Genome assembly evaluation tool
QUAST evaluates genome assemblies by computing various metrics.
It works both with and without reference genomes.
The tool accepts multiple assemblies, thus is suitable for comparison.
QUAST automatically compiles all its sub-parts when needed (on the first use).
Thus, installation is not required. However, if you want to precompile everything and add quast.py to your
PATH, you may choose either:
Basic installation (about 120 MB):
Full installation (about 540 MB, includes (1) tools for SV detection based on read pairs, which is used for more precise misassembly detection, (2) and tools/data for reference genome detection in metagenomic datasets):
The default installation location is
/usr/local/bin/ for the executable scripts, and
the python modules and auxiliary files. If you are getting a permission error during the installation, consider running setup.py with
sudo, or create a virtual python environment and install into it.
Alternatively, you may use old-style installation scripts (
./install.sh or ./install_full.sh`), which build QUAST package inplace.
./quast.py test_data/contigs_1.fasta \ test_data/contigs_2.fasta \ -R test_data/reference.fasta.gz \ -G test_data/genes.txt \ -O test_data/operons.txt \ -1 test_data/reads1.fastq.gz -2 test_data/reads2.fastq.gz \ -o quast_test_output
report.txt summary table report.tsv tab-separated version, for parsing, or for spreadsheets (Google Docs, Excel, etc) report.tex Latex version report.pdf PDF version, includes all tables and plots for some statistics report.html everything in an interactive HTML file icarus.html Icarus main menu with links to interactive viewers contigs_reports/ [only if a reference genome is provided] misassemblies_report detailed report on misassemblies unaligned_report detailed report on unaligned and partially unaligned contigs k_mer_stats/ [only if --k-mer-stats is specified] kmers_report detailed report on k-mer-based metrics reads_stats/ [only if reads are provided] reads_report detailed report on mapped reads statistics
Metrics based only on contigs:
- Number of large contigs (i.e., longer than 500 bp) and total length of them.
- Length of the largest contig.
- N50 (length of a contig, such that all the contigs of at least the same length together cover at least 50% of the assembly).
- Number of predicted genes, discovered either by GeneMark.hmm (for prokaryotes), GeneMark-ES or GlimmerHMM (for eukaryotes), or MetaGeneMark (for metagenomes).
When a reference is given:
- Numbers of misassemblies of different kinds (inversions, relocations, translocations, interspecies translocations (metaQUAST only) or local).
- Number and total length of unaligned contigs.
- Numbers of mismatches and indels, over the assembly and per 100 kb.
- Genome fraction %, assembled part of the reference.
- Duplication ratio, the total number of aligned bases in the assembly divided by the total number of those in the reference. If the assembly contains many contigs that cover the same regions, its duplication ratio will significantly exceed 1. This occurs due to multiple reasons, including overestimating repeat multiplicities and overlaps between contigs.
- Number of genes in the assembly, completely or partially covered, based on a user-provided list of gene positions in the reference.
- NGA50, a reference-aware version of N50 metric. It is calculated using aligned blocks instead of contigs. Such blocks are obtained after removing unaligned regions, and then splitting contigs at misassembly breakpoints. Thus, NGA50 is the length of a block, such that all the blocks of at least the same length together cover at least 50% of the reference.
For the full documentation, see the manual.html.
You can also check out the web interface: http://quast.bioinf.spbau.ru
Please refer to the LICENSE.txt file for copyrights and citing instructions.
Linux (64-bit and 32-bit with slightly limited functionality) and macOS (OS X) are supported.
For the main pipeline:
- Python2 (2.5 or higher) or Python3 (3.3 or higher)
- Perl 5.6.0 or higher
- GCC 4.7 or higher
- basic UNIX tools (make, sh, sed, awk, ar)
For the optional submodules:
- Time::HiRes perl module for GeneMark-ES (needed when using
- Java 1.8 or later for GRIDSS (needed for SV detection)
- R for GRIDSS (needed for SV detection)
Most of those tools are usually preinstalled on Linux. Mac OS X, however, requires to install the Command Line Tools for Xcode to make them available.
QUAST draws plots in two formats: HTML and PDF. If you need the PDF versions, make sure that you have installed Matplotlib. We recommend to use Matplotlib version 1.1 or higher. QUAST is fully tested with Matplotlib v.1.3.1. Installation on Ubuntu:
sudo apt-get update && sudo apt-get install -y pkg-config libfreetype6-dev libpng-dev python-matplotlib