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Integration of multiple types of single-cell data with Seurat v3
July 17 @ 9:00 am - 10:00 am PDT
Large datasets, in particular single cell datasets, pose a challenge for integration across different samples and multiple data types (gene expression, chromatin accessibility, spatial). We invite you to a webinar to learn about new updates for the R package Seurat (version 3) to address these challenges, with a focus on new features for diverse biological disciplines
The webinar will be presented by our guest speaker, Dr. Rahul Satija of the NYGC and NYU, followed by a live Q&A session.
In this webinar you will learn about:
- Improved and expanded methods for single-cell RNA-seq integration, including datasets collected across different donors and species for assembly into a reference ‘atlas’
- New methods for harmonizing and classifying cells based on chromatin accessibility (scATAC-seq) and scRNA-seq profiles, as well as transferring information between spatial and sequencing-based profiles
- An efficiently restructured Seurat object, with an emphasis on the analysis of multi-modal data, for example, from CITE-seq
- A new normalization procedure that effectively mitigates the effect of technical variation while preserving biological heterogeneity”
- Rahul Satija
Bring your questions and we look forward to seeing you there!Register