ScreenClust: Advanced statistical software for supervised and unsupervised high resolution melting (HRM) analysis.
BACKGROUND
High resolution melting (HRM) is an emerging new method for interrogating and characterizing DNA samples. An important aspect of this technology is data analysis. Traditional HRM curves can be difficult to interpret and the method has been criticized for lack of statistical interrogation and arbitrary interpretation of results.


METHODS
Here we report the basic principles and first applications of a new statistical approach to HRM analysis addressing these concerns. Our method allows automated genotyping of unknown samples coupled with formal statistical information on the likelihood, if an unknown sample is of a known genotype (by discriminant analysis or "supervised learning"). It can also determine the assortment of alleles present (by cluster analysis or "unsupervised learning") without a priori knowledge of the genotypes present.


CONCLUSIONS
The new algorithms provide highly sensitive and specific auto-calling of genotypes from HRM data in both supervised an unsupervised analysis mode. The method is based on pure statistical interrogation of the data set with a high degree of standardization. The hypothesis-free unsupervised mode offers various possibilities for de novo HRM applications such as mutation discovery.
Reja
Valin
V
Bio Republic, 14 Birriwa Street Greystanes, NSW 2145, Australia.
Kwok
Alister
A
Stone
Glenn
G
Yang
Linsong
L
Missel
Andreas
A
Menzel
Christoph
C
Bassam
Brant
B
D000465:Algorithms; D001185:Artificial Intelligence; D016000:Cluster Analysis; D004252:DNA Mutational Analysis / Q000379:methods*; D005615:Freezing; D005838:Genotype; D009691:Nucleic Acid Denaturation; D025341:Principal Component Analysis; D012984:Software