hrmpython 0.1

A simple package to handle HRM data in python

hrmPy

A simple python package to handle High Resolution Melting (HRM) experiment data analysis. For full functionality see tutorial.ipynb.

Quick start

Install dependencies

pip install -r requirements.txt
pip install hrmpython

Create simple visulization with clustering

from hrmpy import HRM
import pandas as pd
import matplotlib.pyplot as plt

df = pd.read_csv('./Sample-HRM-p50-genotyping.csv')

hrm = HRM(df)
hrm.subset((75,88))
hrm.clustering('kmeans', 3)
data = hrm.diff()

palette = ['red', 'blue', 'green']

for i in range(len(data.columns)):
    column = data.columns[i]
    plt.plot(hrm.temp, data[column], color=palette[hrm.cluster[i]])

plt.xlabel('Temperature (°C)')
plt.ylabel('-d(norm RFU)/dT') 

Find sample Tm

hrm.tm()

   Sample  Temperature
0      G6         81.0
1      G7         82.2
2      G8         82.2
3      G9         82.2
4     G10         82.2
...
31    J10         82.2
32    J11         82.4
33    J12         81.0
34    J13         82.2
35    J14         82.2

Data input

Technically melting data from any instrument should work, as long it is formatted correctlly.

• Remove empty columns or empty rows
• First column should be 'Temperature' and the rest is melting data with sample or 'well' as column name.

Please see Sample-HRM-p50-genotyping.csv for input example.

Credit

• hrmpy is implementation and improvement of liuyigh's PyHRM
• example input Sample-HRM-p50-genotyping.csv is created by liuyigh