Skip Navigation


CIT can broadcast your seminar, conference or meeting live to a world-wide audience over the Internet as a real-time streaming video. The event can be recorded and made available for viewers to watch at their convenience as an on-demand video or a downloadable file. CIT can also broadcast NIH-only or HHS-only content.

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

Loading video...

427 Views  
   
Air date: Tuesday, January 31, 2017, 12:00:00 PM
Time displayed is Eastern Time, Washington DC Local
Views: Total views: 427, (106 Live, 321 On-demand)
Category: Special
Runtime: 01:00:53
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.
Debug: Show Debug
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
Webcasts
Download: To download this event, select one of the available bitrates:
[64k]  [150k]  [240k]  [440k]  [740k]  [1040k]  [1240k]  [1440k]  [1840k]    How to download a Videocast
Caption Text: Download Caption File
NLM Classification: QY 26.5
NLM ID: 101702156
CIT Live ID: 21733
Permanent link: https://videocast.nih.gov/launch.asp?21118