Biostatistics and Bioinformatics Core (BBC)

The Biostatistics and Bioinformatics Core (BBC) provides expertise in bioinformatics and statistical science to ensure scientific rigor in study design, bioinformatics and statistical analysis, and interpretation of cancer research studies. The BBC contributed to 112 peer reviewed publications during the current period, resulting in a 29% increase compared to the previous submission. Members of the Core have expertise in a range of scientific disciplines including design and analysis of clinical trials, observational studies, in vitro and in vivo studies, biomarker discovery, bioinformatics, genomics, proteomics, metabolomics, and validation projects. They collaborate with Cancer Center investigators in the planning phase of studies to ensure that hypotheses are testable and that the data will be adequate to address the study questions.

They develop novel bioinformatics algorithms and methods required for specific KCI research projects for the analysis of high-throughput data (mRNA, proteomics, methylation, etc.). They provide expertise on data collection and management and devise analysis plans consistent with study objectives and good statistical practice. At study completion, they evaluate the data for conformity with the assumptions of the statistical tests, provide estimates of the endpoints with confidence intervals, develop appropriate statistical models, assess the adequacy of the models, and prepare written reports to the investigator. The Core can also carry out full tertiary bioinformatics analysis including the identification of biological processes, cellular components and biochemical functions involved in a given phenotype, the identification of the impacted pathways, construction of novel mechanisms, biomarker identification, meta-analysis of several experiments, multi-omics analysis of varying data types, etc.

The Core maintains a variety of bioinformatics tools and statistical applications. It has licenses for iPathwayGuide, iVariantGuide and Ingenuity Pathway Analysis (IPA). It maintains a variety of bioinformatics tools for conducting downstream bioinformatics analyses including differential expression and network analyses. Statistical software includes R, R/Bioconductor, SAS and Stata/MP as well as software for sample size and statistical power calculations including PASS and nQuery Advisor.

Application software resides on a highperformance, multi-processor Dell 820 server. Access to the server is restricted to members of the Biostatistics and Bioinformatics Core and authorized guests. For some intensive computing projects, Core members use the WSU high-performance computing grid. KCI contributed four servers to the grid for use by Core members and other authorized KCI members whose research requires high performance computing.

Google Cloud is used for large, resource-intensive bioinformatics computing. A pipeline developed in the Core uses best practices suggested by The Broad Institute to leverage multiple processors and provide efficient, end-to-end processing of complex sequencing data.

Grant Number: 3P30CA022453-43S3
NIH Institute/Center: NIH
Principal Investigator: Judith Abrams