Richard Chen, M.D., is a Clinical Instructor of Dermatology at Stanford and Chief Scientific Officer at Personalis, Inc. He attended medical school and completed residency at Stanford University, serving as Chief Resident in his final year. His interests include general dermatology, genetics, bioinformatics and technology innovation for improved health care delivery.
- Genetics, bioinformatics and technology innovation for improved health care delivery
Clinical Instructor, Dermatology
Internship:Santa Clara Valley Medical Center Radiology Residency (2008) CA
Board Certification: Dermatology, American Board of Dermatology (2011)
Medical Education:Stanford University - CAPS (2007) CA
Residency:Stanford University - Dept of Dermatology (2011) CA
- Genetic analysis in a patient with nine primary malignant neoplasms: A rare case of Li-Fraumeni syndrome ONCOLOGY REPORTS 2016; 35 (3): 1519-1528
- Disease Variant Landscape of a Large Multiethnic Population of Moyamoya Patients by Exome Sequencing G3-GENES GENOMES GENETICS 2016; 6 (1): 41-49
- Achieving high-sensitivity for clinical applications using augmented exome sequencing GENOME MEDICINE 2015; 7
Achieving high-sensitivity for clinical applications using augmented exome sequencing.
2015; 7 (1): 71-?
Whole exome sequencing is increasingly used for the clinical evaluation of genetic disease, yet the variation of coverage and sensitivity over medically relevant parts of the genome remains poorly understood. Several sequencing-based assays continue to provide coverage that is inadequate for clinical assessment.Using sequence data obtained from the NA12878 reference sample and pre-defined lists of medically-relevant protein-coding and noncoding sequences, we compared the breadth and depth of coverage obtained among four commercial exome capture platforms and whole genome sequencing. In addition, we evaluated the performance of an augmented exome strategy, ACE, that extends coverage in medically relevant regions and enhances coverage in areas that are challenging to sequence. Leveraging reference call-sets, we also examined the effects of improved coverage on variant detection sensitivity.We observed coverage shortfalls with each of the conventional exome-capture and whole-genome platforms across several medically interpretable genes. These gaps included areas of the genome required for reporting recently established secondary findings (ACMG) and known disease-associated loci. The augmented exome strategy recovered many of these gaps, resulting in improved coverage in these areas. At clinically-relevant coverage levels (100 % bases covered at ≥20×), ACE improved coverage among genes in the medically interpretable genome (>90 % covered relative to 10-78 % with other platforms), the set of ACMG secondary finding genes (91 % covered relative to 4-75 % with other platforms) and a subset of variants known to be associated with human disease (99 % covered relative to 52-95 % with other platforms). Improved coverage translated into improvements in sensitivity, with ACE variant detection sensitivities (>97.5 % SNVs, >92.5 % InDels) exceeding that observed with conventional whole-exome and whole-genome platforms.Clinicians should consider analytical performance when making clinical assessments, given that even a few missed variants can lead to reporting false negative results. An augmented exome strategy provides a level of coverage not achievable with other platforms, thus addressing concerns regarding the lack of sensitivity in clinically important regions. In clinical applications where comprehensive coverage of medically interpretable areas of the genome requires higher localized sequencing depth, an augmented exome approach offers both cost and performance advantages over other sequencing-based tests.
View details for DOI 10.1186/s13073-015-0197-4
View details for PubMedID 26269718
View details for PubMedCentralID PMC4534066
Disease Variant Landscape of a Large Multiethnic Population of Moyamoya Patients by Exome Sequencing.
G3 (Bethesda, Md.)
