Pseudo-bulk analysis for single-cell RNA-Seq data | Detailed workflow tutorial

Опубликовано: 04 Апрель 2022
на канале: Bioinformagician

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A detailed walk-through of steps to find perform pseudo-bulk differential expression analysis for single-cell RNA-Seq data in R. In this video I discuss what is pseudo-bulk analysis, why do we take this approach, and lastly how to perform this analysis. In this tutorial, I demonstrate how to manipulate data and aggregate counts to sample level using a Seurat object, followed by differential expression analysis using DESeq2 to find differentially expressed genes in a specific cell type cluster. I hope you find the video informative. I look forward to your comments in the comments section!

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

2) Vignettes:
▸ https://hbctraining.github.io/scRNA-s...
▸ http://biocworkshops2019.bioconductor...
▸ http://bioconductor.org/books/3.14/OS...
▸ http://bioconductor.org/books/3.14/OS...

3) Papers:
▸ https://www.nature.com/articles/s4146...
▸ https://bmcbioinformatics.biomedcentr...
▸ https://genomebiology.biomedcentral.c...

Chapters:
0:00 Intro
0:29 WHAT is pseudo-bulk analysis?
1:48 WHY perform pseudo-bulk analysis?
5:25 (onwards) HOW to perform pseudo-bulk analysis?
5:44 Fetch data from ExperimentHub
8:36 QC and filtering
12:11 Seurat's standard workflow steps
14:10 Visualize data
15:54 To use integrated or nonintegrated data?
16:49 Aggregate counts to sample level
21:35 Data manipulation step 1: Transpose matrix
22:16 Data manipulation step 2: Split data frame
24:46 Data manipulation step 3: Fix row.names and transpose again
29:18 DESeq2 step 1: Get count matrix (corresponding to a cell type)
30:09: Create sample level metadata i.e. colData
32:23 DESeq2 step 2: Create DESeq2 dataset from matrix
33:38 DESeq2 step 2: Run DESeq()
33:51 Get results

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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