e-learning
Single-cell quality control with scater
Abstract
Single-cell RNA-seq (scRNA-seq) is emerging as a promising technology for analysing variability in cell populations. However, the combination of technical noise and intrinsic biological variability makes detecting technical artefacts particularly challenging. Removal of low-quality cells and detection of technical artefacts is critical for accurate downstream analysis.
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
- How to ensure the quality of single-cell RNA-seq data?
- What are the confounding factors that may affect the interpretation of downstream analyses?
Learning Objectives
- Examine scRNA-seq data for low-quality cells
- Visualise data with various types of plots
- Filtering low-quality cells with the appropriate approach
Licence: Creative Commons Attribution 4.0 International
Keywords: Single Cell
Target audience: Students
Resource type: e-learning
Version: 4
Status: Active
Prerequisites:
- Introduction to Galaxy Analyses
- Plates, Batches, and Barcodes
Learning objectives:
- Examine scRNA-seq data for low-quality cells
- Visualise data with various types of plots
- Filtering low-quality cells with the appropriate approach
Date modified: 2023-11-09
Date published: 2019-10-23
Contributors: Graham Etherington, Nicola Soranzo
Scientific topics: Transcriptomics
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