2015; 6 (1): 41-49
Moyamoya disease (MMD) is a rare disorder characterized by cerebrovascular occlusion and development of hemorrhage-prone collateral vessels. Approximately 10-12% of cases are familial, with a presumed low penetrance autosomal dominant pattern of inheritance. Diagnosis commonly occurs only after clinical presentation. The recent identification of the RNF213 founder mutation (p.R4810K) in the Asian population has made a significant contribution, but the etiology of this disease remains unclear. To further develop the variant landscape of MMD, we performed high-depth whole exome sequencing of 125 unrelated, predominantly nonfamilial, ethnically diverse MMD patients in parallel with 125 internally sequenced, matched controls using the same exome and analysis platform. Three subpopulations were established: Asian, Caucasian, and non-RNF213 founder mutation cases. We provided additional support for the previously observed RNF213 founder mutation (p.R4810K) in Asian cases (P = 6.01×10(-5)) that was enriched among East Asians compared to Southeast Asian and Pacific Islander cases (P = 9.52×10(-4)) and was absent in all Caucasian cases. The most enriched variant in Caucasian (P = 7.93×10(-4)) and non-RNF213 founder mutation (P = 1.51×10(-3)) cases was ZXDC (p.P562L), a gene involved in MHC Class II activation. Collapsing variant methodology ranked OBSCN, a gene involved in myofibrillogenesis, as most enriched in Caucasian (P = 1.07×10(-4)) and non-RNF213 founder mutation cases (P = 5.31×10(-5)). These findings further support the East Asian origins of the RNF213 (p.R4810K) variant and more fully describe the genetic landscape of multiethnic MMD, revealing novel, alternative candidate variants and genes that may be important in MMD etiology and diagnosis.
View details for DOI 10.1534/g3.115.020321
View details for PubMedID 26530418
View details for PubMedCentralID PMC4704723
Transcriptome sequencing in Sezary syndrome identifies Sezary cell and mycosis fungoides-associated lncRNAs and novel transcripts
2012; 120 (16): 3288-3297
Sézary syndrome (SS) is an aggressive cutaneous T-cell lymphoma (CTCL) of unknown etiology in which malignant cells circulate in the peripheral blood. To identify viral elements, gene fusions, and gene expression patterns associated with this lymphoma, flow cytometry was used to obtain matched pure populations of malignant Sézary cells (SCs) versus nonmalignant CD4(+) T cells from 3 patients for whole transcriptome, paired-end sequencing with an average depth of 112 million reads per sample. Pathway analysis of differentially expressed genes identified mis-regulation of PI3K/Akt, TGFβ, and NF-κB pathways as well as T-cell receptor signaling. Bioinformatic analysis did not detect either nonhuman transcripts to support a viral etiology of SS or recurrently expressed gene fusions, but it did identify 21 SC-associated annotated long noncoding RNAs (lncRNAs). Transcriptome assembly by multiple algorithms identified 13 differentially expressed unannotated transcripts termed Sézary cell-associated transcripts (SeCATs) that include 12 predicted lncRNAs and a novel transcript with coding potential. High-throughput sequencing targeting the 3' end of polyadenylated transcripts in archived tumors from 24 additional patients with tumor-stage CTCL confirmed the differential expression of SC-associated lncRNAs and SeCATs in CTCL. Our findings characterize the SS transcriptome and support recent reports that implicate lncRNA dysregulation in human malignancies.
View details for DOI 10.1182/blood-2012-04-423061
View details for Web of Science ID 000311619200020
View details for PubMedID 22936659
View details for PubMedCentralID PMC3476540
The direct cellular target of topically applied pimecrolimus may not be infiltrating lymphocytes
BRITISH JOURNAL OF DERMATOLOGY
2011; 164 (5): 996-1003
Topically applied calcineurin inhibitors have been shown to be effective in the treatment of atopic dermatitis. When systemically administered, these agents cause immunosuppression via inhibition of calcineurin in lymphocytes. As topical agents, the mechanism of action is poorly defined.To test the hypothesis that skin-infiltrating lymphocytes are directly targeted when calcineurin inhibitors are applied to the skin.Ten patients with atopic dermatitis were treated with 1% pimecrolimus cream twice daily to target lesions. Skin biopsies were performed before and 48 h after beginning therapy. We assessed the cellular localization of NFAT1 and NFAT2 as a surrogate measure of intracellular calcineurin activity (e.g. increasing cytoplasmic localization with increasing calcineurin inhibition).All patients showed a clinical response, at both 48 h and 2 weeks. As previously described, NFAT2 localized to the follicular keratinocytes, and its activation was partially inhibited by topical pimecrolimus. NFAT1 was found to be expressed by follicular and interfollicular keratinocytes, and its mostly nuclear localization was not affected by topical pimecrolimus therapy. Both NFAT1 and NFAT2 were found in the infiltrating lymphocytes. However, using both manual counting as well as an automated method to assess nuclear intensity of NFAT staining, we found that the proportion of infiltrating leucocytes with nuclear ('activated') NFAT did not change following therapy with pimecrolimus.Our results suggest that topical pimecrolimus does not act primarily by inhibiting the calcineurin/NFAT axis in lymphocytes but may instead act by other mechanisms, possibly by decreasing NFAT2 activity in follicular keratinocytes.
