Single-cell RNA-seq Pipeline

Comprehensive analysis of single-cell transcriptomics data

Overview

This pipeline covers the analysis of single-cell RNA-sequencing data from raw reads to cell type annotation and downstream analysis.

flowchart LR
    A[Raw FASTQ] --> B[Cell Ranger]
    B --> C[QC & Filtering]
    C --> D[Normalization]
    D --> E[Integration]
    E --> F[Clustering]
    F --> G[Annotation]
    
    style A fill:#e74c3c,color:white
    style B fill:#f39c12,color:white
    style C fill:#3498db,color:white
    style D fill:#9b59b6,color:white
    style E fill:#1abc9c,color:white
    style F fill:#27ae60,color:white
    style G fill:#2c3e50,color:white

Pipeline Steps

1. Cell Ranger Processing

Read More →

Demultiplexing, alignment, and UMI counting with Cell Ranger.

Cell Ranger FASTQ 10x Genomics

2. Ambient RNA Correction

Read More →

Removing ambient RNA contamination using CellBender.

cellbender Ambient RNA correction QC

3. Data processing and Integration

Read More →

Normalization, identification of highly variable genes, and data integration.

Integration Seurat HVGs

4. Copy Number Variation Inference

Read More →

For Tumor samples, infer copy number variations using Numbat.

PCA UMAP Louvain

Required Inputs

Input Description Source
Raw FASTQ files Sequencing reads Sequencer
Reference genome Cell Ranger reference 10x Genomics
Sample metadata Sample information User-provided

Expected Outputs

  • Quality control reports
  • Filtered count matrices
  • UMAP/tSNE visualizations
  • Cluster assignments
  • Cell type annotations
  • Marker gene lists
  • Differential expression between clusters