David Craig serves as Vice-Chair of USC's new Department of Translational Genomics ( http://dtg.usc.edu ) within the USC Keck School of Medicine. Dr. Craig's expertise is in genomics, bioinformatics, and data analysis of high-throughput genomics data. His laboratory consists of both a wet-lab and dry-lab. Within his group, lab personnel have the opportunity to either specialize or become dual trained in bioinformatics and molecular biology.

His group pioneered cost-effective GWAS methods leading to genetic associations reported in Science, Nature Genetics, and New England Journal of Medicine. His publications include some of the most significant papers addressing the challenges of data sharing and data privacy (Homer et al, PLOS Genetics 2008). Since 2006, his group has been developing tools based on NGS beginning with publishing one of the first papers for targeted variant calling in humans (Craig et al Nature Methods, 2008). In the past 8 years, his group has published and collaborated on over 60 NGS publications balanced between the wet and dry-labs. During this time, he has served in several international genomics projects including as PI on a U01 responsible for developing bioinformatic pipelines for the Phase I and Phase II portions of the 1000 Genomes Project.

With collaborators, his group was among the first to implement NGS in molecular profiling for cancer patient treatment recommendations in a feasibility study in metastatic triple negative breast cancer (Craig et al., Mol Cancer Ther. 2013). Building upon this and other efforts his group developed an end-to-end platform for personalized medicine, NGS data management, analysis, and clinical genomic interpretation following CAP/CLIA guidelines. Within this framework, they completed analytical validation for integrated RNA/DNA analysis of tumor/normal sets. Community resources from these efforts included include a collaborative release of COLO829 tumor/normal sequencing reference sets. He also was a founding scientific director for TGen's Center for Rare Childhood Disorders - a research clinic enrolling over 1000 individuals into a study developing integrative RNA/DNA approaches for identifying the germline genetic basis of disease. 

Dr. Craig's laboratory has openings for post-doctoral fellows and graduate students, and can be reached at davidwcr at symbol usc.edu.

Academic Appointments

Associate Professor, Pathology

Associate Professor, Genetics

Member, Bio-X

Member, Cardiovascular Institute

Member, Maternal & Child Health Research Institute (MCHRI)

Administrative Appointments

Director of Genome Informatics, Department of Pathology (2011 - Present)

Professional Education

B.A.Sc., University of British Columbia, Engineering Physics (2002)

Ph.D., University of British Columbia, Genetics (2006)

Stanley F. Nelson, MD is Professor and Vice Chair of Human Genetics and Professor of Psychiatry within the David Geffen School of Medicine at UCLA where he has been on faculty since 1993. Prof. Nelson attended the University of Michigan and obtained a BS degree in Physics in 1982. He graduated from Duke University School of Medicine in 1987 and completed an ITT International Fellowship to Sweden in the Laboratory of George Klein. He was trained in Pediatrics and Pediatric Hematology-Oncology at UCSF School of Medicine, and subsequently trained as a postdoctoral fellow with Patrick Brown from 1990-1993 where he developed genomic mismatch scanning and initiated the lab development of DNA microarrays for genomic applications. At UCLA, Prof. Nelson has continued to be interested in technology development and application of genomics to cancer biology and common human diseases with active research areas in Autism, ADHD, vertigo and brain cancers. He developed and led the first genomics core on UCLA campus ( UCLA DNA Microarray Facility). He led the whole genome expression array analysis for the NIH Neuroscience Blueprint. With a team in Pathology and Pediatrics, he implemented whole exome sequencing for clinical purposes in 2011.  He formed the Center for Duchenne Muscular Dystrophy in 2007 with Drs. Miceli and Spencer that has grown into a unique center that provides coordinated patient care, access to clinical trials, translational and basic research, and educational opportunities on campus.  In 2014, he initiated with others, the Undiagnosed Diseases Network UCLA Clinical Site to improve diagnosis of individuals with difficult to diagnose genetic disorders.  His laboratory continues to develop and use genomic techology to pursue biological insights that lead to new therapeutic interventions in humans. 

Faculty Pending, Department of Genetics
Director, Center for Translational Bioinformatics, Institute for Biomedical Informatics (IBI),
Associate Director for Bioinformatics, Institute for Biomedical Informatics (IBI),
Associate Director, Center for Precision Medicine

University of Pennsylvania

Dr. Marylyn Ritchie, PhD is a new faculty member in the Department of Genetics at the University of Pennsylvania, Perelman School of Medicine.  She is also the Associate Director of Bioinformatics and the Director of a new Center for Translational Bioinformatics at Penn.

Dr. Ritchie is a statistical and computational geneticist with a focus on understanding genetic architecture of complex human disease.  She has expertise in developing novel bioinformatics tools for complex analysis of big data in genetics, genomics, and clinical databases, in particular in the area of Pharmacogenomics.  Dr. Ritchie has received several awards and honors including selection as a Genome Technology Rising Young Investigator in 2006, an Alfred P. Sloan Research Fellow in 2010, a KAVLI Frontiers of Science fellow by the National Academy of Science from 2011-2014, and she was named one of the most highly cited researchers in her field by Thomas Reuters in 2014.  Dr. Ritchie has extensive experience in all aspects of genetic epidemiology and translational bioinformatics as it relates to human genomics.  She also has extensive expertise in dealing with big data and complex analysis including GWAS, next-generation sequencing, data integration of meta-dimensional omics data, Phenome-wide Association Studies (PheWAS), and development of data visualization approaches.

Kaitlin is currently a postdoctoral fellow involved with both the Deciphering Developmental Disorders (DDD) and DECIPHERprojects. Her work is focused on studying and understanding the patterns of rare variation that contribute to disease.

Brian Shirts M.D., Ph.D.

Assistant Professor

Department of Laboratory Medicine

University of Washington Medical Center

Clinical Positions

Associate Director, Genetics Division, Laboratory Medicine

Assistant Director, Informatics Division, Laboratory Medicine

My research focuses on integrating complex genetics knowledge into clinical care. There are several related aspects of this research:

1. Research on clinical classification of rare variants of uncertain significance, particularly variants in familial cancer genes.

We are developing optimal family-based methods to classify variants of uncertian significance with small to medium sized families.

We are investigating practical and ethical issues surrounding patient-driven pedigree building for variant classification.

We have launched an online guide to help patients and genetic counselors understand family analysis for variant classification: findmyvariant.org

2. Research on the storage and communication of genetic information in the health care setting. This includes formatting genetic test results so that they are searchable in clinical laboratory information systems and so that electronic health records can use genetics to provide active decision support.

3. Research on improving the use of complex and multifactorial clinical information, with special interest in personalized healthcare using genetic information.

We are developing statistical methods to integrate quantitative diagnostic information with genetic information.

We are investigating methods to identify when genetic information is clinically useful and when it may not be clinically useful despite clear biological associations.

In related clinical projects we have worked to evaluate laboratory test ordering patterns, to develop content for online decision support tools, and to implement complex and interactive test reports.