FastQC protocols

FastQC specifications

Information


Unique identifier OMICS_01043
Name FastQC
Software type Application/Script
Interface Command line interface, Graphical user interface
Restrictions to use None
Input format FASTQ
Output format HTML
Biological technology Illumina, Pacific Biosciences, Roche
Operating system Unix/Linux, Mac OS, Windows
Programming languages Java
License GNU General Public License version 3.0, GNU General Public License version 2.0
Computer skills Advanced
Version 0.11.7
Stability Stable
Requirements Picard BAM/SAM,JRE
Maintained Yes

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Maintainer


  • person_outline Simon Andrews <>

Additional information


http://www.bioinformatics.babraham.ac.uk/projects/fastqc/Help/1%20Introduction/1.1%20What%20is%20FastQC.html

FastQC IN pipelines

 (683)
2018
PMCID: 5739345
PMID: 29091815
DOI: 10.1016/j.phytochem.2017.10.004

[…] (rna-seq) libraries were constructed using the kappa stranded rna-seq kit and libraries were sequenced on an illumina hiseq 2500 generating 150 nt paired-end reads. read quality was assessed using fastqc (v0.11.2; http://www.bioinformatics.babraham.ac.uk/projects/fastqc/) with default parameters and adaptors and low quality sequences removed using trimmomatic (parameter: leading:10 trailing:10 […]

2018
PMCID: 5739345
PMID: 29091815
DOI: 10.1016/j.phytochem.2017.10.004

[…] kit and libraries were sequenced on an illumina hiseq 2500 generating 150 nt paired-end reads. read quality was assessed using fastqc (v0.11.2; http://www.bioinformatics.babraham.ac.uk/projects/fastqc/) with default parameters and adaptors and low quality sequences removed using trimmomatic (parameter: leading:10 trailing:10 slidingwindow:4:15 minlen:30) (v0.32, (bolger et al., 2014). […]

2018
PMCID: 5754486
PMID: 29301877
DOI: 10.1128/genomeA.01391-17

[…] using a paired-end read length of 2 × 101 bp, and genome libraries were constructed using a truseq dna pcr-free library preparation kit (illumina, inc.). the quality of the raw data was checked with fastqc (8), and adapters were trimmed with trimmomatic (9). the genomes were assembled with velvet version 1.2.10 (10) and annotated with the ncbi prokaryotic genome annotation pipeline (11)., […]

2018
PMCID: 5755806
PMID: 29304111
DOI: 10.1371/journal.pone.0190670

[…] an agilent technologies 2100 bioanalyzer with a high-sensitivity chip. the libraries were enriched using adapter-compatible pcr primers., the quality of the raw sequence reads was confirmed using fastqc v0.10.1, and the adapters and low-quality reads were filtered. the filtered high-quality sequences were aligned and mapped onto the b73 reference genome […]

2018
PMCID: 5758603
PMID: 29354153
DOI: 10.3389/fpls.2017.02226

[…] as a reference, differential gene expression analysis was carried out based on published protocols (trapnell et al., 2012). briefly, raw sequencing data were first evaluated with the fastqc program. all filtered and properly paired reads were then mapped to the arabidopsis genome using tophat. the fragment alignments generated by tophat were then used as input files […]

FastQC institution(s)
Babraham Institute, Cambridge, UK

FastQC reviews

 (3)
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Sangram keshari sahu

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Desktop
One of the oldest and basic tools for NGS data quality check. Every sequencing project needs this tool to determine various aspects of the sequencing output results in each step of the analysis. I have used this tool from my very start day with NGS data analysis.

Vijay Lakhujani

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Desktop
I am using FastQC on a daily basis for a number of samples obtained using sequencing run. I am writing this review after 3.5 years of usage.

1. Very simple tool
I must say this is a fairly simple tool used during the first step of ngs analysis i.e. quality check. A series of tests are perfomed and each test is flagged as pass/warning/fail which depends on how far it departs from the ideal expectations.It is possible that the biological. With not too many options in the UI version, its intuitive to use and work with. Even the command line version is fairly simple.

2. Support for variety of platforms
The tools supports NGS data(fatsq) files generated on many plaforms such Illumina-HiSeq, MiSeq, pacbio, 454 etc. This makes it number one choice to get a quick assesment of quality.

3. Quality check on multiple aspects:
The tool generates colored reports on 8-10 different quality assesment metrics such as read length distribution, quality distribution, per base GC content, adapter contamination level, kmer distibution etc. This provides a global picture of the complete quality of data.

4. Automation Level:
The tools is available in 2 modes - intractive and command line. THe interactive mode allows to view results for multiple files in a single
application. Alternatively, the non interactive mode(command line) generates an HTML report for each file processed.The command line version provides a fantastic utility to automate the analysis on multiple samples (paired and unpaired fastq files) at once. User can define the number of cores using the -t option for no. of threads. It also supports wild card character example the '*' for subsetting the fastq files based on their names or extension.

5. Development, support and documentation:
The tools is well maintained and being constantly developed for bug fixes and new features. It is supported on windows,linux and mac. The latest vertsion v11.5 was released on 08-03-16. Release notes are well maintained and could be found at:
https://www.bioinformatics.babraham.ac.uk/projects/fastqc/RELEASE_NOTES.txt

A well written documentation on the analysis modules is available at the below link:
https://www.bioinformatics.babraham.ac.uk/projects/fastqc/Help/

Bugs can be tracked or reported on bugzilla at the below link
http://www.bioinformatics.babraham.ac.uk/bugzilla/buglist.cgi?quicksearch=fastqc

6. Installation
Installation is quite easy for a person having intermediate knowledge of working on linux. A well written installation documentation is available at below link:
https://www.bioinformatics.babraham.ac.uk/projects/fastqc/INSTALL.txt

Requirements:
FastQC is a cross-platform application, written in java.
- java


Pros
- cross platform (runs on windows, linux and mac), user friendly
- interactive and command line mode
- comprehensive html summary reports
- suitable for data generated on variety of platforms
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Cons
- Some of the metrics work on a subset of the overall data hence the interpretation may vary.