python脚本过滤得到non-overlap的utr

使用该脚本对上述的结果"lin_20240321_calculating_rG4score.R"进行过滤

python 复制代码
import csv

def read_file(file_path):
    with open(file_path, 'r') as file:
        reader = csv.DictReader(file, delimiter='\t')
        return list(reader)

def process_sequences(data):
    gene_sequences = {}
    for row in data:
        gene_id = row['Id']
        start = int(row['Start'])
        end = int(row['End'])
        length=int(row['total_length'])
        score = float(row['G4Hscore'])

        if gene_id not in gene_sequences:
            gene_sequences[gene_id] = []

        gene_sequences[gene_id].append({
            'Type': row['Type'],
            'Start': start,
            'End': end,
            'Length': length,
            'Sequence': row['Sequence'],
            'Score': score
        })

    # 对每个基因的序列按分数降序排序
    for gene_id, sequences in gene_sequences.items():
        gene_sequences[gene_id] = sorted(sequences, key=lambda x: x['Score'], reverse=True)

    # 保留分数最高且不重叠的序列
    final_selection = {}
    for gene_id, sequences in gene_sequences.items():
        final_selection[gene_id] = []
        for seq in sequences:
            if not any(seq['Start'] < s['End'] and seq['End'] > s['Start'] for s in final_selection[gene_id]):
                final_selection[gene_id].append(seq)

    return final_selection

def write_results(gene_sequences, output_file):
    with open(output_file, 'w', newline='') as file:
        writer = csv.writer(file, delimiter='\t')
        writer.writerow(['Id', 'Type', 'Start', 'End', 'Total_length','Sequence', 'Score'])
        for gene_id, sequences in gene_sequences.items():
            for seq in sequences:
                writer.writerow([gene_id, seq['Type'], seq['Start'], seq['End'], seq['Length'], seq['Sequence'], seq['Score']])

# 输入和输出文件路径
#usage:python lin_filter_non-overlap_rg4.py -f1 lijinonextended_3utr_allrg4output1.fasta -f2 lijinonextended_3utr_allrg4output2.fasta
import argparse
parser = argparse.ArgumentParser(description="Advanced screening always by hash")
parser.add_argument("-f1","--file1",help="input1")
parser.add_argument("-f2","--file2",help="input2")
args = parser.parse_args()

# 读取文件
data = read_file(args.file1)
# 处理序列,保留得分最高且不重叠的序列
gene_sequences = process_sequences(data)
# 将结果写入新文件
write_results(gene_sequences, args.file2)
相关推荐
Mr_Xuhhh6 小时前
Java泛型进阶:从基础到高级特性完全指南
开发语言·windows·python
老天文学家了7 小时前
蓝桥杯备战Python
开发语言·python
ID_180079054737 小时前
除了 Python,还有哪些语言可以解析 JSON 数据?
开发语言·python·json
FreakStudio8 小时前
小作坊 GitHub 协作闭环:fork-sync-dev-pr-merge 实战指南
python·单片机·嵌入式·面向对象·电子diy
普通网友9 小时前
阿里云国际版服务器,真的是学生党的性价比之选吗?
后端·python·阿里云·flask·云计算
小陈工10 小时前
2026年4月2日技术资讯洞察:数据库融合革命、端侧AI突破与脑机接口产业化
开发语言·前端·数据库·人工智能·python·安全
陈晓明start10 小时前
【python】豆包模型,自动生成测试用例初探索
python
阿kun要赚马内10 小时前
Python中元组和列表差异:底层结构分析
开发语言·python
万添裁10 小时前
pytorch的张量数据结构以及各种操作函数的底层原理
人工智能·pytorch·python