Biostatistics and Bioinformatics Core
Mission of the Core
The Biostatistics and Bioinformatics Core serves as a resource for cancer investigators engaged in basic (in vitro and in vivo), clinical, population, and translational sciences. Biostatistics plays a crucial role in the design of cancer research studies, ensuring that scientific questions are framed for precise and efficient answers, and in the analysis of these studies to guarantee accurate and valid conclusions. Bioinformatics is essential for computationally efficient and informative analyses.
The Biostatistics and Bioinformatics Core is supported, in part, by NIH Center grant P30 CA022453 to the Karmanos Cancer Institute at Wayne State University.
Core Services Available
Specifically, members of the Core:
- Develop experimental designs for clinical, laboratory, intervention, and observational studies
- Conduct statistical and bioinformatic analyses and collaborate on interpreting results
- Process raw genomic data (e.g., RNA-seq, exome sequencing) for use in statistical analyses
- Conduct downstream bioinformatics analyses, including differential expression, pathway, network, and classification analyses
- Perform statistical analyses of in vitro, in vivo, clinical and epidemiologic data
- Write statistical reports and deliver statistical presentations
- Collaborate with investigators to write statistical and bioinformatic sections for grant proposals and manuscripts
- Provide instruction in biostatistics to cancer researchers through journal clubs, seminar series, and grand rounds presentations
- Assess new and conventional statistical and bioinformatic methodologies for their applicability to cancer research projects, and apply or adapt methods as required
- Develop biostatistics and bioinformatics methods for specific cancer research projects when current methods are inadequate
New Collaboration Request
All new collaboration requests must be submitted using either the offline or online collaboration request form, which are available below. For existing collaborations, please directly contact the relevant Core member(s). Once we receive your request, please allow up to five business days for us to respond. We kindly ask that you review the collaboration policies before submitting your collaboration request.
Software, Servers and the Grid
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Bioinformatics software includes ANNOVAR (annovar.openbioinformatics.org), Bioconductor (www.bioconductor.org), GATK (gatk.broadinstitute.org), GSEA (www.gsea-msigdb.org/gsea), iPathwayGuide (www.advaitabio.com), iVariantGuide (www.advaitabio.com), and MetaboAnalyst (www.metaboanalyst.ca), among others. The Core continuously reviews and updates processes to follow and maintain best practices when designing custom computational pipelines for all stages of bioinformatics analysis from data pre-processing to variant discovery.
Statistical applications include general-purpose software such as R, SAS, and SPSS. Software for calculating statistical power includes PASS.
MS Windows-based application software resides on two Windows servers. One is a Dell PowerEdge R760 Server, which has two Intel Xeon Gold 6444Y 3.6 GHz processors, each with 45MB cache, 256GB RAM, two 1.92 TB SSD disk drives, and 15 1.2 TB SAS disk drives. The other is a Dell R820 with four Xeon E5-4650 2.70GHz processors, each with eight cores, 128GB RAM, four 600GB, and two 146GB disk drives. Access to the servers is restricted to members of the Biostatistics and Bioinformatics Core and authorized guests.
The backup unit is a 4 DAT drive running Veritas Backup Exec. Incremental backup of data files is performed nightly. Full back-ups are performed weekly, and the data tapes are maintained off-site in a secure, fireproof storage facility.
Linux-based application software may be run on the Wayne State University high-performance grid system. The Wayne State University Grid is a tightly networked system of 400+ nodes and over 8000 processing cores.
Integrated into the Wayne State University high-performance grid computing facility are three Linux servers. One is a PowerEdge R7625 Server, with 512GB RAM, two AMD EPYC 9374F 3.85 GHz processors, each with 256 Cache, and 1.6 TB enterprise-grade SSD disk drives. The other two are PowerEdge R710 Servers, each with 48GB RAM, dual 6 core Intel Xeon X5680 3.33 GHz processors, and 1TB hard drives that run under the Linux operating system. These computers were purchased by Karmanos for the use of Core members but are accessible to other authorized Karmanos members whose research requires high-performance computing capabilities.
The Core uses the Google Cloud Platform for computationally intensive analyses, analyses that require large memory, are highly distributed, or CPU-intensive, particularly pre-processing raw sequence data. Cloud resources will also be utilized for medium and long-term storage of raw data, processed data, and associated procedures and pipelines. All third-party resources are HIPAA compliant.
Core Members
Seongho Kim, Ph.D.
Professor, Department of Oncology, School of Medicine
Director, Biostatistics and Bioinformatics Core
Wei Chen, Ph.D.
Professor, Department of Oncology, School of Medicine
Greg Dyson, Ph.D.
Associate Professor, Department of Oncology, School of Medicine
Hunter Dlugas, B.S.
Biostatistician
Hyejeong Jang, M.S.
Biostatistician
Charles Robinson, Ph.D.
Biostatistician
Core Affiliates
Suzan Arslanturk, Ph.D.
Assistant Professor, Department of Computer Science, College of Engineering
Sorin Draghici, Ph.D.
Professor, Department of Computer Science, College of Engineering
Zichun Zhong, Ph.D.
Associate Professor, Department of Computer Science, College of Engineering
Dongxiao Zhu, Ph.D.
Associate Professor, Department of Computer Science, College of Engineering
Contact
Seongho Kim, Ph.D.
Professor, Department of Oncology, School of Medicine
Director, Biostatistics and Bioinformatics Core
313-576-8653
kimse@karmanos.org