Bioinformatics-as-a-Service

Bioinformatics as a Service

Vision and mission

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
ChIP-Seq
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

For more information about our services, please send an email to gbsc-baas-team@lists.stanford.edu

Case studies

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)

BaaS Team

Ramesh Nair, PhD

Ramesh, Director of Bioinformatics at SCGPM, heads up the Bioinformatics-as-a-Service resource for the GBSC. 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.

Lyong Heo, MS

2022-present: Lyong is a staff bioinformatician for the BaaS team whose interests are in population genomics, machine learning, and NGS analysis. Prior to joining the GBSC, he was a Computational Biologist at the Van Andel Institute (VAI) in Grand Rapids, MI, where he performed bioinformatic analyses on patients with pediatric acute myeloid leukemia (AML). Prior to that, he was a Research Assistant in GWAS projects on metabolic diseases in population-based cohorts and Korean Reference Genome (KRG) at Korea National Institute of Health. He also managed multi-omics data at the Center for Genome Science in South Korea. Lyong received his Master’s Degree in Computer Science from Chungbuk National University.

Meng Wang, PhD

2022-present: Meng is a senior bioinformatician for the BaaS team whose interests are in developing statistical methods and computational tools to better understand the complexity of biology. She was most recently a research scientist with the Snyder Lab and led the algorithm development in several projects. In the GTEx project, she was in charge of proteomics data analysis and integration, and developed several new algorithms in robust normalization and data-adaptive quantification of tissue-specificity (AdaTiSS). In the project to predict the onset of COVID-19 from wearable device data, she developed both offline and online detection algorithms to detect infection-associated heart rate anomalies from smartwatch data. Meng received her PhD in Mathematical Statistics from the University of California, San Diego.

Workshops & Conferences

2018 Microbiome workshop

2017 Microbiome workshop

2016 Microbiome workshop

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