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return example.SerializeToString()
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def parse_data(filepath):
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examples = []
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with open(filepath) as handle:
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for row in parse(handle, "fastq"):
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sequence = str(row.seq)
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motifs = create(row.seq)
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example = generate_example(sequence=sequence, weight_matrix=motifs.pwm)
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examples.append(example)
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return examples
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def create_dataset(filepath):
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data = parse_data(filepath)
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train_test_split = 0.7
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with TFRecordWriter("data/train_data.tfrecords") as train_writer, TFRecordWriter(
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"data/test_data.tfrecords"
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) as test_writer:
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for element in data:
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if random() < train_test_split:
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train_writer.write(element)
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else:
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test_writer.write(element)
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create_dataset("data/curesim-HVR.fastq")
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