About Us

The Sanders Lab aims to refine the diagnosis and management of prenatal and childhood disorders using genomic technologies, including exome sequencing, whole-genome sequencing and RNA-seq. We have used these approaches to identify over 100 genes associated with autism spectrum disorder and to illuminate the role of noncoding elements in human disorders. Our research often involves large groups of collaborators to collect the large-scale data and broad expertise necessary to make insights. This led to the creation of authorlist.org to help ensure everyone received credit for the work.

Stephan Sanders

Script Creator



Dr. Sanders trained as a pediatric physician in the UK before undertaking a PhD and postdoctoral research position at Yale. He is now an Assistant Professor at UCSF in the Department of Psychiatry. His research focuses on using genomics and bioinformatics to understand the etiology of developmental disorders, such as Autism Spectrum Disorder (ASD).
As a member of Dr. Matthew State’s lab, he worked with the Simons Simplex Collection Genomic Consortium (SSCGC) to quantify the role of de novo copy number variants (CNVs) in ASD, including discovering that de novo duplications at 7q11.23 are an ASD risk factor (Sanders et al. Neuron 2011). He also used exome sequencing to show that de novo protein-truncating variants PTVs (also called loss-of-function (LoF) mutations) are associated with ASD.

Read More This analysis established a statistical framework for identifying the specific genes involved in ASD pathology, based on these de novo events, discovering that the voltage-gated sodium channel SCN2A is an ASD risk gene (Sanders et al. Nature 2012). Working with collaborators, he helped develop this approach to gene discovery further (He et al. PLoS Genetics 2013; Samocha et al. Nature Genetics 2014) and apply it to larger ASD cohorts (De Rubeis et al. Nature 2014, Iossifov et al. Nature 2014, Dong et al. 2014). Combining data from the Simons Simplex Collection (SSC), Autism Sequencing Consortium (ASC), and the Autism Genome Project (AGP), Dr. Sanders’ work identified 65 ASD-associated genes and 6 ASD-associated CNV loci (Sanders et al. Neuron 2015). In addition, by comparing the CNV and exome data, this analysis showed that a single critical gene is often present in small de novo deletions (e.g. ≤7 genes), whereas large de novo CNVs tend to contain multiple risk genes of lower effect.
As a PI, Dr. Sanders co-leads the whole-genome sequencing (WGS) working group of the ASC with Michael Talkowski. This group developed the Category-Wide Association Study (CWAS) approach to WGS analysis, which provides a framework to define and account for the multiple comparisons inherent to these analyses (Werling et al. Nature Genetics 2018). He is also a member of the Whole-Genome Sequencing in Psychiatric Disorders (WGSPD) steering group, which seeks to integrate WGS data across multiple disorders to maximize power (Sanders et al. Nature Neuroscience 2018).
His lab has helped understand the role of SCN2A mutations in human disorders. In collaboration with Dr. Kevin Bender, he showed that loss-of-function variants that reduce neuronal excitability lead to ASD and developmental delay, while gain-of-function variants that increase neuronal excitability lead to infantile seizures (Ben-Shalom et al. Biological Psychiatry 2017). The loss-of-function mutations also impact back-propagation of the action potential and synaptic plasticity (Spratt et al. BioRxiv 2018), potentially opening an avenue to future therapeutics, as discussed in the review written in collaboration with the SCN2A family group and numerous researchers (Sanders et al. Trends in Neuroscience 2018).
Dr. Sanders is the Director of the Psychiatry Department Bioinformatics Core (PsychCore) at UCSF, a member of the SPARK medical genetics committee, the Autism Science Foundation Scientific Advisory Board, and an Assistant Editor for the Journal of Neurodevelopmental Disorders.

Claudia Dastmalchi

Website Creator



As a staff bioinformatics programmer in the Sanders Lab’s Psychiatry Bioinformatics Core (PsychCore), Claudia’s main focus has been on co-developing an automated, cloud-based NGS pipeline that can take in raw sequencing data, call variants, and conduct downstream analyses on these variants for large scale samples. This has required the integration and thorough understanding of AWS, Google Cloud Platform, and Hail. Previously, Claudia studied Biotechnology in graduate school, during which she engaged in an internship with the responsibility of processing mutation data from variant databases (HGMD, ClinVar, OMIM, Uniprot) and identifying disease connections at the molecular level (mainly protein domains). Claudia’s main passion has been in transforming healthcare by using computational tools to gain beneficial insight from genomic data and ultimately influence personalized medicine.