View details for DOI 10.1111/j.1365-2133.2010.10190.x
View details for Web of Science ID 000289898200012
View details for PubMedID 21166661
Automated diagnosis of data-model conflicts using metadata
JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION
1999; 6 (5): 374-392
The authors describe a methodology for helping computational biologists diagnose discrepancies they encounter between experimental data and the predictions of scientific models. The authors call these discrepancies data-model conflicts. They have built a prototype system to help scientists resolve these conflicts in a more systematic, evidence-based manner. In computational biology, data-model conflicts are the result of complex computations in which data and models are transformed and evaluated. Increasingly, the data, models, and tools employed in these computations come from diverse and distributed resources, contributing to a widening gap between the scientist and the original context in which these resources were produced. This contextual rift can contribute to the misuse of scientific data or tools and amplifies the problem of diagnosing data-model conflicts. The authors' hypothesis is that systematic collection of metadata about a computational process can help bridge the contextual rift and provide information for supporting automated diagnosis of these conflicts. The methodology involves three major steps. First, the authors decompose the data-model evaluation process into abstract functional components. Next, they use this process decomposition to enumerate the possible causes of the data-model conflict and direct the acquisition of diagnostically relevant metadata. Finally, they use evidence statically and dynamically generated from the metadata collected to identify the most likely causes of the given conflict. They describe how these methods are implemented in a knowledge-based system called GRENDEL and show how GRENDEL can be used to help diagnose conflicts between experimental data and computationally built structural models of the 30S ribosomal subunit.
View details for Web of Science ID 000082447300006
View details for PubMedID 10495098
View details for PubMedCentralID PMC61381
RIBOWEB: Linking structural computations to a knowledge base of published experimental data
5th International Conference on Intelligent Systems for Molecular Biology (ISMB-97)
AMER ASSOC ARTIFICIAL INTELLIGENCE. 1997: 84–87
The world wide web (WWW) has become critical for storing and disseminating biological data. It offers an additional opportunity, however, to support distributed computation and sharing of results. Currently, computational analysis tools are often separated from the data in a manner that makes iterative hypothesis testing cumbersome. We hypothesize that the cycle of scientific reasoning (using data to build models, and evaluating models in light of data) can be facilitated with resources that link computations with semantic models of the data. Riboweb is an on-line knowledge-based resource that supports the creation of three-dimensional models of the 30S ribosomal subunit. It has three components: (I) a knowledge base containing representations of the essential physical components and published structural data, (II) computational modules that use the knowledge base to build or analyze structural models, and (III) a web-based user interface that supports multiple users, sessions and computations. We have built a prototype of Riboweb, and have used it to refine a rough model of the central domain of the 30S subunit from E. coli. procedure. Our results suggest that sophisticated and integrated computational capabilities can be delivered to biologists using this simple three-component architecture.
View details for Web of Science ID 000072320000011
View details for PubMedID 9322019
RNA secondary structure as a reusable interface to biological information resources
1997; 190: GC59-GC70
The dissemination of biological information has become critically dependent on the Internet and World Wide Web (WWW), which enable distributed access to information in a platform independent manner. The mode of interaction between biologists and on-line information resources, however, has been mostly limited to simple interface technologies such has hypertext links, tables and forms. The introduction of platform-independent runtime environments facilitates the development of more sophisticated WWW-based user interfaces. Until recently, most such interfaces have been tightly coupled to the underlying computation engines, and not separated as reusable components. We believe that many subdisciplines of biology have intuitive and familiar graphical representations of knowledge that can serve as multipurpose user interface elements. We call such graphical idioms "domain graphics". In order to illustrate the power of such graphics, we have built a reusable interface based on the standard two dimensional (2D) layout of RNA secondary structure. The interface can be used to represent any pre-computed layout of RNA, and takes as a parameters the sets of actions to be performed as a user interacts with the interface. It can provide to any associated application program information about the base, helix, or subsequence selected by the user. We show the versatility of this interface by using it as a special purpose interface to BLAST, Medline and the RNA MFOLD search/compute engines. These demonstrations are available at: http://www-smi.stanford.edu/projects/helix/pubs/ gene-combis-96/
View details for Web of Science ID A1997WP51800001
View details for PubMedID 9197551
Standardized representations of the literature: Combining diverse sources of ribosomal data
5th International Conference on Intelligent Systems for Molecular Biology (ISMB-97)
