通过爬虫在GEO数据库上获取对应SRR号

最新推荐文章于 2025-06-04 23:11:29 发布

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最新推荐文章于 2025-06-04 23:11:29 发布 · 1.2k 阅读

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#python

一、配置python环境

详见百度

二、Chromdriver安装

Chromdriver下载地址：

http://chromedriver.storage.googleapis.com/index.html

http://npm.taobao.org/mirrors/chromedriver/

需要下载与本机谷歌浏览器版本一致，具体配置百度。

三、安装软件Pycharm

官网下载即可。

四、爬虫

代码如下：

# 通过GSM号搜索ncbi中的Run，SRX细节页信息
# GSM号表中以GSM为列名，以GSM号为列内容
import requests        #导入requests包
import pandas as pd
import re
from bs4 import BeautifulSoup
url = 'https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc='
# strhtml = requests.get(url)        #Get方式获取网页数据
# print(strhtml.text)

df = pd.read_csv("C://Users//admin//Desktop//pachong//GSE195956//srr.csv", encoding='utf-8')
row = df['gsm']
# 列表字段
GSE = ""
GSMID = ""
GSMName = ""
PMID = ""
Characteristic = ""
Source_name = ""
Organism = ""
SRR = ""
Instrument = ""
Strategy = ""
Source = ""
Selection = ""
Layout = ""
for gsm in row:
    gsmurl = url+gsm
    print(gsmurl)
    strhtml = requests.get(gsmurl)
    sampleDetailSoup = BeautifulSoup(strhtml.text, 'lxml')
    detailHtml = sampleDeta