This facility supports Fox Chase Cancer Center's Cancer Center Support Grant (CCSG) from the National Cancer Institute.
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Director:
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Staff:
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Karthik Devarajan, PhD, Associate Research Professor
Brian L. Egleston, MPP, PhD, Associate Research Professor Elizabeth Handorf, PhD, Associate Research Professor Suraj Peri, PhD, Assistant Research Professor Yan Zhou, MSE, PhD, Assistant Research Professor Mengying Deng, MS, Research Biostatistician Karen J. Ruth, MS, Senior Research Biostatistician Michael Slifker, MS, Bioinformatician Samuel Litwin, PhD, Associate Professor |
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Contact:
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Location & Phone:
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Reimann R383
215-728-4330 |
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Pricing & Scheduling:
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Contact Ms. Judie Devlin for pricing and scheduling.
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Electronic Request for Service: The preferred method to obtain biostatistics and bioinformatics support is through our short electronic request form or email Eric Ross.
The Biostatistics and Bioinformatics Facility is a shared, institutional resource for biostatistics and bioinformatics consulting and collaboration. We provide rigorous biostatistics and bioinformatics design, analysis and interpretation of experiments and studies, and also create new biostatistics and bioinformatics methods for specific research problems. Our members are broadly skilled in quantitative and computational methods for clinical trials, pre-clinical studies, biological experiments, translational investigations, and cancer prevention and control problems. We embrace new problems and technologies that surface in a rapidly changing scientific environment.
Available software and hardware include:
- Standard statistical packages, such as SAS, Stata and R
- Sample size and power computation applications, including PASS, Solo Power Analysis and custom-written applications
- Tools for methodological research, such as Matlab, Python, Perl, Fortran and C.
- Bioinformatics tools, including Ingenuity Pathway Analysis (IPA), R/Bioconductor, Python/Anaconda, GSEA, Cytoscape, and a large number of public domain tools for analyzing transcriptomic, genomic, and proteomics data.
- A 480-core high performance computing cluster equipped with modules for all stages of NGS data analysis (QC, alignment, variant calling, differential expression, peak calling, annotation, visualization, etc.).
