Professional Certificate Single-Cell RNA Analysis: Essential Skills
-- ViewingNowThe Professional Certificate in Single-Cell RNA Analysis: Essential Skills is a comprehensive course that equips learners with the latest skills in single-cell RNA sequencing (scRNA-seq) data analysis. This certificate course is essential for professionals working in the fields of genomics, bioinformatics, and computational biology.
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โข Introduction to Single-Cell RNA Analysis: Basics of single-cell RNA sequencing (scRNA-seq), its applications, and benefits over bulk RNA sequencing.
โข Data Preprocessing for Single-Cell RNA Analysis: Quality control, data filtering, normalization, and feature selection for scRNA-seq data.
โข Clustering and Dimensionality Reduction Techniques: Hierarchical clustering, k-means clustering, t-SNE, and UMAP for single-cell RNA data analysis.
โข Differential Expression Analysis: Identifying differentially expressed genes (DEGs) in single-cell RNA data using edgeR, DESeq2, or Monocle.
โข Cell Type Identification: Annotation of cell clusters using SingleR, scCATCH, or Seurat.
โข Cellular Trajectory Analysis: Reconstruction of cellular developmental trajectories using Monocle, Slingshot, or PAGA.
โข Functional Enrichment Analysis: Identification of enriched pathways and gene ontologies in the differentially expressed genes.
โข Data Visualization and Interpretation: Visualization of scRNA-seq results using tools like Seurat, Scater, and ggplot2.
โข Integrating Single-Cell RNA Data with Multi-omics Data: Techniques for integrating scRNA-seq data with other omics data types.
โข Reproducible Research Practices and Tools: Utilization of version control, containerization, and workflow management tools for reproducible single-cell RNA analysis.
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