AMER ASSOC ARTIFICIAL INTELLIGENCE. 1997: 15–24
We are building a knowledge base (KB) of published structural data on the 30s ribosomal subunit in prokaryotes. Our KB is distinguished by a standardized representation of biological experiments and their results, in a reusable format. It can be accessed by computer programs that exploit the rich interconnections within the data. The KB is designed to support the construction of 3D models of the 30S subunit, as well as the analysis and extension of relevant functional and phylogenetic information. Most published information about the structure of the ubiquitous ribosome focuses on E. coli as a model system. At the same time, thousands of RNA sequences for the ribosome have been gathered and cataloged. The volume and complexity of these data can complicate attempts to separate structural data peculiar to E. coli from data of universal relevance. We have written an application that dynamically queries the KB and the Ribosome Database Project, a repository of ribosomal RNA sequences from other organisms, in order to assess the relevance of structural data to particular organisms. The application uses the RDP alignment to determine whether a set of data refer primarily to conserved, mismatched, or gapped positions. For a set of 16 representative articles evaluated over 211 sequences, 73% of observations have unambiguous translations from E. coli to the other organisms, 21% have somewhat ambiguous translations, and 6% have no translations. There is a wide variation in these numbers over different articles and organisms, confirming that some articles report structural information specific to E. coli while others report information that is quite general.
View details for Web of Science ID 000072320000002
View details for PubMedID 9322010
Computational methods for defining the allowed conformational space of 16S rRNA based on chemical footprinting data
RNA-A PUBLICATION OF THE RNA SOCIETY
1996; 2 (9): 851-866
Structural models for 16S ribosomal RNA have been proposed based on combinations of crosslinking, chemical protection, shape, and phylogenetic evidence. These models have been based for the most part on independent data sets and different sets of modeling assumptions. In order to evaluate such models meaningfully, methods are required to explicitly model the spatial certainty with which individual structural components are positioned by specific data sets. In this report, we use a constraint satisfaction algorithm to explicitly assess the location of the secondary structural elements of the 16S RNA, as well as the certainty with which these elements can be positioned. The algorithm initially assumes that these helical elements can occupy any position and orientation and then systematically eliminates those positions and orientations that do not satisfy formally parameterized interpretations of structural constraints. Using a conservative interpretation of the hydroxyl radical footprinting data, the positions of the ribosomal proteins as defined by neutron diffraction studies, and the secondary structure of 16S rRNA, the location of the RNA secondary structural elements can be defined with an average precision of 25 A (ranging from 12.8 to 56.3 A). The uncertainty in individual helix positions is both heterogeneous and dependent upon the number of constraints imposed on the helix. The topology of the resulting model is consistent with previous models based on independent approaches. The result of our computation is a conservative upper bound on the possible positions of the RNA secondary structural elements allowed by this data set, and provides a suitable starting point for refinement with other sources of data or different sets of modeling assumptions.
View details for Web of Science ID A1996VH69500001
View details for PubMedID 8809013
View details for PubMedCentralID PMC1369421
Constraining volume by matching the moments of a distance distribution
COMPUTER APPLICATIONS IN THE BIOSCIENCES
1996; 12 (4): 319-326
The problem of computing a molecular structure from a set of distances arises in the interpretation of NMR data as well as other experimental methods that yield distance information. Techniques for computing structures must find conformations consistent with the distance data. There are often other constraints on the structure that must be satisfied as well. One of the most problematic constraints is the constraint on the total volume occupied by the atoms. In this paper, we use the first two moments (mean and variance) of an estimated distance distribution to constrain the volume of a computed structure. We show that a probabilistic algorithm for matching the first two moments of the estimated distance distribution significantly improves the quality of the solution, especially when the distance information alone is not sufficient to define the structure precisely. We also show that our method is not sensitive to small errors in the estimates of mean and variance of the distance distribution. Finally, we demonstrate the use of this constraint in computing a low-resolution structure of the 30S prokaryotic ribosomal subunit. Quantitative analysis of our results allows us to assess the information content contained in constraints on volume, and to show that in some cases addition of a volume constraint adds information roughly equivalent to doubling the number of input distances. Our results also demonstrate the flexibility of probabilistic representations of structural constraints, and the importance of including volume information to constrain structural computations-especially in the case of sparse data.
View details for Web of Science ID A1996VM02500008
View details for PubMedID 8902359