NGS: Single-cell RNA-sequencing Analysis

Course Overview

  • Written by experts
  • Introductory
  • 100% online
  • Video content
  • Multiple choice quiz
  • Approx. x hours to complete
  • Completion certificate
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About this course

Single-cell transcriptomics is a powerful tool to study the heterogeneity of the cellular transcriptome at single-cell levels. This course aims to equip participants with essential skills to process RNA-sequencing reads from single-cell transcriptomics experiment and to perform downstream analyses of the single-cell gene expression data. This course is designed for participants with some experience in R programming and running command-line programs. We will be using published single-cell RNA-sequencing datasets to perform quality control, data normalisation, cell clustering, differential expression and trajectory analyses.

This course is for you if
  • You have basic knowledge in using command-line terminal and in running commands in R
  • You work with, or about to work with, single-cell transcriptomics experiments
  • You need to analyse your own single-cell transcriptomics dataset, or analyse publicly available datasets
  • You require flexible learning format

Learning objectives

  • A broad understanding of different single-cell transcriptomics experiments
  • Confidently process and analyse single-cell transcriptomics datasets
  • Being able to formulate research questions on single-cell transcriptomics analysis and finding answers to these questions

By the end of the course you will be able to:

  • Identify different single-cell sequencing methods and its advantages and disadvantages
  • Explain the various applications of single-cell sequencing experiments
  • Process raw sequencing data from 10x genomics for gene expression analysis
  • Analyse gene expression data in R using the Seurat package
  • Perform single-cell analysis workflow which includes quality control, data normalisation, data clustering, differential expression analysis and trajectory analysis.
  • Visualise single-cell expression data

If you have any questions, please contact innovationscholars@kcl.ac.uk.


Course authors and designers

Dr Fursham Hamid

Lecturer in Bioinformatics







Karla Lozano
Gonzalez