Understanding 10X Single Cell RNA-Seq Analysis
This content delves into the intricacies of analyzing 10X single-cell RNA-Seq data, covering topics such as how 10X RNA-Seq works, evaluating CellRanger QC reports, dimensionality reduction techniques like PCA, tSNE, and UMAP, using the Loupe cell browser, and frameworks for scRNA analysis in R. It
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Understanding Dimension Reduction Techniques in Data Analysis
Employing techniques like PCA, tSNE, and UMAP allows for effective visualization and integration of multi-dimensional datasets. These methods help in reducing data complexity to reveal patterns and insights for further analysis. Gene expression data is used as an example to illustrate the principles
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Understanding 10X Single-Cell RNA-Seq Data Analysis
Explore the intricacies of analyzing 10X Single-Cell RNA-Seq data, from how the technology works to using tools like CellRanger, Loupe Cell Browser, and Seurat in R. Learn about the process of generating barcode counts, mapping, filtering, quality control, and quantitation of libraries. Dive into di
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