GSE115889   Details

GSE Accession GSE115889
Title A Rank-based Semblance kernel over Probability Spaces
Submission Date 6/15/18
Last Update Date 10/2/18
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Experiment Type Expression profiling by high throughput sequencing
Contributor Divyansh,,Agarwal; Nancy Zhang
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Summary Purpose: scRNA-seq allows disocvery of novel cell types. Here, we design a kernel method to discover niche cell populations, and show that our kernel provides encoruaging results on a dataset of retinal horizontal cells; Methods: Retinal mRNA profiles of Horizontal cells from 10-week-old wild-type (WT) Black 6 mouse were generated by scRNA sequencing. The data was normalized using Seurat.; Results: Using an optimized data analysis workflow, we found the Semblance yielded two populations with the retinal horizontal cells, and the second population was found to have unique metabolic properties.; Conclusions: Our kernel method providees a unique framework to study cell-to-cell similarity.
Overall Design Retinal Horizontal cell mRNA datafrom a 10-week old wild type (WT) aBlack 6 mouse.
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