Abstract

While most efforts have been focused on how to make more accurate calls on whole genome or whole exome sequencing data, it is becoming increasingly clear that even with more and more accurate and complete calls, how to interpret data and make meaningful genotype phenotype connections is still a huge challenge. Building comprehensive pipelines and making calls easily interpretable for clinical professionals is an important and urgent task. I am going to discuss some exome sequencing data analysis procedures that may help clinicians to understand the data and to make genotype phenotype connections. These include routinely checking and reporting aneuploidy, hidden consanguineous marriage in family, coverage on most interested candidate genes, etc. In addition to linkage analysis to narrow down the list of mutations for further examination, I will also introduce two software we developed in identifying sharing of recent founder haplotypes among cases with unknown relationship, HRRA and HaploShare, that may aid the search for causal mutations or major disease contributors. Incorporation of other information will also prove to be important in understanding the data, such as nature of mutation, function and expression profile of the related genes, and population genetic information. I will try to make a point that in most cases, making genotype phenotype connection is going to need an extremely comprehensive endeavor and sophisticated computation and modeling. Close collaborations among experts from different disciplines are necessary.