Last updated: 2021-02-01

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Knit directory: Bio326/

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File	Version	Author	Date	Message
html	b425594	mariesaitou	2021-01-28	Build site.
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html	067284e	mariesaitou	2021-01-28	Build site.
Rmd	76be303	mariesaitou	2021-01-28	Publish the initial files for BIO326
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This workflow is based on Galaxy Training materials aimed for the two-hour courses in Bio326, NMBU 2021. Lecture slide is here: (contains hands-on materials on this page)pdf

The workflow is based on the following materials but modified and updated for Galaxy.no 2021.

Quality Control

Mapping

Variant Analysis

0. Goal of this workflow

Objective: Compare the mitochondrial variants between mother and child (human)

We will learn: A.How to conduct “cleaning” of the data, B.How to map the sequence read to refeerence genome, C. How to call genetic variants.

1. Galaxy introduction

1-2. Play around with Galaxy

1-3. Review the genome analysis workflow

2. Quality Control

2-0. Introduction

During sequencing, the nucleotide bases in a DNA or RNA sample (library) are determined by the sequencer. For each fragment in the library, a short sequence (=read) is generated,.

Modern sequencing technologies can generate a massive number of sequence reads in a single experiment. However, each instrument will generate different types and amount of errors, such as incorrect nucleotides being called. These wrongly called bases are due to the technical limitations.

Therefore, it is necessary to understand, identify and exclude error-types that may impact the interpretation of downstream analysis. Sequence quality control is therefore an essential first step in your analysis. Catching errors early saves time later on.

Objective: Conduct quality control and trimming of sequence data from two individuals, mother and child

We will learn: How to conduct quality control with FastQC, how to interpret FastQC output, how to conduct trimming with fastp.

2-1. Prapere the data

Create a new history.

Import the data set.

Copy and paste the following URLs to import the data:

https://zenodo.org/record/1251112/files/raw_child-ds-1.fq

https://zenodo.org/record/1251112/files/raw_child-ds-2.fq

https://zenodo.org/record/1251112/files/raw_mother-ds-1.fq

https://zenodo.org/record/1251112/files/raw_mother-ds-2.fq

Rename the data for to manage them.

Let’s have a look…

What is written in the FastQ files

2-2. Quality control with fastQC

fastQC (go to the website for details)

Taking too long? Download the data from here: (Will be uploaded)

Let’s see the result of quality check Example results “Per base sequence quality”: X-axis is the base position, Y-axis is the read quality. Green is good, yellow is okay, red is not good.

Our results: We see that the ending part ot our reads shows not good quality. -> Trimming. Per sequence quality score. X-axis is the quality score, Y-axis is the observed count. We see that most of the reads show good quality, but still there are some low-quality reads.