NIH VideoCast - Learning the ‘metadata’ of the cell with single cell genomics and Seurat

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Learning the ‘metadata’ of the cell with single cell genomics and Seurat

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Air date:	Tuesday, January 31, 2017, 12:00:00 PM Time displayed is Eastern Time, Washington DC Local
Views:	Total views: 463 (106 Live, 357 On-demand)
Category:	Special
Runtime:	01:00:53
Closed captioning:	Check box to display CC outside of the video Note: You can drag the captioning window around and resize it
Description:	NIH Single Cell Analysis Lecture Series Dr. Satija's group brings cutting-edge analysis tools such as the package "Seurat" to help us understand cell heterogeneity in complex biological systems. The creative insight and innovative tools developed by the Satija group and colleagues help in handling highly multi-dimensional single cell genomics datasets, and have been recently utilized in many groundbreaking, high-throughput single cell RNA-Seq publications. This seminar is sponsored by NCI-CCR, with organizational support from the Single Cell Genomics, Bioinformatics and Data Science Special Interest Groups.

NLM Title:	Learning the "metadata" of the cell with single cell genomics and Seurat / Rahul Satija.
Author:	Satija, Rahul. NIH Common Fund. Single Cell Analysis Program, Center for Cancer Research (National Cancer Institute (U.S.)),
Publisher:
Abstract:	(CIT): NIH Single Cell Analysis Lecture Series Dr. Satija's group brings cutting-edge analysis tools such as the package "Seurat" to help us understand cell heterogeneity in complex biological systems. The creative insight and innovative tools developed by the Satija group and colleagues help in handling highly multi-dimensional single cell genomics datasets, and have been recently utilized in many groundbreaking, high-throughput single cell RNA-Seq publications. This seminar is sponsored by NCI-CCR, with organizational support from the Single Cell Genomics, Bioinformatics and Data Science Special Interest Groups.
Subjects:	Computer Simulation Computers, Molecular Datasets as Topic Gene Expression Genetic Heterogeneity Single-Cell Analysis
Publication Types:	Lecture Webcast

NLM Classification:	QY 26.5
NLM ID:	101702156
CIT Live ID:	21733
Permanent link:	https://videocast.nih.gov/watch=21733

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