Title	Statistical analysis of RNA-seq data at different scales
Creator	Leek, Jeff
Publisher	Banff International Research Station for Mathematical Innovation and Discovery
Date Issued	2015-08-03T09:47
Description	RNA-seq is now the primary technology used to measure transcriptional abundance. The analysis of RNA-seq data can be done at multiple levels (genes, regions, or transcripts) and at multiple scales (small experiments or large population cohorts). I will discuss statistical challenges in developing and applying software for the analysis of RNA-seq data at multiple scales including reproducibility, statistical power, trust in genomic annotations, and detection and removal of artifacts. These issues are critical in the analysis of data from genomic experiments in general, but are particularly acute in the analysis of dynamic data from transcriptomes.
Extent	32 minutes
Subject	Mathematics; Statistics; Biology and other natural sciences
Type	Moving Image
File Format	video/mp4
Language	eng
Notes	Author affiliation: Johns Hopkins Bloomberg School of Public Health
Series	BIRS Workshop Lecture Videos (Banff, Alta)
Date Available	2016-04-18
Provider	Vancouver : University of British Columbia Library
Rights	Attribution-NonCommercial-NoDerivatives 4.0 International
DOI	10.14288/1.0300003
URI	http://hdl.handle.net/2429/57647
Affiliation	Non UBC
Peer Review Status	Unreviewed
Scholarly Level	Faculty
Rights URI	http://creativecommons.org/licenses/by-nc-nd/4.0/
Aggregated Source Repository	DSpace

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