Bioinformatics as a Service
Vision and mission
NEWSFLASH: We are hiring new bioinformaticians for this service! For more details, see our posting on the Stanford Careers website. Apply today!
Our goal with Bioinformatics-as-a-Service (BaaS) is to help Stanford labs do cutting-edge bioinformatics data analysis without a significant investment in laboratory personnel. The bioinformaticians supporting this service are embedded with Stanford Center for Genomics & Personalized Medicine (SCGPM) Bioinformatics Team. Members of this team support various large-scale genomics projects at Stanford, including Stanford Sequencing Service Center, ENCODE, Integrative Personal Omics Profiling, Human Microbiome Project, Stanford Clinical Genomics Service, CIRM Center of Excellence for Stem Cell Genomics and the VA's Million Veteran Program. You can be assured that you are getting the best practice that Stanford has to offer. And Stanford is indeed the best in bioinformatics.
Services offered in pipeline development, secondary and tertiary analysis, data interpretation, and training. We support NGS data types like:
- RNA-Seq including single cell and with synthetic spike-ins
- DNA-Seq including Whole Genome Sequencing, Whole Exome Sequencing, Deep Sequencing (Gene panels) and Cancer Seq (Germline and somatic)
- Microbiome Seq
- Uncommon data types such as ATAC-seq, Hi-C, Methyl-Seq
The descriptions are minimized to preserve research confidentiality. Please follow links for publicly disclosed information.
Understanding birth defects by investigating meiosis with Hi-C
Villenueve lab investigates mechanisms underlying the faithful inheritance of eukaryotic chromosomes and focuses on elucidating the events required for orderly segregation of homologous chromosomes during meiosis, the crucial process by which diploid germ cells generate haploid gametes. Understanding these events is of central importance to sexually reproducing organisms, since errors in meiosis lead to chromosomal aneuploidy, one of the leading causes of miscarriages and birth defects in humans. Hi-C is a variant of the 3-C (Chromosome conformation capture) technology that uses crosslinking and ligation to detect proximity between DNA sequences within the cell nucleus on a genome-wide basis. BaaS services implemented a Hi-C data processing pipeline that the laboratory can use to analyze DNA organization during meiosis in C. elegans. (more)
Effect of drug on huntington’s disease using RNA-Seq
Huntington’s disease is a progressive, fatal neurological disorder with no cure. It’s genetic, and a child of an affected parent has a 50 percent chance of also developing the condition. In an international collaboration, researchers at the National Yang-Ming University in Taiwan and Stanford’s School of Medicine discovered a protein that may one day be a viable therapeutic target for those afflicted with the condition. Our bioinformatics service provided analysis for an RNA-Seq study done to examine global gene expression patterns in healthy individuals and Huntington's disease patients with and without drug treatment is providing insights into a possible mode of action. (more)
Investigating skin cancer using whole exome sequencing
Immune suppressing drugs are taken during transplant, and for chronic autoimmune disorders, such as celiac disease, Crohn’s disease, Graves’ disease, lupus, and rheumatoid arthritis. These drugs can increase risk of skin cancer. Stanford High-Risk Skin Cancer Clinic serves as an early-warning system, a frontline defense and, if need be, an all-hands-on-board diagnosis and treatment center. Our bioinformatics service has been supporting physicians at the Clinic in the analysis of whole exome sequencing of squamous cell skin cancer to offer clues of phenotype-driven variant signatures in terms of the implicated genes. (more)
Genetic architecture of cardiomyopathy
Both familial hypertrophic cardiomyopathy (HCM) and dilated cardiomyopathy (DCM) are prevalent hereditary cardiac disorder linked to arrhythmia and sudden cardiac death. Joseph Wu's lab seeks to elucidate the mechanisms underlying HCM and DCM development for the purposes of modeling these 2 prevalent diseases using RNA-Seq, single-cell RNA-Seq studies and whole genome sequencing studies. BaaS services are helping with data analysis and interpretation. (more)
Understanding drug induced developmental toxicity
One oral pharmaceutical drug is used for treatment of skin acne, and is also known to be a teratogen that causes heart malformations in newborns. In this study of Snyder Lab, molecular mechanisms underlying this drug induced developmental toxicity in cardiomyocyte differentiation were investigated using both human induced pluripotent stem cells and human embryonic stem cells. BaaS is helping the analyses of genome-wide transcriptomic profiling by RNA-seq and dynamics of open-chromatin profiling by ATAC-seq. The analysis revealed that multiple signaling pathways with respect to early-stage development are involved. Results from this study are expected to broaden our knowledge of the congenital diseases of newborns that arise as a result of maternal drug exposure during the pregnancy.
