Biostatistics and Bioinformatics Core

Biostatistics and Bioinformatics Core

Mission of the Core 

The Biostatistics and Bioinformatics Core is a resource for Karmanos members in basic (in vitro and in vivo), clinical, population and translational sciences. Biostatistics is important in the design of cancer research studies to ensure that the scientific questions are framed so that they can be answered precisely and efficiently and in the analysis of these studies to ensure that the conclusions are accurate and valid. Bioinformatics is important to ensure 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 interpretation of results
  • Process raw genomic data (e.g., RNA-seq, exome sequencing) for use in statistical analyses
  • Conduct downstream bioinformatics analyses, including pathway, differential expression, and network analyses
  • Conduct statistical analyses of in vitro, in vivo, clinical and epidemiologic data
  • Write statistical reports and make statistical presentations
  • Write statistical and bioinformatic sections for grant proposals and manuscripts in collaboration with investigators
  • Provide instruction in biostatistics to cancer researchers in journal clubs, seminar series and grand rounds presentations
  • Evaluate new and conventional statistical and bioinformatic methodology for applicability to cancer research projects and for application or adaptation of methods as required
  • When current methods are inadequate, develop biostatics and bioinformatics methods for specific cancer research projects

Software, Servers and the Grid

Bioinformatics software includes ANNOVAR (, Bioconductor (, GATK (, iPathwayGuide (, iVariantGuide (, Ingenuity ( and Oncomine (, 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 R, SAS and Stata/MP. Software for calculating statistical power includes PASS and nQuery Advisor.

MS Windows-based application software resides on a Dell PowerEdge 2950 III, which has two quad core Intel Xeon 5460 3.16 MHz processors, each with 2x6 MB cache, 32GB memory and two 300 GB disk drives and a Dell R820 with 4 Xeon E5-4650 2.70GHz processors, each with eight cores, 128GB memory, four 600GB and two 146GB disk drives. 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. Access to the server is restricted to members of the Biostatistics Core and authorized guests.

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 two PowerEdge R710 computers, 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. Those 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.

Biostatistics Core Selected Publications

Senft N, Hamel LM, Manning MA, Kim S, Penner LA, Moore TF, Carducci MA, Heath EI, Lansey DG, Albrecht TL, Wojda M, Jordan A, Eggly S. Willingness to Discuss Clinical Trials Among Black vs White Men With Prostate Cancer. JAMA Oncol 2020. PMCID: PMC7499244

TM Nguyen, A Shafi, T Nguyen, S Draghici. Identifying significantly impacted pathways: a comprehensive review and assessment. Genome Biology. 2019; 20:1-15. PMCID: PMC6784345

Azmi AS, Khan HY, Muqbil I, Aboukameel A, Neggers JE, Daelemans D, Mahipal A, Dyson G, Kamgar M, Al Hallak MN, Tesfaye A, Kim S, Shidham V, Ramzi M, Philip PA. Preclinical assessment with clinical validation of Selinexor with gemcitabine and nab-paclitaxel for the treatment of pancreatic ductal adenocarcinoma. Clin Cancer Res 2020; 26:1338-1348. PMCID: PMC7073299

Canzian F, Rizzato C, Obazee O, Stein A, Flores-Luna L, Camorlinga-Ponce M, Mendez-Tenorio A, Vivas J, Trujillo E, Jang H, Chen W, Kasamatsu E, Bravo MM, Torres J, Muñoz N, Kato I. Genetic polymorphisms in the cag pathogenicity island of Helicobacter pylori and risk of stomach cancer and high-grade premalignant gastric lesions. Int J Cancer 2020.

Beebe-Dimmer JL, Ruterbusch JJ, Harper FWK, Baird TM, Finlay DG, Rundle AG, Pandolfi SS, Hastert TA, Schwartz KL, Bepler G, Simon MS, Mantey J, Abrams J, Albrecht TL, Schwartz AG. Physical activity and quality of life in African American cancer survivors: The Detroit Research on Cancer Survivors study. Cancer 2020.

McKnight BN, Kim S, Boerner JL, Viola NT. Cetuximab PET delineated changes in cellular distribution of EGFR upon dasatinib treatment in triple negative breast cancer. Breast Cancer Res 2020; 22:37. PMCID: PMC7160960

Hu C, Zhang M, Moses N, Hu CL, Polin L, Chen W, Jang H, Heyza J, Malysa A, Caruso JA, Xiang S, Patrick S, Stemmer P, Lou Z, Bai W, Wang C, Bepler G, Zhang XM. The USP10-HDAC6 axis confers cisplatin resistance in non-small cell lung cancer lacking wild-type p53. Cell Death Dis 2020;11:328. PMCID: PMC7206099 Powell IJ,

Heilbrun LK, Kittles RA. Re: African American Race is Not Associated with Risk of Reclassification during Active Surveillance: Results from Canary Prostate Cancer Active Surveillance Study. J. M. Schenk, L. F. Newcomb, Y. Zheng, A. V. Faino, K. Zhu, Y. A. Nyame, J. D. Brooks, P. R. Carroll, M. R. Cooperberg, A. Dash, C. P. Filson, M. E. Gleave, M. Liss, F. M. Martin, T. M. Morgan, P. S. Nelson, I. M. Thompson, A. A. Wagner and D. W. Lin J Urol 2020; 203: 727-733. J Urol 2021;205:338-339.

Walker C, Nguyen TM, Jessel S, Alvero AB, Silasi DA, Rutherford T, Draghici S, Mor G. Automated Assay of a Four-Protein Biomarker Panel for Improved Detection of Ovarian Cancer. Cancers (Basel) 2021;13 PMCID: PMC7830619

Cho WJ, Kessel D, Rakowski J, Loughery B, Najy AJ, Pham T, Kim S, Kwon YT, Kato I, Kim HE, Kim HC. Photodynamic Therapy as a Potent Radiosensitizer in Head and Neck Squamous Cell Carcinoma. Cancers (Basel) 2021;13 PMCID: PMC7998908

Manning M, Jiang Y, Wang R, Liu L, Rode S, Bonahoom M, Kim S, Yang ZQ. Pan-cancer analysis of RNA methyltransferases identifies FTSJ3 as a potential regulator of breast cancer progression. RNA Biol 2020; 474-486. PMCID: PMC7237164

Zhou K, Arslanturk S, Craig DB, Heath E, Draghici S. Discovery of primary prostate cancer biomarkers using cross cancer learning. Sci Rep 2021;11:10433. PMCID: PMC8128891


Seongho Kim, Ph.D.

Sorin Draghici, Ph.D.
Co-Director, Biostatistics and Bioinformatics Core

Wei Chen, Ph.D.

Greg Dyson, Ph.D.

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