Core E: Biostatistics and Bioinformatics Core

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BIOSTATISTICS AND BIOINFORMATICS CORE E ABSTRACT Project Summary Traditionally, much IDD research has focused on a single domain, e.g., either neuroimaging or behavior; either animal research or human research; either genetics or neuroimaging. Today, the state of the science is evolving into far more complex combinations of data from multiple viewpoints (e.g., genetic, neuroimaging, and behavioral data), which together can propel the next generation of IDD research aimed at discovering how to better identify, prevent, and intervene for those with IDDs. Thus, there is a great need to determine the most effective ways to combine and to analyze these multiple types and sources of data. Furthermore, for data types that are inherently multidimensional (e.g., genetics or neuroimaging), a second challenge becomes apparent: many of these approaches require big sample sizes. Therefore, an additional focus of Core E is to explore ways of effectively utilizing large repositories of data (BioVU/Synthetic Derivative). While these data sources are advantageous in size, navigating them is a daunting process for most investigators. Within this context, the overarching objective of Core E is to leverage the considerable statistical and bioinformatics expertise at VU and VUMC in order to push the current boundaries of design and analyses in the service of innovative discoveries in IDD. Against this backdrop, Core E has three aims: Aim 1 is to provide statistical consultation to IDDRC investigators in implementing state-of-the art approaches to experimental design, statistical analysis, and interpretation of findings. Core E provides behavioral and biobehavioral statistical consultations to IDDRC investigators and their trainees who need guidance on basic or innovative research study design; efficient data collection and storage; proper method evaluation and implementation; and data analyses and interpretation. Aim 2 is to develop new bioinformatics platforms for automation of data processing from multiple sources and to implement less widely used or novel data analysis approaches in IDD research. Aim 3 is to create IDD- specific databases from large-scale electronic medical record and genomic resources at VUMC and to provide corresponding training and support services. These Aims meet the needs of IDDRC investigators, including the U54 Research Project, while also generating new platforms, processes, and analytic methods that advance translational IDD science.