Vascular biology of atherosclerosis using single-cell RNA-Seq
Atherosclerosis is deposition of fatty substances along arterial walls form atherosclerotic plaques that become brittle and vulnerable to rupture, and ultimately cause heart attack and stroke. In collaboration with investigators at the David Geffen School of Medicine at UCLA and the Icahn School of Medicine in New York City, Stanford has discovered anti-tumor antibodies that could counter atherosclerosis. Our bioinformatics service provided analyses of single-cell RNA-Seq data on the vascular biology of atherosclerosis disease to detect cell subpopulations and heterogeneity and is providing fundamental insights into the field of vascular biology of this heart disease. (more)
Probing aging using parabiosis and RNA-Seq
Wyss-Coray lab conducts research on neurodegeneration and age-related changes in the brain. RNA-Seq techniques are applied by the lab to study the transcriptional profile during normal aging and impact during parabiosis, a process in which mice are surgically connected to share blood circulation. The lab utilized our services to train its researchers to do best practice RNA-Seq analysis including individual sample quality assessment, read mapping, gene expression quantification, differently expressed genes detection, splice variant analysis, heat map generation, visualization of mapped reads using the integrative genomics viewer, and Gene Ontology term and pathway enrichment functional analysis. (more)
Understanding immune responses using single cell RNA-Seq
CD4+ T cells (TMPS) are known to be very important for most immune responses, but their precise role in the context of influenza vaccination and protection is not well understood. In collaboration with Howard Hughes Medical Institute, Mark Davis' lab is characterizing the time course with which specific TMPS appear in infants and children and also analyze whether their rise is continuous, or spikes with major vaccinations, acquisition of a microbiome or disease exposure. BaaS services help Davis lab analyze single T-cell RNA-sequencing of murine and human T cell receptors. (more)
Function of long non-coding RNA
Kirkegaard Lab works on the function of a long non-coding RNA (Nettoie Salmonella pas Theiler’s, NeST) that affects pathogen susceptibility and is likely to function by recruiting activating chromatin modification complexes. The lab's working hypothesis is that the lncRNA is ultimately anti-inflammatory. They have recently developed mice that are knockouts for the NeST promoter, and these mice show increased susceptibility to the pathogenesis of dengue, poliovirus, and Plasmodium infection. BaaS team is helping Kirkegaard Lab interpret RNA-seq data on T cells before and after infection. (more)
Type 2 Diabetes and RNA-Seq
Genome wide association studies have identified approximately 400 genes with an increased incidence in type 2 diabetic patients. It is hypothesized that nucleotide polymorphisms within or near the coding region of these ‘candidate’ diabetes risk genes can suppress or enhance gene function resulting in an increased likelihood of developing T2D. Using screening tools in Drosophila, Seung Kim's lab have identified a group of 9 candidate genes which may potentially be involved in maintaining beta cell function. BaaS is helping the project focusing on one of these candidate genes, a repressive transcription factor with no known role in human beta cell function. When this gene was knocked-down in primary human islets Kim Lab observed a significant enhancement in basal and glucose-stimulated insulin secretion. BaaS is helping with RNA-seq analysis in order to understand the pathways/downstream candidates regulated by this gene which would explain the phenotype of enhanced insulin secretion. (more)
Ramesh Nair, PhD
Ramesh, Acting Director of Bioinformatics at SCGPM, heads up the Bioinformatics-as-a-Service resource for the GBSC, and is the bioinformatician-in-residence for the CIRM-initiated Stem Cell Center of Excellence (CESCG) where he is responsible for diverse bioinformatics needs for the Center Initiated Projects and its extensive collaboration network. Prior to joining SCGPM, Ramesh was a Bioinformatics Analyst at Center for Cancer Systems Biology (CCSB) where among other things, he was sole developer of next-generation sequencing (NGS) pipelines for genome sequencing (Exome-Seq) applied to follicular lymphoma and transcriptome sequencing (RNA-Seq) applied to lung cancer tumor microenvironment. Prior to joining Stanford, he was a Sr. Scientist at various Biotech firms in Bay Area including Cobalt Biofuels, Iconix BioSciences (now Entelos), Lynx Therapeutics (now Illumina) and DuPont. Ramesh has a PhD in Chemical Engineering from Northwestern University and MTech in Biochemical Engineering and Biotechnology from Indian Institute of Technology Delhi.
Wenyu Zhou, PhD
Wenyu is a Bioinformatics Scientist at SCGPM dedicated to BaaS. She recently finished her post-doctorate training with Dr. Michael Snyder at Stanford University. With Dr. Snyder, she studies Type 2 Diabetes (T2D) and utilizes multi-omic techniques to measure both host and microbial molecular changes over time and to understand underlying associations with the disease onset and development. She led the Integrative Personal Omics Profiling (iPOP, http://med.stanford.edu/ipop.html) project over the last five years, and has expertise in analyzing different types of high-throughput data (NGS, mass-spec based and others) and applying statistical modeling and visualization techniques. Wenyu has first-authored research articles published in internationally reputable journals, such as Nature, Cell Stem Cell, Cell Systems and EMBO Journal, and actively serves as a reviewer for a number of scientific journals in the genomics field. Wenyu received her PhD in Biology from the University of Washington at Seattle in 2012.
Gao Zhou, PhD
Gao is a Bioinformatics Scientist at SCCPM dedicated to BaaS. Gao has broad knowledge in computational biology, bioinformatics and molecular biology. He has hands-on experience in analyzing different types of next generation sequencing (NGS) data. He has expertise in machine learning and algorithm development. He enjoys applying, defining and validating computational approaches to deliver important biological insights. Prior to joining SCGPM, Gao has been part of the wearable team in Snyder Lab who performed the first systematic analysis and demonstrated the power of using wearable and portable for monitoring human and early detection of inflammatory diseases and diabetes. Gao has a PhD in Biomaterial Science from University of Toronto in Canada.