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Computational Biology Resource Center

MUSC Bioinformatics Core (MBC)

Scientific Director:
Gerard (Gary) T Hardiman, PhD
Professor, Division of Nephrology, Department of Medicine
Phone: 843-792-0771
E-Mail: hardiman@musc.edu
Location: 135 Cannon Street, Suite 303 MSC 835

Associate Director:
E. Starr Hazard, Ph.D.
Associate Professor, Library, Biochemistry and Molecular Biology
Director, Computational Biology Resource Center
E-Mail: hazards@musc.edu
Phone: 792-0715
Location: BSB 101H

The MUSC Bioinformatics Core (MBC) provides state of the art bioinformatics analysis for genomic and epigenomic assays and supports the research goals of MUSC investigators. A range of bioinformatics services that have proven to be transformative in enabling investigators to advance disease-related research goals are offered. An emphasis will be placed on strengthening local bioinformatics resources, leveraging state resources (including the high-performance Palmetto computing (HPC) resource at Clemson University), and reducing barriers to utilization of bioinformatics tools by the MUSC community.


Computational Infrastructure:
The MBC houses a high performance compute cluster (HPCC) which consists of a 16 node 132 central processing unit computing cluster combined with terabit storage capacity. The HPCC Current capacity is 35 TB of fiber channel storage on an XFS file system with an expandable storage capacity up to 16 exabytes. In addition to 35TB of local storage for computational analyses, 64 TB of dedicated SAN storage is available for data archival. Analysis tools include commercial software packages such as Partek® Flow™ and Genomics Suite™ in addition to a variety of open source tools.


The MBC will support

1.  Experimental Design
Bioinformatics support for assistance with experimental design, choice of technological platform, data analysis and data quality control.

2.  High-Performance Computing Resources
Access to High-performance computing (HPCC) resources, systems administration and infrastructure for data storage, backup and mining.

3.  Expression Microarray Technology
Analyses of conventional Affymetrix and Illumina expression microarray platforms for genome wide analysis of gene expression.

4. Bioinformatics Support for High-Throughput Sequencing Assays.
High-throughput sequencing data analysis for Illumina HiSeq 2500 and Miseq platforms, whole genome sequencing (WGS), RNA sequencing (RNAseq), microRNA sequencing (miRNAseq), chromatin immunoprecipitation linked to massively parallel sequencing (ChIP-Seq), MethylC-sequencing, capture based sequencing (exome/focused panel) and metagenomics (16S rRNA gene sequencing). 

5.  Training and Consultation: User Interface
Consultation and training of students, postdoctoral fellows, investigators and technical staff regarding high-throughput sequencing methodologies and data analysis will be provided. 
 

 
 
 

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