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CORTEX seq-FISH: selection of spatial coherent genes Xu, Hang
Description
Dr Hang Xu is a postdoctoral Fellow in Christina Curtis's Lab (Stanford). Hang obtained her PhD in bioinformatics at the University of Nottingham, UK. She then trained as a postdoctoral research fellow in the Francis Crick Institute with Charles Swanton. Hang is interested in studying cancer evolutionary dynamics. Her research asked the following questions; 1. Can scRNA-seq data be overlaid onto seqFISH for resolution enhancement 2. What is the minimal number of genes needed for data integration She followed the approaches that described in Zhu's paper (Zhu et al 2018) which integrated scRNAseq and smFISH data. By following the approach, she randomly selected a subset of differently expressed genes and applied a SVM model to estimated the minimal number of genes that are required data integration. Code is available at https://github.com/gooday23/smfishscRNAHackathon/
Item Metadata
| Title |
CORTEX seq-FISH: selection of spatial coherent genes
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| Creator | |
| Publisher |
Banff International Research Station for Mathematical Innovation and Discovery
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| Date Issued |
2020-06-15T07:21
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| Description |
Dr Hang Xu is a postdoctoral Fellow in Christina Curtis's Lab (Stanford). Hang obtained her PhD in bioinformatics at the University of Nottingham, UK. She then trained as a postdoctoral research fellow in the Francis Crick Institute with Charles Swanton. Hang is interested in studying cancer evolutionary dynamics.
Her research asked the following questions;
1. Can scRNA-seq data be overlaid onto seqFISH for resolution enhancement
2. What is the minimal number of genes needed for data integration
She followed the approaches that described in Zhu's paper (Zhu et al 2018) which integrated scRNAseq and smFISH data. By following the approach, she randomly selected a subset of differently expressed genes and applied a SVM model to estimated the minimal number of genes that are required data integration.
Code is available at https://github.com/gooday23/smfishscRNAHackathon/
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| Extent |
17.0 minutes
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| Subject | |
| Type | |
| File Format |
video/mp4
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| Language |
eng
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| Notes |
Author affiliation: Stanford Cancer Institute
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| Series | |
| Date Available |
2020-12-14
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| Provider |
Vancouver : University of British Columbia Library
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| Rights |
Attribution-NonCommercial-NoDerivatives 4.0 International
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| DOI |
10.14288/1.0395266
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| URI | |
| Affiliation | |
| Peer Review Status |
Unreviewed
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| Scholarly Level |
Postdoctoral
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| Rights URI | |
| Aggregated Source Repository |
DSpace
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Rights
Attribution-NonCommercial-NoDerivatives 4.0 International