Core Functions

The Data Science Core provides CIDD investigators with design, statistical and data management assistance. The overall objectives of the Core are to enhance the productivity of CIDD investigators and to enhance the quality of their research. We achieve these objectives by collaborating with investigators, providing them with services through every stage of a research project. We participate in:

• writing grant proposals;
• developing efficient experimental designs;
• designing data collection instruments and conducting pilot tests;
• designing and implementing database management systems;
• supervising execution of the study and collection of data;
• operating database management systems to clean, store, and retrieve and archive data;
• performing statistical and bioinformatics analyses and writing research papers and reports

To each phase of the research effort we contribute the unique perspectives and experiences of psychometricians, biometricians, professionally trained research database managers, and a support staff of proficient programmers and data managers.

As part of our Data Science Core we offer a host of bioinformatics and biostatistical consulting, including

1. Bioinformatics

Analysis of RNA-Seq, ChIP-Seq, ATAC-Seq data
Analysis of whole exome sequencing (WES), whole genome sequencing (WGS) data
Analysis of chromatin interactomic data (from C technologies)
Analysis of additional quantitative sequencing data

2. Biostatistics

Study design, power and sample size calculations

3. Analysis of Brain Imaging data

Analysis of fMRI data
Analysis of EEG data
Analysis of multi-modal data

Membership and Access Information

To be considered for membership in the CIDD and to gain access to core resources in the IDDRC, please visit the Membership and Access Information page. Membership and Access Information

Data Science Core Expertise and Contact Information

Core Director
Yun Li, Ph.D.
Analysis of genetics and genomics data
yun_li@med.unc.edu

Core Co-Director
Kinh Young Truong
Analysis of imaging data, small samples, mixed models, time series modeling, multivariate statistical methods and statistical machine learning.
truong@bios.unc.edu

Faculty:
Jeremy Simon
Design, implementation, analysis, and biological interpretation of high-throughput sequencing-based studies, including RNA-seq and exome sequencing, as well as functional genomics assays such as ChIP, Dnase, FAIRE, and ATAC.
jeremy_simon@med.unc.edu

Guorong Wu
Consulting for image-related machine learning approaches;
Providing service of brain network analysis which includes: structural network construction/analysis, functional brain network analysis, and imaging-genetics association;
Consulting for computational approaches for microscopy images which include (1) nuclei segmentation, (2) mouse image registration.
grwu@med.unc.edu
www.acmlab.org