Our long-term goal for our newly formed bioinformatics company Enodar BioLogic Corporation (Enodar) is to bring rigorously developed statistical tools to clinical genomic studies by marketing a software module called SNIPLus. In the short-term we will investigate the performance of this haplotype-based method for analyzing multiple SNP markers from candidate genes, especially the scalability of handling dozen of SNPs to over hundreds of SNPs, and flexibility of testing haplotype/environmental interactions. If the preliminary results turn out to be promising, we will develop the methodology into a working prototype of SNiPlus. SNiPlus will associate haplotypes with clinical outcomes, facilitating discovery of haplotype-based biomarkers for assessing efficacy of clinical treatment and prognosis. Phase I specific aims are to: 1) develop and test SNiPlus for modeling clinical outcomes with SNP profiles and 2) develop a user-friendly SNiPlus software prototype module. SNiPlus will be able to fill the gap between biomedical researchers and statistical genetics, and to enable biomedical investigators to postulate and test specific haplotype-based hypotheses under rigorous statistical assessment.
The investigators will market the SNiPlus statistical software module as an add-on package to GENEPLUS, our existing bioinformatics software suite for analyzing genomic data. Commercially, Enodar will develop a user-friendly software interface for use by both basic science and clinical science researchers, who will more easily generate valuable leads for clinical research.
| Zhao, Lue Ping; Fan, Wenhong; Goodman, Gary et al. (2015) Deciphering Genome Environment Wide Interactions Using Exposed Subjects Only. Genet Epidemiol 39:334-46 |
| Zhao, Lue Ping; Huang, Xin (2013) Recursive organizer (ROR): an analytic framework for sequence-based association analysis. Hum Genet 132:745-59 |
