生物信息学知识库

浅言前言

软件安装

Linux基础

报错及解决方案

• Some index files failed to download. They have been ignored, or old ones used instead.：编辑vi /etc/resolv.conf，加入：

nameserver 8.8.8.8
nameserver 8.8.4.4

Nginx

• 不同域名指定端口

# Default server configuration
#
server {
	listen 80 default_server;
	listen [::]:80 default_server;

	root /var/www/html;

	# Add index.php to the list if you are using PHP
	index index.html index.htm index.nginx-debian.html;

	server_name _;

	location / {
		# First attempt to serve request as file, then
		# as directory, then fall back to displaying a 404.
		try_files $uri $uri/ =404;
	}
}

server {
    listen 80;
    server_name xxx.xxx.com;
    location / {
        proxy_pass http://localhost:3000;
        proxy_set_header Host $host;
        proxy_set_header X-Real-IP $remote_addr;
        proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
        proxy_set_header X-Forwarded-Proto $scheme;
    }
}

server {
    listen 80;
    server_name xxx.xxx.com;
    location / {
        proxy_pass http://localhost:1288;
        proxy_set_header Host $host;
        proxy_set_header X-Real-IP $remote_addr;
        proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
        proxy_set_header X-Forwarded-Proto $scheme;
    }
}

数据库

• BUSCO：基因组组装质量评估软件。

  • 使用教程：简书链接

• Addgene：非营利性的质粒库

• Primer3Plus：引物设计
• DBD：转录因子预测数据库
• Plant Transcription Factor Database：植物转录因子数据库
• RiceNetDB：水稻基因互作数据库（浙大）
• RPAN: Rice Pan-genome Browser：水稻泛基因组数据库（上海交大）
• NCBI blast数据库
• 国家微生物数据科学中心数据下载
• PlaD：植物对病原体防御反应的转录组学数据库
• 植物转录组表达数据库
• JASPAR：预测转录因子结合位点的网站
• NAR专刊: 各种数据库文章
• 南方科技大学-植物转录组数据库

序列处理

从基因组提取蛋白序列

gffread genome.gff -g genome.fa -y 100.pep

从基因组提取基因序列

搜索半天找不到合适的工具，让ChatGPT写了一个：

from Bio import SeqIO
import gffutils
import argparse

# 解析命令行参数
parser = argparse.ArgumentParser(description="Extract gene sequences from genome and GFF files.")
parser.add_argument("-genome", dest="genome_file", required=True, help="Path to the genome FASTA file")
parser.add_argument("-gff", dest="gff_file", required=True, help="Path to the GFF3 file")
parser.add_argument("-out", dest="out_file", required=True, help="Path to the output file")
args = parser.parse_args()

# 读取基因组序列
genome_seq = SeqIO.to_dict(SeqIO.parse(args.genome_file, "fasta"))

# 读取GFF文件并建立数据库
db_file = args.gff_file + ".db"
db = gffutils.create_db(args.gff_file, dbfn=db_file, force=True)

# 遍历所有基因，提取核酸序列并输出到文件
with open(args.out_file, "w") as out_file:
    for gene in db.features_of_type("gene"):
        # 获取基因序列的位置信息
        seq_region = gene.seqid
        start = gene.start
        end = gene.end
        strand = gene.strand
        
        # 从基因组序列中提取基因核酸序列
        if seq_region in genome_seq:
            gene_seq = genome_seq[seq_region][start-1:end].seq
            if strand == "-":
                gene_seq = gene_seq.reverse_complement()
            
            # 输出基因核酸序列到文件
            out_file.write(">" + gene.id + "\n")
            out_file.write(str(gene_seq) + "\n")

提取启动子序列

# 导入所需的包
from Bio import SeqIO
import argparse

# 创建参数解析器
parser = argparse.ArgumentParser(description='从GFF文件中提取每个转录本的信息，并在此基础上提取指定长度的启动子序列。')
parser.add_argument(
    '-i',
    '--input',
    dest='gff_file',
    type=str,
    required=True,
    help='输入GFF文件路径。'
)
parser.add_argument(
    '-g',
    '--genome',
    dest='genome_file',
    type=str,
    required=True,
    help='输入基因组序列文件路径。'
)
parser.add_argument(
    '-o',
    '--output',
    dest='output_file',
    type=str,
    required=True,
    help='输出文件路径。'
)
parser.add_argument(
    '-l',
    '--length',
    dest='promoter_length',
    type=int,
    default=1500,
    help='指定启动子序列的长度，默认为1500bp。'
)

# 解析参数
args = parser.parse_args()

# 初始化基因组序列
genome_dict = SeqIO.to_dict(SeqIO.parse(args.genome_file, 'fasta'))

# 从GFF文件中提取转录本位置信息，并从基因组序列中提取启动子序列
with open(args.output_file, 'w') as out_file, open(args.gff_file) as in_file:
    for line in in_file:
        fields = line.strip().split('\t')
        if fields[2] == 'mRNA':
            transcript_id = fields[8].split(';')[0].split('=')[1]
            gene_id = fields[8].split(';')[1].split('=')[1]
            chr_num = fields[0]
            start = int(fields[3])
            end = int(fields[4])
            strand = fields[6]
            # 根据正负链计算起始位置和终止位置
            if strand == '+':
                promoter_start = max(0, start - args.promoter_length)
                promoter_end = start
            else:
                promoter_start = end
                promoter_end = min(len(genome_dict[chr_num]), end + args.promoter_length)
            # 从基因组序列中提取启动子序列
            promoter_seq = str(genome_dict[chr_num].seq[promoter_start:promoter_end]).upper()
            # 将启动子序列写入输出文件
            out_file.write(f'>{transcript_id}\n{promoter_seq}\n')

用法如下：

python getpromoterseqfromgenome.py -genome 1.fa -gff temp.gff -length 5 -out test.fa    

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