High Resolution Melt Analysis in Python
Switch branches/tags
Nothing to show
Clone or download
Fetching latest commit…
Cannot retrieve the latest commit at this time.

README.md

PyHRM

High Resolution Melt Analysis in Python

I am surprised that no free software is available to do such simple data analysis. So with some opensource spirit, I decide to write my own and share it with fellow scientists.

You can view this ipython notebook demo here:

https://github.com/liuyigh/PyHRM/blob/master/PyHRM.ipynb

FAQ

Clustering not working.

When you get noisy data, the k-means is not going to magically salvage it. Try these:

  • Do your PCR with touch down protocol, it greatly improves data quality, like magic!
  • Make sure you get rid off empty wells, failed wells (look at your melting curve peaks), obvious outliers
  • Make sure you choose the best temp range ± 5 degree C around melting temp usually works the best.
  • For subtle differences, your eyes can be better at pattern recognition than k-means. Use the provided code to plot it with plot.ly. You can look at individual lines on plot.ly to make your own judgement.
  • Reduce heat block variation by running only 1 target gene in symatrically arranged wells.

How sensitive is pyHRM?

I am able to reliably detect:

  • nfkb1-/- genetyping: WT vs HET vs KO; using original regular PCR primer
  • an amplicon in nfkb2 gene that have single point T->G mutation: WT vs HET vs KO
  • an amplicon in nfkb2 gene that have 4 base pair "TCCA" loss mutation: WT vs HET vs KO

Reagents

qPCR protocol

Do your PCR with touch down protocol, it greatly improves data quality, like magic!

Basics: HRM - High Resolution Melt Analysis

Kapa BioSystems HRM Guide

Other Software

  • Precision Melt from Bio-Rad: $3,455
  • GenEx: EUR€595 - 2,495
  • Life Technologies: $794, 1 license
  • uAnalyze: Does not support Bio-Rad CFX platforms