e-learning
Batch Correction and Integration with Seurat or Scanpy
Abstract
Single cell analyses can be complex. We may have data from different experimental batches, perhaps because we ran our experiments at different times, in different labs, or using different sequencing platforms. Sometimes we might want to combine multiple datasets, for example if we want to compare our own experimental data to a similar public dataset.
About This Material
This is a Hands-on Tutorial from the GTN which is usable either for individual self-study, or as a teaching material in a classroom.
Questions this will address
- What is the difference between batch correction and integration?
- How can we perform batch correction or integration using the Scanpy and Seurat pipelines?
Learning Objectives
- Understand what batch correction and integration are and how they are different
- Know when to perform batch correction or integration on single cell data
- Perform batch correction or integration using either the Scanpy or Seurat pipelines
Licence: Creative Commons Attribution 4.0 International
Keywords: 10x, Single Cell
Competency level: • Beginner
Target audience: Students
Resource type: e-learning
Version: 1
Status: Active
Prerequisites:
- Clustering 3K PBMCs with Scanpy
- Clustering 3K PBMCs with Seurat
- Introduction to Galaxy Analyses
Learning objectives:
- Understand what batch correction and integration are and how they are different
- Know when to perform batch correction or integration on single cell data
- Perform batch correction or integration using either the Scanpy or Seurat pipelines
Date modified: 2026-07-09
Date published: 2026-07-09
Authors: 
Marisa Loach
Contributors: Wendi Bacon, Diana Chiang Jurado
Activity log
