Bioinformatics
Overview
The Bioinformatics Shared Resource provides cutting-edge computational and systems biology support to the Institute and its NCI-designated Cancer Center. We specialize in omics data analysis, multi-omics data integration, network and pathway analysis, and machine learning. Different levels of data analyses are provided, based on the complexity of researchers’ data sets. This may include automated pipeline-based analyses, customized deep data mining, development and application of machine learning models, and hypothesis driven in-silico drug discovery. Our focus is to help researchers put data into biological contexts across various disease areas, and to create testable hypotheses and understandable biological processes.
We also provide Bioinformatics classes and training for the entire Cancer Center and Sanford Burnham Prebys community. Both internal and external customers are charged at assigned hourly rates.
The areas we focus on include:
- Data mining of Next Generation Sequencing (NGS) data sets, including:
- RNA-Seq, ChIP-Seq, ATAC-Seq, DNA Methylation etc.
- Single-cell RNA and ATAC (10X platforms, PIP-seq, etc.)
- Spatial transcriptomics including 10X Genomics Visium and Visium HD, CosMX, GeoMX
- Data integration of transcriptomics, genomics, proteomics, and epigenomics data sets
- Network and pathway analyses using customized algorithms and commercially available software, including Ingenuity Pathway Analysis, GSEA, etc.
- Machine learning applications and implementation
- Drug screening data analysis
- Biostatistics
- Data management and upload (GEO/SRA and ProteomeXchange)
- Training and consultation on bioinformatics
- Grant and letter-of-support writing services
Services
Assistance is provided in the following areas:
- Transcriptomics
Bulk RNA-seq, Microarray, nanoString nCounter, miRNA-seq, and single-cell RNA-seq) Data pre-processing (alignment and quantification using Nextflow pipelines), data QC/QA, differential gene expression, pathway and network analysis, report generation and visualization using Shiny apps. - Spatial transcriptomics
(Visium and Visium HD, nanoString GeoMX and CosMX) Data pre-processing using proprietary pipelines and analysis. - Epigenomics
(ChIP-seq, ATAC-seq, Cut&Run, Cut&Tag, DNA methylation, single-cell ATAC-seq) Data pre-processing (alignment, filtering), QC/QA, peak calling, differential binding/accessibility analysis, motif search, visualization using IGV/UCSC Genome Browser, pathway and network analysis. - Proteomics
(Global and phosphoproteomics) Data pre-processing (summarization and normalization), QC/QA, missing data imputation, differential expression analysis, pathway and network analysis. - Variant calling
(WGS, Exome-seq, SNP array) Data pre-processing (alignment, filtering), variant calling, variant annotation and filtering, visualization. - Functional Genomics
(CRISPR screening) Data pre-processing (alignment, filtering) and normalization, gene essentiality scoring, pathway/network analysis.
Other areas:
- Manuscript preparation: (Custom high-quality figure generation, manuscript writing)
- Custom code (Python/R) and algorithm development
- Biostatistics: (Study design, power analysis, survival analysis, etc.)
- Data management: (Sequencing and proteomics data) Metadata and data management, data submission to NCBI GEO and ProteomeXchange.
- Training: (Bioinformatics classes, training, and tutorials)
Rabi Murad, PhD
(858) 795-5200 ext. 4008
rmurad@sbpdiscovery.org
Equipment & Resources
We have advanced hardware (dedicated server with RStudio server installed for large single cell and spatial omics analysis, HPC clusters, and large collection of software to solve your research problems. The software collections include commercially licensed software suites, including Ingenuity Pathway Analysis (IPA), TRANSFAC; and open source software and databases such as Cytoscape, Broad Institute’s Genome Analysis ToolKit (GATK), GSEA; and customized algorithm and pipeline development using R/Bioconductor and Python. We actively use data from public databases (GEO, TCGA, CCLE, DepMap, and other sources) for biomarker discovery, survival analysis and predictive modeling. We have constructed automated computational pipelines using best-practices for RNA-seq, ChIP-seq, ATAC-seq, CRISPR screening, etc. We use Nextflow pipelines for better reproducibility of analyses.
Price List
For price and cost estimate, please call (858) 795-5200 ext. 4008 or email rmurad@sbpdiscovery.org.
| Bioinformatics Services | Internal Subsidized | Internal | External Non-Profit | External For-Profit | |
|---|---|---|---|---|---|
| Bioinformatics Custom Data Analysis/Application | hour | $50 | $62.50 | $67.50 | $131.50 |
| Statistics data Analysis | hour | $50 | $62.50 | $67.50 | $131.50 |
Leadership
Rabi Murad, PhD
Director
rmurad@sbpdiscovery.org
Contact
Dr. Rabi Murad specializes in applying integrative genomics and epigenomics techniques for biomarker discovery in developmental biology, microRNA biology, and cancer. He has contributed to diverse projects such as genome/transcriptome assembly, functional annotation, gene expression profiling including at single cell level, microRNA profiling, and epigenomics profiling such as ChIP-seq and ATAC-seq. Dr. Murad received his PhD in biological sciences from University of California Irvine, where he received extensive training in applying genomics and bioinformatics techniques to diverse questions in developmental biology and cancer. As part of the ENCODE consortium, his work led to near comprehensive profiling and characterization of microRNAs during mouse embryonic development. He has contributed to several scientific papers published in prominent genome biology journals such as Genome Research and BMC Genomics as well as in Science and Nature.
Yuk-Lap (Kevin) Yip, PhD
Scientific Director
(858) 795-5102
kyip@sbpdiscovery.org
Please call (858) 795-5200 ext. 4008 or use the button below to send us an email.