Title	scNMT-seq:MOSAIC, or Multi-Omic Supervised Integrative Clustering
Creator	Arora, Arshi
Publisher	Banff International Research Station for Mathematical Innovation and Discovery
Date Issued	2020-06-17T07:41
Description	Arshi Arora is a Research Biostatistician in Dr. Ronglai Shen's lab at Memorial Sloan Kettering Cancer Center, https://www.mskcc.org/profile/arshi-arora Her research addressed the following question; We wish to address the problem of identifying localized molecular signatures with respect to an outcome of interest such as stage and lineage. This poses an interesting challenge in understanding heterogeneity in cell populations across multiple data modalities. We aim to illustrate that the application of a supervised integrative clustering will provide a more accurate delineation of cell subpopulation across genomic, epigenomic, and transcriptomic landscape that is directly relevant to the biological outcome of interest. Code is available at https://github.com/arorarshi/scNMT_seq_MOSAIC
Extent	18.0 minutes
Subject	Mathematics; Statistics; Biology and other natural sciences
Type	Moving Image
File Format	video/mp4
Language	eng
Notes	Author affiliation: Memorial Sloan Kettering Cancer Center
Series	BIRS Workshop Lecture Videos (Banff, Alta)
Date Available	2021-01-19
Provider	Vancouver : University of British Columbia Library
Rights	Attribution-NonCommercial-NoDerivatives 4.0 International
DOI	10.14288/1.0395663
URI	http://hdl.handle.net/2429/77152
Affiliation	Non UBC
Peer Review Status	Unreviewed
Scholarly Level	Graduate
Rights URI	http://creativecommons.org/licenses/by-nc-nd/4.0/
Aggregated Source Repository	DSpace

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scNMT-seq:MOSAIC, or Multi-Omic Supervised Integrative Clustering Arora, Arshi

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