Don Conrad, Core Leader
Co-Investigators: Suzanne Fei and Robert Searles
The Portland Alcohol Research Center (PARC) research projects will generate large amounts of gene expression and epigenetic data from multiple species and treatment conditions. The Bioinformatics Core will play an integral role in the management and analysis of these data, enabling the identification of genomic markers of alcohol exposure and risk for alcohol addiction. The key functions of C002 will be to provide foundational analyses to enable the primary endpoints within each project, provide higher-order inference by integrating data across PARC projects, and to augment these analyses by integration of PARC data with publicly available data resources. C002 will work with PARC investigators to design, troubleshoot, and execute best-practice computational analysis pipelines appropriate for the primary endpoints for each project. The core’s experimental design and analysis services include: 1) Bioinformatics such as DNA-and RNA-seq read alignment, differential expression and pathway analysis, methylation and epigenetic analyses, data integration, and custom script writing; and 2) Biostatistics such as biomarker, longitudinal, survival, and high-throughput/high-dimensional omics analysis. Services under these two categories are often integrated during a given study. Each analysis is customized to best fit the needs of the project and investigator. Furthermore, C002 will augment individual PARC projects by bespoke integration of big data resources available in the public domain. C002 will download and organize available single-cell RNA-sequencing (scRNA-seq) data from relevant mouse brain regions, creating an atlas of cell type-specific expression that can be used for fine-mapping the cell types driving differential expression patterns observed in P001 and P002. Likewise, C002 will host publicly available epigenetic information from human and mouse, which will allow expression and methylation in Projects P001-P004 to be annotated and contextualized with a much larger set of genomic annotations (e.g. ChIP-seq, ATAC-seq, etc). Finally, C002 will perform cross-project integration by searching for signals that may be shared across species, first by assessing for common gene sets or pathways identified in mouse and macaque experiments, and, as a final translational step, assessing the convergence of PARC-based insights with the vast amount of human genetics data emerging on Alcohol Use Disorder.
This Core supports all four Center research Projects, several other NIH grants (R01, R37, U01, K01, F31 and F32) and VA grants focused on alcohol research, and training our students and postdocs in statistics, computation, and bioinformatics.