Talk title: Functional Interpretation of Omics Data for Health and Disease
Abstract: Recent advances in next-generation sequencing technologies have resulted in an explosive growth of diverse omics data. Functional interpretation of such data faces challenges due to their size, multi-modality, and heterogeneity. Surmounting these challenges requires intelligent algorithms and scalable analytical frameworks. In this talk, I will present new computational methods that address these challenges to discover novel biological insights in downstream analyses. First, I will describe our sensitive and scalable alignment-free metagenomic functional profiling tool, Carnelian, that generates accurate and comparable functional summaries of large-scale metagenomic datasets. I will demonstrate how we can uniquely reveal trends in microbial metabolic function across diverse populations (different nations or geographical boundaries) concerning healthy and disease individuals using these summaries. Second, I will describe our statistical framework for assessing the rare variant burden in pathways of interest and its application in rare diseases.