FastQC statistics

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FastQC specifications


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
Maintained Yes




No version available


  • person_outline Simon Andrews

Additional information

FastQC citations


MLL fusion driven leukemia requires SETD2 to safeguard genomic integrity

Nat Commun
PMCID: 5959866
PMID: 29777171
DOI: 10.1038/s41467-018-04329-y

[…] were prepared using NEBNext Ultra DNA Library Prep Kit for Illumina (New England BioLabs) and sequenced on Illumina HiSeq 4000 using 50 bp single-read chemistry.Raw ChIP-seq reads were evaluated with FastQC (version 0.11.4). Quality-filtering and trimming was done with PRINSEQ-lite (version 0.20.4). Resulting high-quality reads were simultaneously mapped against the Mus musculus (GRCm38) and Droso […]


Elucidating the genetic architecture of reproductive ageing in the Japanese population

Nat Commun
PMCID: 5958096
PMID: 29773799
DOI: 10.1038/s41467-018-04398-z
call_split See protocol

[…] r sequences and default filtering parameters was performed as suggested in the program’s documentation, with exception of a hard clip of the first 13 bases of the reads; this latter step was based on FastQC visualization of the read qualities before trimming, which indicated significantly lower read qualities in those bases as compared to the remainder of the read. Trimmed reads that passed the Tr […]


An epizootic of Chlamydia psittaci equine reproductive loss associated with suspected spillover from native Australian parrots

PMCID: 5953950
PMID: 29765033
DOI: 10.1038/s41426-018-0089-y

[…] ried out on an Illumina HiSeq 2500 platform, generating 125 bp paired-end reads at the Australian Genome Research Facility (AGRF), Parkville, Australia. Read quality for each sample was assessed with FastQC v.0.11.2, prior to trimming, read mapping, and de novo assembly using CLC Genomics workbench (Qiagen, USA). Initial read mapping to the reference C. psittaci 6BC, as well as Horse_pl chromosome […]


Integrated analysis of hepatic mRNA and miRNA profiles identified molecular networks and potential biomarkers of NAFLD

Sci Rep
PMCID: 5955949
PMID: 29769539
DOI: 10.1038/s41598-018-25743-8

[…] We performed quality control on raw sequence data using the FastQC tool. To obtain high-quality, clean data for analysis, adaptor sequence trimming and removal of low-quality reads were performed. Clean reads were aligned with the rat genome using TopHat v2.1. […]


B cell activation and plasma cell differentiation are inhibited by de novo DNA methylation

Nat Commun
PMCID: 5953949
PMID: 29765016
DOI: 10.1038/s41467-018-04234-4

[…] RRBS FASTQ files were quality trimmed using FastQC (v0.11.5) and mapped to the mouse genome (mm9) using Bismark (v0.16.3) using the following options: “--bam --chunkmbs 1024 –multicore 8”. Mapped BAM files were sorted with SAMtools (v0.1.19-96b […]


Case Report: Identification of an HNF1B p.Arg527Gln mutation in a Maltese patient with atypical early onset diabetes and diabetic nephropathy

PMCID: 5952643
PMID: 29764441
DOI: 10.1186/s12902-018-0257-z
call_split See protocol

[…] equence reads were mapped and aligned to the Human Reference Genome (UCSC hg19, NCBI build 37) using the Burrows-Wheeler transformation algorithm, and duplicated reads were removed using Picard [, ]. FastQC was used to check the quality of sequence data []. Calling of SNPs and InDels was done using GATK Unified Genotyper, which uses a Bayesian genotype likelihood model to report alleles and Phred- […]


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FastQC institution(s)
Babraham Institute, Cambridge, UK

FastQC reviews

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Sangram keshari sahu

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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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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

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:

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