Facility Core #4: Bioinformatics & Biostatistics
Transcriptional profiling and other high throughput genomic technologies (e.g. high density SNP genotyping, next generation sequencing) generate large amounts of complex data. The majority of investigators do not possess the skills or expertise in bioinformatics and biostatistics to perform thorough and rigorous data analysis. In addition, research in bioinformatics and biostatistical methods for genomic data continues to develop very rapidly, and even the most statistically savvy life science investigator finds it difficult, if not impossible, to keep up with the field. The Bioinformatics and Biostatistics Core provides support that enables CEEH investigators to incorporate microarray and other high-throughput laboratory assays into their research. The Bioinformatics and Biostatistics Facility Core is a "full-service" bioinformatics center for the design of studies utilizing high throughput genomic, proteomic and metabolomic technologies and the analysis of the corresponding data. This facility core manages a suite of bioinformatics and statistical software and maintains a database for gene expression measurements. Members of the core provide on-site user support, conduct tutorials on data analysis, and, most importantly, provide comprehensive data management and analysis.
The goals of the Bioinformatics and Biostatistics Facility Core are:
- Provide expert advice on the design of microarray (mRNA) and microRNA array experiments, including the numbers of biological and technical replicates, and the experimental design for one color and two-color platforms.
- Provide full-service data analysis, including signal quantification, data normalization and transformation, data modeling, significance analysis, identification of differentially expressed genes, and data mining (e.g. cluster analysis, pathway analysis).
- Provide advanced analysis of proteomics data, including Gene Ontology and pathway analyses.
- Provide advanced analysis of metabolomics data, including the use of mixed effects linear models for biomarker prediction.
- Develop and establish analysis pipeline for Next Generation Sequencing data.
- Support manuscript and grant proposal review and preparation.
- Facilitate collaborations between CEEH investigators who utilize the core.
Director: Kathleen Kerr, Ph.D
katiek@u.washington.edu
(206) 543-2507
Research Scientists:
Theo Bammer, Ph.D.
tbammler@u.washington.edu
(206) 616 – 7378
Richard Beyer, Ph.D.
dbeyer@u.washington.edu
(206) 616-7378