Global Certificate Single-Cell RNA Analysis: Innovative Approaches
-- ViewingNowThe Global Certificate in Single-Cell RNA Analysis course equips learners with the latest skills in single-cell RNA sequencing (scRNA-seq) data analysis. This innovative approach is critical in understanding complex biological systems, such as cancer, at the individual cell level.
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โข Single-Cell RNA Sequencing Technologies: An overview of single-cell RNA sequencing technologies, including droplet-based and plate-based methods, and their applications in molecular biology.
โข Data Preprocessing and Quality Control: Techniques for data preprocessing, quality control, and normalization to ensure the accuracy and reliability of single-cell RNA sequencing data.
โข Data Analysis and Visualization: An introduction to data analysis and visualization methods for single-cell RNA sequencing data, including dimensionality reduction, clustering, and differential expression analysis.
โข Cell Type Identification and Annotation: Methods for cell type identification and annotation using single-cell RNA sequencing data, including the use of reference atlases and machine learning algorithms.
โข Trajectory Analysis and Pseudotime Reconstruction: Techniques for reconstructing differentiation trajectories and identifying developmental stages using single-cell RNA sequencing data.
โข Integration of Multi-omic Data: Strategies for integrating single-cell RNA sequencing data with other types of omics data, such as epigenomics and proteomics, to gain a more comprehensive understanding of cellular processes.
โข Computational Tools and Software Packages: An overview of popular computational tools and software packages for single-cell RNA sequencing data analysis, including Seurat, Monocle, and Scanpy.
โข Best Practices and Challenges: Discussion of best practices and challenges in single-cell RNA sequencing data analysis, including experimental design considerations, data interpretation, and data sharing.
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