Bioinformatics Shared Resource Core VCU Massey Cancer Center

Mission

Bioinformatics has become an indispensable component to support the interpretation of Big Data collected in a broad range of cancer research. The mission of the Bioinformatics Core at Massey Cancer Center is to provide a comprehensive, high-quality and cost-efficient bioinformatics service infrastructure to support Massey researchers in basic science, translational research and cancer control.

Through collaborative interactions with MCC members, the core supports the analysis of high-throughput multi-omics data with state-of-the-art bioinformatics algorithms and pipelines, facilitate the access and mining of public cancer datasets, support grant applications and provide consultation and training to cancer center members and trainees.

Acknowledge the Bioinformatics Core

All publications that include results, services or products generated by the VCU Massey Cancer Center Shared Resources must include the following acknowledgement in the manuscript:

"Services and products in support of the research project were generated by the VCU Massey Cancer Center [insert name of core] Shared Resource, supported, in part, with funding from NIH-NCI Cancer Center Support Grant P30 CA016059."

PubMed Central (PMC) ID numbers are required for those publications that use CCSG-supported shared resources. All of Massey Cancer Center's Shared Resources are supported by the CCSG.

This Shared Resource is jointly supported by VCU Massey Cancer Center and the Office of the Vice President for Research and Innovation.

Data Types	Services
Whole genome/exome sequencing	Somatic mutation and germline mutation calling, copy number variation, structure variations and genome rearrangement
Transcriptome sequencing with RNA-seq and Nanostring ncounter	Differential gene expression profiling, differential splicing analysis, detection of abnormal RNA transcripts
Single cell sequencing (scRNA-seq) and spatial transcriptomics	Cell clustering, cell type identification, differential expression analysis, cell trajectory analysis, pseudo-time analysis
Epigenetic sequencing (CHIP-seq and bisulfite sequencing)	DNA-binding site identification with CHIP-seq, CpG island identification, differential methylation analysis
Array-based technologies	Differential expression analysis, genome wide association analysis
Proteomic and Metabolomics	Differential abundance analysis, dimensionality reduction and clustering.
Gene ontology and pathway enrichment analysis	Gene set enrichment analysis with biological categories or pathways supported using GSEA and IPA
Others	Analysis of 3rd-generation sequencing data generated by PacBio or Nanopore technologies

Data Types	Services
Whole genome/exome sequencing	Somatic mutation and germline mutation calling, copy number variation, structure variations and genome rearrangement
Transcriptome sequencing with RNA-seq and Nanostring ncounter	Differential gene expression profiling, differential splicing analysis, detection of abnormal RNA transcripts
Single cell sequencing (scRNA-seq) and spatial transcriptomics	Cell clustering, cell type identification, differential expression analysis, cell trajectory analysis, pseudo-time analysis
Epigenetic sequencing (CHIP-seq and bisulfite sequencing)	DNA-binding site identification with CHIP-seq, CpG island identification, differential methylation analysis
Array-based technologies	Differential expression analysis, genome wide association analysis
Proteomic and Metabolomics	Differential abundance analysis, dimensionality reduction and clustering.
Gene ontology and pathway enrichment analysis	Gene set enrichment analysis with biological categories or pathways supported using GSEA and IPA
Others	Analysis of 3rd-generation sequencing data generated by PacBio or Nanopore technologies