scRNA-seq (Seurat) pipeline for manuscript

scRNA-seq analysis pipeline 및 여러 분석 방법들에 대해서 진행하기 앞서 앞으로 정리할 사항들에 대한 정리

Step 1: scRNA-seq Preprocessing

(1) Seurat Object Creation
(2) Doublet Filtering
(3) Quality Control Processing
(4) Data Integration
(5) Cell-Type Annotation

Step 2: Plotting code

(1) UMAP
(2) FeaturePlot
(3) VlnPlot
(4) Heatmap
(5) Barplot
. . . etc

Step 3: Advanced Analysis and Result Interpretation

• Downstream Analysis of Specific Cell Types: Focusing on particular cells for deeper insights.
• Identifying Key Cell Types: Through function like immune scoring and severity-based clustering.

Additional Pipeline Enhancements

• DEG (Differentially Expressed Genes) Analysis: Incorporating volcano plotting for a comprehensive view.
• Gene Enrichment Pathway Analysis: For understanding the functional implications of your findings.
• WGCNA Module Development: To explore gene networks.
• CellChat Tutorial: For insights into cell-cell communication.
• Seurat Object Conversion in Scanpy: Enhancing interoperability between platforms.
• Gene Set Scoring Using AddModuleScore: For refined gene expression analysis.
• Pseudotime Analysis: To explore cellular differentiation trajectories.
• Gene-Gene Interaction Exploration: For understanding genetic interplays.
• pheatmap (Clustering): To identify patterns in gene expression data.
• Handling of Gene Matrices: For efficient data management and analysis.