%0 Journal Article
%T A base-calling algorithm for Tm-shifted melting curve SNP assay
%A Kung-Hao Liang
%A Jun-Jeng Fen
%A Hsien-Hsun Chang
%A Hsei-Wei Wang
%A Yuchi Hwang
%J Journal of Clinical Bioinformatics
%D 2011
%I BioMed Central
%R 10.1186/2043-9113-1-3
%X We presented a supervised base-calling algorithm and software for Tm-shifted melting curve SNP assays. The algorithm comprises a peak detection procedure and an ordinal regression model. The peak detection procedure is required for building models as well as handling new samples. Ordinal regression is proposed because signal intensities of alleles AA, AB, and BB usually follow an ordinal pattern with the heterozygous allele lie between two distinct homozygous alleles. Coefficients of the ordinal regression model are first trained and then used for base calling.A dataset of 12 SNPs of 44 unrelated persons was used for a demonstration purpose. The call rate is 99.6%. Among the base calls, 99.1% are identical to those made by the sequencing method. A small fraction of the melting curve signals (0.4%) is declared as "no call" for further human inspection. A software was implemented using the Java language, providing a graphical user interface for the visualization and handling of multiple melting curve signals.Tm-shifted melting curve SNP assays, together with the proposed base calling algorithm and software, provide a practical solution for genetic tests on a clinical setting. The software is available in http://www.bioinformatics.org/mcsnp/wiki/Main/HomePage webciteDiscoveries of associations between genetic variants and clinical traits have improved our knowledge of human in health and disease [1]. Most of these findings came from research-phrase genome-wide association studies (GWAS) of various common-complex diseases [2-5]. Once validated in independent cohorts, these associations can facilitate the development of genetic tests for estimating personal disease risks. As GWAS gains popularity among clinical scientists, genetic tests are anticipated to play an increasingly important role in preventive and personalized healthcare systems.Single nucleotide polymorphism (SNP) is an important class of human genomic variants widely assayed on GWAS. Current genetic tests ar
%U http://www.jclinbioinformatics.com/content/1/1/3