System requirements
- Windows 7, Windows 8, Windows 10, Windows Server 2012, Windows Server 2016 and Windows Server 2019
- OS X 10.11 and macOS 10.12, 10.13 and 10.14
- Linux: RHEL 7 and later, SUSE Linux Enterprise Server 12 and later. The software is expected to run without problem on other recent Linux systems, but we do not guarantee this. To use BLAST related functionality, libnsl.so.1 is required.
- 64 bit operating system
- 2 GB RAM required
- 4 GB RAM recommended
- 1024 x 768 display required
- 1600 x 1200 display recommended
- Intel or AMD CPU required
Special system requirements for the 3D Molecule Viewer
- Requirements
- A graphics card capable of supporting OpenGL 2.0.
- Updated graphics drivers. Please make sure the latest driver for the graphics card is installed.
- Recommendations
- A discrete graphics card from either Nvidia or AMD/ATI. Modern integrated graphics cards (such as the Intel HD Graphics series) may also be used, but these are usually slower than the discrete cards.
Indirect rendering (such as x11 forwarding through ssh), remote desktop connection/VNC, and running in virtual machines is not supported.
Special system requirements for read mapping
. The numbers below give minimum and recommended memory for systems running mapping and analysis tasks. The requirements suggested are based on the genome size.- E. coli K12 (4.6 megabases)
- Minimum: 2 GB RAM
- Recommended: 4 GB RAM
- C. elegans (100 megabases) and Arabidopsis thaliana (120 megabases)
- Minimum: 2 GB RAM
- Recommended: 4 GB RAM
- Zebrafish (1.5 gigabases)
- Minimum: 2 GB RAM
- Recommended: 4 GB RAM
- Human (3.2 gigabases) and Mouse (2.7 gigabases)
- Minimum: 6 GB RAM
- Recommended: 8 GB RAM
Special requirements for de novo assembly
. De novo assembly may need more memory than stated above - this depends both on the number of reads, error profile and the complexity and size of the genome. See http://resources.qiagenbioinformatics.com/white-papers/White_paper_on_de_novo_assembly_4.pdf for examples of the memory usage of various data sets.
Subsections