Pseudo-Bulk Analysis for Single-Cell RNA-Seq Data - Detailed Workflow Tutorial

Pseudo-Bulk Analysis for Single-Cell RNA-Seq Data - Detailed Workflow Tutorial

bioinformagician via YouTube Direct link

Aggregate counts to sample level

10 of 18

10 of 18

Aggregate counts to sample level

Class Central Classrooms beta

YouTube videos curated by Class Central.

Classroom Contents

Pseudo-Bulk Analysis for Single-Cell RNA-Seq Data - Detailed Workflow Tutorial

Automatically move to the next video in the Classroom when playback concludes

  1. 1 Intro
  2. 2 WHAT is pseudo-bulk analysis?
  3. 3 WHY perform pseudo-bulk analysis?
  4. 4 onwards HOW to perform pseudo-bulk analysis?
  5. 5 Fetch data from ExperimentHub
  6. 6 QC and filtering
  7. 7 Seurat's standard workflow steps
  8. 8 Visualize data
  9. 9 To use integrated or nonintegrated data?
  10. 10 Aggregate counts to sample level
  11. 11 Data manipulation step 1: Transpose matrix
  12. 12 Data manipulation step 2: Split data frame
  13. 13 Data manipulation step 3: Fix row.names and transpose again
  14. 14 DESeq2 step 1: Get count matrix corresponding to a cell type
  15. 15 : Create sample level metadata i.e. colData
  16. 16 DESeq2 step 2: Create DESeq2 dataset from matrix
  17. 17 DESeq2 step 2: Run DESeq
  18. 18 Get results

Never Stop Learning.

Get personalized course recommendations, track subjects and courses with reminders, and more.

Someone learning on their laptop while sitting on the floor.