Json To Vcf May 2026

data = json.load(f) df = pd.DataFrame(data) Convert dataframe to VCF format vcf_data = [] for index, row in df.iterrows():

[ "chr": "chr1", "pos": 100, "ref": "A", "alt": "T" , "chr": "chr2", "pos": 200, "ref": "C", "alt": "G" ] “`python import json import pandas as pd Load JSON data with open(‘input.json’) as f: json to vcf

As data scientists, researchers, and developers work with diverse data sources, the need to convert data from one format to another arises. In this article, we will focus on converting JSON data to VCF format, exploring the reasons behind this conversion, the tools and methods available, and a step-by-step guide on how to achieve it. data = json

vcf_row = [ row['chr'], row['pos'], '.', row['ref'], row['alt'], '100', 'PASS', '.', '.' ] vcf_data.append(vcf_row) with open(‘output.vcf’, ‘w’) as f: A JSON object might look like this:

"name": "John", "age": 30, "variants": [ "chr": "chr1", "pos": 100, "ref": "A", "alt": "T" ]

pip install json pandas

JSON is a lightweight, text-based format that represents data as key-value pairs, arrays, and objects. A JSON object might look like this: