![]() ![]() $ : chr "AAACCCACATAACTCG-1" "AAACCCACATGTAACC-1" "AAACCCAGTGAGTCAG-1" "AAACCCAGTGCTTATG-1". counts :Formal class 'dgCMatrix' with 6 slots 10.3 External RNA Control Consortium (ERCC)Īdj.matrix 10.1 Orchestrating Single-Cell Analysis with Bioconductor.9.10 LIGER, 3’ 10k PBMC cells and whole blood STRT-Seq.9.9 Harmony, 3’ 10k PBMC cells and whole blood STRT-Seq.9.8 Seurat v3, 3’ 10k PBMC cells and whole blood STRT-Seq.9.4 Practical Integration of Real Datasets.9.3 Cannonical Correlation Analysis (Seurat v3).8.4 Differential expression and marker selection.8.3 SCTransform normalization and clustering.8.2 Normalization and dimensionality reduction.8.1 Basic quality control and filtering.8 Single cell RNA-seq analysis using Seurat.7.3.4 Models of single-cell RNA-seq data.7.3 Differential Expression (DE) Analysis.6.6.5 Evaluation and Comparison of Batch-removal Approaches.6.6.2 Load and Normalize the Tung Dataset.6.2 Data Visualization and Dimensionality Reduction.6 Basic Quality Control (QC) and Exploration of scRNA-seq Datasets.4.13.5 Plotting data from more than 2 cells.3.6 Brief Summary and Processing Recommendations.3.4 STARsolo and Alevin-full-decoy: High Speed and High Accuracy.3.3.4 Chromium Versions and Cell Barcode Whitelists.3.3.3 Cell Ranger Reference Preparation.3.3 Read Alignment and Quantification in Droplet-based scRNA-seq Data.3.2 Processing of Bulk RNA-seq and Full-length scRNA-seq Data.3.1 Reference Genome and its Annotation.3 Processing Raw scRNA-Seq Sequencing Data: From Reads to a Count Matrix.
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