- Unique identifier:
- Command line interface, Graphical user interface
- Input format:
- Biological technology:
- Illumina, Pacific Biosciences, Roche
- Programming languages:
- Computer skills:
- Software type:
- Restrictions to use:
- Output format:
- Operating system:
- Unix/Linux, Mac OS, Windows
- GNU General Public License version 3.0, GNU General Public License version 2.0
- Picard BAM/SAM,JRE
- Simon Andrews <>
No open topic.
Babraham Institute, Cambridge, UK
2 user reviews
2 user reviews
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:
A well written documentation on the analysis modules is available at the below link:
Bugs can be tracked or reported on bugzilla at the below link
Installation is quite easy for a person having intermediate knowledge of working on linux. A well written installation documentation is available at below link:
FastQC is a cross-platform application, written in java.
- 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
- Some of the metrics work on a subset of the overall data hence the interpretation may vary.