Bioinformatics Facility

Overview

The Bioinformatics Shared Resource continuously develops new and efficient approaches to data analysis as a response to emerging research needs. Facility functions include: statistical analyses and computational modeling; advanced bioinformatics tools for integrative cancer biology; and data management. Routine data analyses include large scale information datasets (-omics data) generated by high-throughput technologies, which address the following areas:

Gene expression (bulk and single-cell RNA-seq, spatial transcriptomics, smRNA-seq, Nanostring, legacy microarrays)
Gene regulation (ChIP-seq, CUT&RUN, ATAC-seq, epigenetic profiling, methylation assays)
Screening technologies (CRISPR, shRNA, small molecule screening)
3D genome organization (HiC, Hi-ChIP)
Genome and transcriptome sequencing (alternate splicing, RNA editing, mutation detection, CNV, LOH)
Biomarkers (discovering markers in mRNA, miRNA and protein expression data)
Proteomic analyses (mass spectrometry-based spectra, LCMS, DIGE, RPPA, spatial proteomics, etc.)
Pathway and network analysis
Integration of multi-platform data
Other customized data analysis projects

Services

High-throughput data analysis:
- Next generation sequencing data analysis
- Single cell RNA-seq
- Spatial transcriptomics, sequencing-based (GeoMx)
- Spatial transcriptomics, microscopy single-cell (CosMx)
- Hybridization platforms (Nanostring, microarrays)
- Low-density PCR arrays (mi-RNA, pathways, custom)
- Proteomics and metabolomics data
- CRISPR, shRNA, molecular screening
- Enrichment Analysis (Ingenuity, GSEA, DAVID, Enrichr)
Comprehensive analysis of complex projects that require multi-platform data integration
Consultation and support of experimental design and customized bioinformatics services
Statistical consultation and predictive model building
Computational support for data management, high performance computing, and custom programming
Centralized computation resources, including data management and collaboration tools, sequence databases, homology algorithms, and other sequence manipulation tools
Web-based application/database development and management
Training: Ingenuity, Genome Browser(s), DAVID, GSEA
Grant and publication support: results, methods, figures
Advanced biological models and illustrations

Equipment and Features

High-performance computational clusters
GPU-enabled cluster nodes
Integrated Wistar IT infrastructure
Dedicated servers
Access to storage and backup

Pricing

For pricing information, visit iLab or contact the managing director.

This facility is supported in part by a Cancer Center Support Grant (CCSG) awarded by the National Cancer Institute (NCI) to the Ellen and Ronald Caplan Cancer Center.

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How to Acknowledge Our Shared Resources in Your Publications and Grants

Shared Resources Acknowledgements