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EPI2ME Labs Tutorials
September 01, 2020
2 min
EPI2ME Labs Tutorials

EPI2ME Labs maintains a collection of example bioinformatics notebooks for running analysis in your web browser. Our Python notebook tutorials walk through various topics suitable for bioinfomatics beginners to virtuosos.

Getting Started - Installation

EPI2ME Labs extends the JupyterLab notebook framework with a pre-configured analysis server. The notebooks contain Python code needed to run data analysis, however zero configuration of the code is required. The notebooks can be used both by students and researchers new to nanopore sequence data analysis, and more experienced bioinformaticians who are comfortable working with Python.

See the Notebooks Quickstart page for a walkthrough to guide install the EPI2ME Labs Launcher application which can be used to manage the notebook server environment.

Available notebooks

Below you will find a complete list of available notebooks with a short description of each. Listed also are notebooks in development. The links direct to pre-rendered versions of the notebooks to provide some illustrations of the capabilities of each notebook; these pages are not interactive.

Basic Tasks

  • Introduction to FASTQ - An introduction to the FASTQ format and simple file operations

  • Introduction to VCF

    • An introduction to Variant Call Format files and their manipulation in Python and on the command line.
  • Introduction to BAM - An introduction to the SAM and BAM formats for storing alignment data and their manipulation with samtools.

  • Introduction to FAST5 - A guide to handling raw sequencing data from Oxford Nanopore Technologies’ sequencing devices.

  • Basic QC - A simple workflow using the sequencing summary file, produced by MinKNOW and Guppy, to QC measures such as read length and quality.

  • Alignment QC (Planned) - Walking through alignment of reads to a reference sequence, and and introduction to the world of samtools and pysam.

  • Adaptive Sampling Inputs - A short snippet to aid the creation of the necessary files required by MinKNOW for exome Adaptive Sampling experiment.


  • Assembly tutorial - A workflow utilising Flye and Medaka to produce high quality assemblies of small to mid-sized genomes.

  • Assembly assessment (Planned) - An introduction and tips on assessing the quality of an assembly using both reference-based and reference-free methods.


  • Metagnomic classification - An introduction to Centrifuge and Pavian for the classification of single molecule long-reads, and discovery of What’s in my pot?
  • Post-EPI2ME 16S Analysis - A quick demonstration of adding lineage information to EPI2ME 16S output, and grouping counts by rank.
  • Metagenomic assembly (Planned) - A guided approach to metagenomic assembly and assessment based on Flye’s metagenomic assembly.

cDNA and RNA

  • QC of cDNA reads - A workflow using pyChopper providing preliminary analysis and data filtering of ONT cDNA read datasets.

  • Isoform detection - A tutorial guide for identifying full length transcripts in your cDNA experiments and comparing them against a known annotation.

  • De-novo isoform detection (Planned) - Similar to the Isoform Detection notebook above but using a de-novo, assembly-based method for contructing transcript consensus sequences.

  • Differential Gene Expression - Pipeline for differential gene expression (DGE) and differential transcript usage (DTU) analysis using Nanopore long reads.

Variant calling


  • Clone validation - Validation of synthetic biological constructs using Nanopore sequencing rather than Sanger sequencing.

  • Cas9 Targeted Sequencing - A workflow to complement Cas9 targeted sequencing experiments using ONT devices.

  • SARS-CoV-2 Analysis - A notebook based around the ARTIC pipeline for the analysis of SARS-Cov-2 multiplexed amplicon datasets.

  • Modified bases - A demonstration of the use of Medaka to process and summarise the optional modified base output of Guppy.

  • Medaka tech. demo - A deep dive into the inner workings of Oxford Nanopore Technologies’ Medaka software

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