Technical Requirements

DNASTAR Lasergene Full Suite or Lasergene Genomics Suite


Hardware requirements for Lasergene Genomics Suite or the DNASTAR Lasergene package are largely dependent upon whether you will be doing reference-guided or de novo assemblies. Please see the following sections for details of the technical requirements for each project type. If you ever need help, we welcome your call to help you through the hardware or software installation process.

For a network version of our software, please see our DNASTAR License Server Technical Requirements.

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Supported Operating Systems

Windows 7, 8, or 8.1 (64-bit)

Mac OSX 10.7 or higher*

Linux Ubuntu 12.04**

Linux CentOS 6.5**

* Note that ArrayStar and QSeq were designed to run on Windows operating systems only. However, you can run ArrayStar and QSeq on a Macintosh with an Intel processor by using Parallels Desktop with Windows 7 or higher installed.

**Linux operating systems are supported for SeqMan NGen only.

Reference-Guided Alignments

  • 16 GB RAM
  • Quad-Core 3 GHz processor
  • One 1-8 TB* hard drive for storing temporary files ("scratch disk")
  • One 1 TB hard drive for storing output files

*The size of the hard drive required for storing temporary files is largely dependent upon the size of the reference sequence used and the amount of sequence data assembled.  Assembling large data sets to eukaryotic genome sequences generates large temporary files that will require more space than assembling a bacterial genome, for example.

De Novo Assemblies

  • 16-32 GB RAM**
  • Quad-Core 3 GHz processor

**Memory requirements for de novo assemblies increase in proportion to the number of assembled sequences and contigs. We recommend at least 16 GB for de novo microbial genome assemblies and 32GB RAM for de novo transcriptome data sets. During assembly, it may be helpful to watch the Activity Monitor/Task Manager to make sure adequate memory is available. If adequate memory is not available, either reduce the number of input reads or increase RAM.