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Review the research papers we collaborated on and discover others who are working in the same field.
Science - November 13, 2020
A human cell atlas of fetal gene expression
A reference atlas of human cell types is a major goal for the field. Here, we set out to generate single-cell atlases of both gene expression (this study) and chromatin accessibility (Domcke et al., this issue) using diverse human tissues obtained during midgestation.
Science - November 13, 2020
A human cell atlas of fetal chromatin accessibility
In recent years, the single-cell genomics field has made incredible progress toward disentangling the cellular heterogeneity of human tissues. However, the overwhelming majority of effort has been focused on single-cell gene expression rather than the chromatin landscape that shapes and is shaped by gene expression. Toward advancing our understanding of the regulatory programs that underlie human cell types, we set out to generate single-cell atlases of both chromatin accessibility (this study) and gene expression (Cao et al., this issue) from a broad range of human fetal tissues.
Cell - October 28, 2020
Multi-Omics Resolves a Sharp Disease-State Shift between Mild and Moderate COVID-19
We present an integrated analysis of the clinical measurements, immune cells, and plasma multi-omics of 139 COVID-19 patients representing all levels of disease severity, from serial blood draws collected during the first week of infection following diagnosis. We identify a major shift between mild and moderate disease, at which point elevated inflammatory signaling is accompanied by the loss of specific classes of metabolites and metabolic processes. Within this stressed plasma environment at moderate disease, multiple unusual immune cell phenotypes emerge and amplify with increasing disease severity. We condensed over 120,000 immune features into a single axis to capture how different immune cell classes coordinate in response to SARS-CoV-2. This immune-response axis independently aligns with the major plasma composition changes, with clinical metrics of blood clotting, and with the sharp transition between mild and moderate disease. This study suggests that moderate disease may provide the most effective setting for therapeutic intervention.
Nature - October 12, 2020
Integrated analysis of multimodal single-cell data
The simultaneous measurement of multiple modalities, known as multimodal analysis, represents an exciting frontier for single-cell genomics and necessitates new computational methods that can define cellular states based on multiple data types. Here, we introduce ‘weighted-nearest neighbor’ analysis, an unsupervised framework to learn the relative utility of each data type in each cell, enabling an integrative analysis of multiple modalities. We apply our procedure to a CITE-seq dataset of hundreds of thousands of human white blood cells alongside a panel of 228 antibodies to construct a multimodal reference atlas of the circulating immune system. We demonstrate that integrative analysis substantially improves our ability to resolve cell states and validate the presence of previously unreported lymphoid subpopulations. Moreover, we demonstrate how to leverage this reference to rapidly map new datasets, and to interpret immune responses to vaccination and COVID-19. Our approach represents a broadly applicable strategy to analyze single-cell multimodal datasets, including paired measurements of RNA and chromatin state, and to look beyond the transcriptome towards a unified and multimodal definition of cellular identity.
Nature - February 20, 2019
The single-cell transcriptional landscape of mammalian organogenesis
Mammalian organogenesis is a remarkable process. Within a short timeframe, the cells of the three germ layers transform into an embryo that includes most of the major internal and external organs. Here we investigate the transcriptional dynamics of mouse organogenesis at single-cell resolution. Using single-cell combinatorial indexing, we profiled the transcriptomes of around 2 million cells derived from 61 embryos staged between 9.5 and 13.5 days of gestation, in a single experiment.
Nature Genetics - August 29, 2018
Analysis and visualization of linked molecular and clinical cancer data by using Oncoscape
The rapid generation and expanding the accessibility of clinical and molecular data is shifting the bottleneck in cancer research from data acquisition to data aggregation and interpretation. Many tools have been developed to address various aspects of this need1,2,3,4,5. To overcome the persistent challenges in cohort discovery and analysis for translational research and prospective clinical-decision support in precision medicine, we developed Oncoscape, an online open-access data-analysis and visualization platform (see URLs) that empowers researchers and clinicians to discover novel patterns and relationships between linked clinical and molecular data.
Acta Neuropathologica Communications - May 22, 2017
Multidimensional scaling of diffuse gliomas
Using the web-based platform Oncoscape as a tool, we applied multidimensional scaling-derived molecular groups to the 2D visualization of the 2016 WHO classification of diffuse gliomas. Here we show that molecular multidimensional scaling of TCGA data provides 2D clustering that represents the 2016 WHO classification of diffuse gliomas. Additionally, we used this platform to successfully identify and define novel copy-number alteration-based molecular subtypes, which are independent of WHO grading, as well as predictive of clinical outcome.
2019 Cambia Grove Innovator Fellowship
In collaboration with Cambia Grove, Fred Hutch Data Visualization accepted its inaugural fellowship cohort to develop a biological data catalog to expose valuable clinical and molecular data through consistent web-optimized application programming interfaces (APIs). These efforts will help researchers worldwide find effective treatments or even cures to cancer.
Brotman Baty Collaboration
We recently partnered with Brotman Baty and UW Genome Sciences to develop a multispecies organogenesis atlas featuring scRNA and ATAC Seq data. Together we are reimagining how to best share and visualize single cell data.