This is a python library to Find Candidate reference gene
In new Version 1.2.0, the computing speed is increased by a factor of 100
Binary installers for the latest released version are available at the pypi
#PyPI
pip install ERgene
- Numpy
- time
- pandas
- itertools
- upsetplot
See the full installation instructions for minimum supported versions of required, recommended and optional dependencies
input
import ERgene
import pandas as pd
data=pd.read_csv('gse.txt',sep='\t')#GSE125792
data=data.set_index(data.columns[0])#This is Ver1.2
ERgene.FindERG(data,3)
output
calculate time:17.3s
['ASHGV40057862', 'ASHGV40057056', 'ASHGV40025887', 'ASHGV40056316', 'ASHGV40056377', 'ASHGV40057617', 'ASHGV40057263']
if you use jupyter notebook, there is an Upsetplot will be generated.
You only need to input the gene to normalizate.
However, the literature has proved that single gene standardization is not desirable, so this method should be used with Caution!!!
input
ans=ERgene.normalizationdata(data,'ASHGV40056316')
print(ans)
output
MIT
