Integrate single-cell RNA-Seq datasets in R using Seurat (CCA) | Detailed Seurat Workflow Tutorial

A detailed walk-through of steps to merge and integrate single-cell RNA sequencing datasets to correct for batch effect in R using the #Seurat package. I hope you liked the video. I look forward to your comments under the comments section!

1) Paper:
Modeling Hepatoblastoma: Identification of Distinct Tumor Cell Populations and Key Genetic Mechanisms through Single Cell Sequencing (scRNA-seq): https://www.ncbi.nlm.nih.gov/pmc/arti...

2) Data:
GSE180665: https://www.ncbi.nlm.nih.gov/geo/quer...

3) Link to code:
https://github.com/kpatel427/YouTubeT...

4) Seurat Integration Vignette:
https://satijalab.org/seurat/articles...

5) Additional resources:
‣ CCA method: https://www.cell.com/cell/fulltext/S0...
‣ MNN method: https://www.ncbi.nlm.nih.gov/pmc/arti...
‣ https://www.nature.com/articles/s4158...
‣ https://satijalab.org/seurat/articles...
‣ https://satijalab.org/seurat/archive/...
‣ https://github.com/hbctraining/scRNA-...

Chapters:
0:00 Intro
0:21 Study design
1:45 When to integrate?
2:41 Types of integration
4:17 Batch correction methods
4:58 Downloading data
7:27 Read data in R
11:08 Merge Seurat objects
14:20 QC and filtering
20:26 Do we see batch effects in our data?
23:07 Visualize merged data (before integration)
25:26 Integration steps
30:34 Visualize integrated data (after integration)
32:03 Comparing UMAPs: before integration vs after integration

Show your support and encouragement by buying me a coffee:
https://www.buymeacoffee.com/bioinfor...

To get in touch:
Website: https://bioinformagician.org/
Github: https://github.com/kpatel427
Email: [email protected]

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