e-learning
Inferring single cell trajectories with Monocle3
Abstract
This tutorial is a follow-up to the 'Single-cell RNA-seq: Case Study'. We will use the same sample from the previous tutorials. If you haven’t done them yet, it’s highly recommended that you go through them to get an idea how to prepare a single cell matrix, combine datasets and filter, plot and process scRNA-seq data to get the data in the form we’ll be working on today.
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 can I prepare input files for Monocle starting from an AnnData object?
- How can I infer lineage relationships between clusters, without a time series?
- What can trajectory analysis tell us?
Learning Objectives
- Identify which operations to perform on an AnnData object to obtain the files needed for Monocle
- Follow the Monocle3 workflow and choose the right parameter values
- Compare the outputs from Scanpy and Monocle
- Interpet trajectory analysis results
Licence: Creative Commons Attribution 4.0 International
Keywords: 10x, MIGHTS, Single Cell, paper-replication
Target audience: Students
Resource type: e-learning
Version: 20
Status: Active
Prerequisites:
- Combining single cell datasets after pre-processing
- Converting between common single cell data formats
- Filter, plot and explore single-cell RNA-seq data with Scanpy
- Generating a single cell matrix using Alevin
- Inferring single cell trajectories with Scanpy (Python)
- Introduction to Galaxy Analyses
Learning objectives:
- Identify which operations to perform on an AnnData object to obtain the files needed for Monocle
- Follow the Monocle3 workflow and choose the right parameter values
- Compare the outputs from Scanpy and Monocle
- Interpet trajectory analysis results
Date modified: 2024-10-28
Date published: 2022-09-30
Contributors: Helena Rasche, Wendi Bacon
Scientific topics: Transcriptomics
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