Title	sc targeted proteomics: Predicting outcome, survival from 3 proteomics datasets (Keren, Jackson, Wagner)
Creator	Lin, Yingxin
Publisher	Banff International Research Station for Mathematical Innovation and Discovery
Date Issued	2020-06-16T07:00
Description	Ms. Yingxin Lin is a PhD candidate in Statistics under the supervision of Prof. Jean Yang, Dr. John Ormerod and Dr. Rachel Wang at the University of Sydney. Her main research interest is in normalisation and statistical modelling of single-cell RNA-seq data. https://yingxinlin.github.io/ She analyzed the three sc targeted proteomics datasets (Keren et al., Jackson et al., and Wagner et al.) which all presented comprehensive portraits of breast cancer tumor immune microenvironment, utilizing different methods to identify and characterize different subtypes of patients with the evidence associated with survival. Code is available at https://yingxinlin.github.io/BIRS_analysis
Extent	20.0 minutes
Subject	Mathematics; Statistics; Biology and other natural sciences
Type	Moving Image
File Format	video/mp4
Language	eng
Notes	Author affiliation: The University of Sydney
Series	BIRS Workshop Lecture Videos (Banff, Alta)
Date Available	2020-12-14
Provider	Vancouver : University of British Columbia Library
Rights	Attribution-NonCommercial-NoDerivatives 4.0 International
DOI	10.14288/1.0395269
URI	http://hdl.handle.net/2429/76779
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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sc targeted proteomics: Predicting outcome, survival from 3 proteomics datasets (Keren, Jackson, Wagner) Lin, Yingxin

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