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phs000834.v3.p1 : Single Cell Analysis Program - Transcriptome (SCAP-T) (UCSD) phs000835.v3.p1 : Single Cell Analysis Program - Transcriptome (SCAP-T) (U. Penn) phs000836.v3.p1 : Single Cell Analysis Program - Transcriptome (SCAP-T) (USC)
- Study Description
This initiative is part of the Single Cell Analysis Program (SCAP) and is funded through the NIH Common Fund (See http://nihroadmap.nih.gov/), which supports cross-cutting programs that are expected to have exceptionally high impact. Common Fund initiatives address key roadblocks in biomedical research that impede basic scientific discovery and its translation into improved human health. In addition, these programs capitalize on emerging opportunities to catalyze progress across multiple biomedical fields.
Single cell analysis has recently emerged as an important field of research because technologies have improved in sensitivity and throughput sufficiently to begin measuring and understanding heterogeneity in complex biological systems and correlating it with changes in biological function and disease processes. By profiling individual cells it is possible to resolve rare cells, transient cell states, and the influence of organization and environment on such cells and states, which cannot be described by ensemble measurements. The long-term goal of the SCAP is to accelerate this move towards personalizing health to the cellular level by understanding the link between cell heterogeneity, tissue function and emergence of disease through the discovery, development and translation of innovative approaches which will dramatically change the way cells are characterized.
The SCAP will focus on research, which will systematically measure, analyze and model cell-to-cell variation, and identify crucial differences and rare biological states, which may have important functional consequences.
Under SCAP, there are three studies to evaluate the cellular heterogeneity using transcriptional profiling of single cells (U01):
- University of Pennsylvania: Role of single cell mRNA variation in systems associated electrically excitable cells
- University of Southern California: Evaluation of cellular heterogeneity using patchclamp and RNA-seq of single cells
- University of California at San Diego: Single cell sequencing and in situ mapping of RNA transcripts in human brains
The SCAP has been designed as a five-year program with several components: (1) the collection, analysis and sharing of comprehensive expression datasets to understand the role of heterogeneity in tissues and systemically and identify critical parameters and states; (2) the discovery of new, innovative tools for spatiotemporal imaging, manipulation, analysis and modeling of a biologically relevant population of cells with minimal perturbation; (3) milestone-driven validation and translation of technologies for characterizing single cells in situ meeting the needs of end-users; and (4) development and coordination of a multidisciplinary research community through workshops and other collective endeavors. Further details about the NIH SCAP-T program can be found here http://commonfund.nih.gov/singlecell/.
The first data release of SCAP-T includes the detailed phenotype information, experimental protocols, QC information, RNA-sequencing data and NGS results for 697 single cells from human brain and heart. The second data release of SCAP-T expands this by including the detailed phenotype information, experimental protocols, QC information, RNA-sequencing data and NGS results for additional 978 single cells from human brain and heart. The SCAP-T data portal provides a customized interface for users to quickly identify and retrieve files by phenotypes, and data properties such as sequencing facility or coverage for all of these 1675 single cells. For more information about the SCAP-T study and the data portal, please visit http://www.scap-t.org.
- Study Weblinks:
- Study Design:
- Study Type:
- Single Cell Analysis
- Authorized Access
- Publicly Available Data (Public ftp)
- Selected publications
- Diseases/Traits Related to Study (MeSH terms)
- Primary Phenotype: N/A
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