Bioinformatics Office Hours:
By appointment, contact gdsc@groups.dartmouth.edu
The new frontier in “-omics” is represented by high-throughput analyses of individual cells. These single-celled, high-throughput technologies are being developed for many areas, including imaging, mass spectrometry, and DNA- and RNA-sequencing. Even though single-cell -omics studies are in their relative infancy, they have already revealed new insights behind gene regulation and the etiology of human diseases, including cancer and cell-to-cell interactions. Single-cell -omics methods are especially suited for complex analyses of heterogeneous cell populations involved in disease or phenotypes.
The goal of this Core (Analytics) is to develop and to support the development of novel approaches for the analysis of -omics data (with a focus on single-cell -omics data), and to provide analytical and computational support for the research projects. This goal requires the integration, maintenance, and rigorous statistical analysis of disparate high-dimensional data, arising from: (i) high-throughput analyses proposed by research projects of this COBRE; and (ii) publicly available databases. Utilization of publicly available -omics data is important for validating the interpretation and prioritization of the findings from individual studies. The “-omics revolution” has already generated a massive (and still growing) volume of data that mostly remains a “hidden treasure”; this resource is particularly valuable for re-mining and for asking new questions of old data. By using already available -omics data, this Core aims to put this hidden treasure to work. The use of high-dimensional data requires the capacity to obtain, retrieve, store, track, curate, and process information in a rapid and efficient manner.