Single-cell RNA-seq Analysis

Package Overview

Goal

Analysis and interpretation of single-cell (or single-nuclei) RNA-seq data

Requirements

  • Single-cell datasets with at least 100 cells
  • Samples processed with 10x Genomics, Smart-seq2, Parse Biosciences, or similar (after consultation)
  • Sufficient sequencing depth according to the technology-specific recommendation
  • Replicates recommended for the identification of differentially expressed genes

Analysis

  • Mapping of sequencing data and generation of a cell-x-gene count matrix
  • Quality control, filtering of low quality cells and normalization
  • Multi-sample integration and batch effect removal
  • Clustering and visualization
  • Identification and functional annotation of marker genes
  • Analysis of cell composition differences
  • Identification of differentially expressed genes

Output

  • Mapped sequencing data and counts
  • Extensive HTML report with plots, tables and documentation
  • Result files for further analysis (Excel, RDS, CSV)
  • Files for interactive exploration of the data (Loupe and cellxgene)

Advanced Analysis

  • Identification of cell-types based on either existing single-cell datasets (provided counts and cell type annotation are available) or cell type markers
  • Trajectory inference and pseudotime analysis
  • Cell-to-cell communication analysis