Difference between revisions of "Quality Control and Preprocessing Exercise"
| Line 14: | Line 14: | ||
* FastQC: http://www.bioinformatics.babraham.ac.uk/projects/fastqc/ | * FastQC: http://www.bioinformatics.babraham.ac.uk/projects/fastqc/ | ||
| − | |||
* FastqMcf: https://code.google.com/p/ea-utils/wiki/FastqMcf | * FastqMcf: https://code.google.com/p/ea-utils/wiki/FastqMcf | ||
| − | module load ea-utils | + | module load FASTQC ea-utils |
* The data set you'll be using is downloaded from ENA (http://www.ebi.ac.uk/ena/data/view/SRP019027). | * The data set you'll be using is downloaded from ENA (http://www.ebi.ac.uk/ena/data/view/SRP019027). | ||
| Line 23: | Line 22: | ||
= View data set = | = View data set = | ||
| − | cd $HOME/i2rda_data/ | + | cd $HOME/i2rda_data/Quality_Control_and_Preprocessing |
zcat Read_1.fastq.gz |head | zcat Read_1.fastq.gz |head | ||
zcat Read_2.fastq.gz |head | zcat Read_2.fastq.gz |head | ||
| + | |||
| + | where: | ||
| + | * zcat outputs gzip-compress files to the screen | ||
| + | * | is the piple operator takes output, converts it to input | ||
| + | * head, only prints first ten lines of input. | ||
= Assessment of data quality = | = Assessment of data quality = | ||
| + | |||
Run FastQC on the raw data: | Run FastQC on the raw data: | ||
| Line 34: | Line 39: | ||
where: | where: | ||
| − | * --nogroup | + | * --nogroup, for visualisation purposes, prevents grouping of bases after read length of 50bp, so reports will show data for every base in the read. |
Look at the FastQC results and answer the following questions: | Look at the FastQC results and answer the following questions: | ||
| Line 46: | Line 51: | ||
Trim reads using Fastq-Mcf: | Trim reads using Fastq-Mcf: | ||
| − | fastq-mcf -o | + | fastq-mcf -o Read_1_q32l50.fastq.qz -o Read_2_q32l50.fastq.qz -q 32 -l 50 \ |
| − | + | --qual-mean 32 adapters.fasta Read_1.fastq.gz Read_2.fastq.gz | |
| − | --qual-mean | ||
<ins>where</ins>: | <ins>where</ins>: | ||
| Line 55: | Line 59: | ||
* -l Minimum remaining sequence length | * -l Minimum remaining sequence length | ||
* --qual-mean - Minimum mean quality score | * --qual-mean - Minimum mean quality score | ||
| + | |||
| + | As you can see fastq-mcf is able to deal with multiple files in the one command. | ||
= Reassessment of data quality = | = Reassessment of data quality = | ||
Run FastQC on the trimmed reads: | Run FastQC on the trimmed reads: | ||
| − | fastqc --nogroup | + | fastqc --nogroup Read_1_q32l50.fastq.gz Read_2_q32l50.fastq.gz |
| − | firefox Read* | + | firefox Read*q34l50*fastqc.html |
Look at the FastQC results and answer the following questions: | Look at the FastQC results and answer the following questions: | ||
Revision as of 13:30, 5 May 2017
Contents
Motivation
NGS can be affected by a range of artefacts that arise during the library preparation and sequencing processes including:
- low base quality
- contamination with adapter sequences
- biases in base composition
Aims
In this part you will learn to:
- assess the intrinsic quality of raw reads using metrics generated by the sequencing platform (e.g. quality scores)
- pre-process data, i.e. trimming the poor quality bases and adapters from raw reads
You will use the following tools, which are available through the module load/unload system:
- FastQC: http://www.bioinformatics.babraham.ac.uk/projects/fastqc/
- FastqMcf: https://code.google.com/p/ea-utils/wiki/FastqMcf
module load FASTQC ea-utils
- The data set you'll be using is downloaded from ENA (http://www.ebi.ac.uk/ena/data/view/SRP019027).
- The reads belong to sample SRR769316, though this has been modified for course timing reasons.
View data set
cd $HOME/i2rda_data/Quality_Control_and_Preprocessing zcat Read_1.fastq.gz |head zcat Read_2.fastq.gz |head
where:
- zcat outputs gzip-compress files to the screen
- | is the piple operator takes output, converts it to input
- head, only prints first ten lines of input.
Assessment of data quality
Run FastQC on the raw data:
fastqc --nogroup Read_1.fastq.gz Read_2.fastq.gz firefox Read_*_fastqc.html &
where:
- --nogroup, for visualisation purposes, prevents grouping of bases after read length of 50bp, so reports will show data for every base in the read.
Look at the FastQC results and answer the following questions:
- What is the quality encoding?
- How many reads are present in each fastq file?
- What is the length of the reads?
- Are there any adapter sequences observed?
- Which parameters you think should be used for trimming the reads?
Pre-processing of data
Trim reads using Fastq-Mcf:
fastq-mcf -o Read_1_q32l50.fastq.qz -o Read_2_q32l50.fastq.qz -q 32 -l 50 \ --qual-mean 32 adapters.fasta Read_1.fastq.gz Read_2.fastq.gz
where:
- -o output file
- -q quality threshold causing base removal
- -l Minimum remaining sequence length
- --qual-mean - Minimum mean quality score
As you can see fastq-mcf is able to deal with multiple files in the one command.
Reassessment of data quality
Run FastQC on the trimmed reads:
fastqc --nogroup Read_1_q32l50.fastq.gz Read_2_q32l50.fastq.gz firefox Read*q34l50*fastqc.html
Look at the FastQC results and answer the following questions:
- How many reads are present in each fastq file?
- What is the length of the reads?
- Did qualities improve?
