e-learning

Filter, plot and explore single-cell RNA-seq data with Scanpy (Python)

Abstract

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

  • Is my single cell dataset a quality dataset?
  • How do I generate and annotate cell clusters?
  • How do I pick thresholds and parameters in my analysis? What's a "reasonable" number, and will the world collapse if I pick the wrong one?

Learning Objectives

  • Interpret quality control plots to direct parameter decisions
  • Repeat analysis from matrix to clustering
  • Identify decision-making points
  • Appraise data outputs and decisions
  • Explain why single cell analysis is an iterative (i.e. the first plots you generate are not final, but rather you go back and re-analyse your data repeatedly) process

Licence: Creative Commons Attribution 4.0 International

Keywords: 10x, MIGHTS, Python, Single Cell, jupyter-notebook, paper-replication

Target audience: Students

Resource type: e-learning

Version: 12

Status: Active

Prerequisites:

  • Combining single cell datasets after pre-processing
  • Generating a single cell matrix using Alevin
  • Introduction to Galaxy Analyses

Learning objectives:

  • Interpret quality control plots to direct parameter decisions
  • Repeat analysis from matrix to clustering
  • Identify decision-making points
  • Appraise data outputs and decisions
  • Explain why single cell analysis is an iterative (i.e. the first plots you generate are not final, but rather you go back and re-analyse your data repeatedly) process

Date modified: 2024-10-28

Date published: 2023-08-25

Authors: Morgan Howells, Wendi Bacon


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