Session 3 - Variant analysis using Nanopore data

Overview of today’s session:

Learn to use CONDA to install tools and create conda environments
Hands-on exercises:
- Quality Control (QC) of raw Nanopore data
- Mapping of processed Nanopore data onto a reference genome
- Run the epi2me-labs/wf-human-variation nextflow pipeline

Public Nanopore Datasets

Experiment Accession

sample

FASTQ

Experiment Title

Organism Name

Instrument

Submitter

Study Accession

Study Title

Sample Accession

Total Size, Mb

Total Spots

Total Bases

Library Strategy

Library Source

Library Selection

SRX14748451

S1

SRR18645307

Homo sapiens

MinION

Drexel University

SRP367676

Multiplex structural variant detection by whole-genome mapping and nanopore sequencing.

SRS12509856

821.1

348226

972620520

OTHER

GENOMIC

other

ERX8211413

S3

ERR8578833

MinION sequencing

Homo sapiens

MinION

the university of hong kong

ERP135493

Target enrichment sequencing and variant calling on medical exome using ONT MinION

ERS10590135

8961.02

9636172

10382057986

Targeted-Capture

GENOMIC

PCR

SRX13322984

S5

SRR17138639

Nanopore targeted sequencing (ReadUntil/ReadFish) of NA12878-HG001- basecalled sequences

Homo sapiens

MinION

Garvan Institute of Medical Research

SRP349335

Comprehensive genetic diagnosis of tandem repeat expansion disorders with programmable targeted nanopore sequencing

SRS11230712

6629.97

5513156

7815960904

WGS

GENOMIC

other

SRX13323057

S6

SRR17138566

Nanopore targeted sequencing (ReadUntil/ReadFish) of NA12878-HG001- basecalled sequences

Homo sapiens

MinION

Garvan Institute of Medical Research

SRP349335

Comprehensive genetic diagnosis of tandem repeat expansion disorders with programmable targeted nanopore sequencing

SRS11230747

17107.98

12278391

20238395479

WGS

GENOMIC

other

What is conda?

Conda is a powerful command line tool for package and environment management that runs on Windows, macOS, and Linux.

Installing conda

Source: https://conda.io/projects/conda/en/latest/user-guide/install/index.html

To install conda, you must first pick the right installer for you. The following are the most popular installers currently available:

Miniconda

Miniconda is a minimal installer provided by Anaconda. Use this installer if you want to install most packages yourself.

Anaconda Distribution

Anaconda Distribution is a full featured installer that comes with a suite of packages for data science, as well as Anaconda Navigator, a GUI application for working with conda environments.

NOTE: if you have already installed conda then you do not need to do the steps below

NOTE: if you have already installed conda then you do not need to do the steps below

Download Miniconda installer for your system https://docs.anaconda.com/free/miniconda/

As we are working with the HPC (Linux) copy and paste the following to your terminal to install Miniconda:

mkdir -p ~/miniconda3
wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh -O ~/miniconda3/miniconda.sh
bash ~/miniconda3/miniconda.sh -b -u -p ~/miniconda3
rm -rf ~/miniconda3/miniconda.sh

After installing initialise the newly installed Miniconda by running the following:

~/miniconda3/bin/conda init bash

Now close your terminal and open it again to be able to use conda.

Once logged in you will be able to access the conda “base” environment

Configure conda channels https://bioconda.github.io/

conda config --add channels defaults
conda config --add channels bioconda
conda config --add channels conda-forge
conda config --set channel_priority strict

Source for information below: https://astrobiomike.github.io/unix/conda-intro

Base environment

The “base” conda environment is, like it sounds, kind of our home base inside conda. We wouldn’t want to install lots of complicated programs here, as the more things added, the more likely something is going to end up having a conflict. But the base environment is somewhere we might want to install smaller programs that we tend to use a lot (example below).

Making a new environment

The simplest way we can create a new conda environment is like so:

Where the base command is conda create, then we are specifying the name of our new environment with -n (here “new-env”). It will check some things out and tell us where it is going to put it, when we hit yand enter, it will be created.

Entering an environment

To enter that environment, we need to execute:

And now we can see our prompt has changed to have (new-env) at the front, telling us we are in that environment.

If we had forgotten the name, or wanted to see all of our environments, we can do so with:

Which will print out all of the available conda environments, and have an asterisk next to the one we are currently in.

Exiting an environment

We can exit whatever conda environment we are currently in by running:

Making an environment with a specific python version

By default, the conda create command will use the python version that the base conda environment is running. But we can specify a different one in the command if we’d like:

Breakdown
conda create – this is our base command
-n python-v2.7 – we are naming the environment “python-v2.7”
python=2.7 – here we are specifying the python version to use within the environment

Removing an environment

And here is how we can remove an environment, by providing its name to the -n flag: