LASERGENE GENOMICS TECHNICAL REQUIREMENTS
Lasergene Genomics Technical Requirements
Lasergene Genomics workflows run efficiently on many modern laptops and desktops. Performance depends primarily on dataset size, available RAM, and storage speed.
SeqMan NGen v19 includes performance improvements for many reference-guided and long-read assembly workflows through both algorithm enhancements and optimization for modern hardware.
Start by reviewing the storage recommendations below, then explore the workflow-specific recommendations based on your analysis needs.
Storage Recommendations for Optimal Performance
Storage configuration is one of the most important factors affecting SeqMan NGen performance and workflow stability, especially for large genome assembly projects.
For best results, use an SSD or NVMe drive with sufficient free space for input, temporary, and output files.
- Use a single SSD or NVMe drive for input, temporary, and output files.
- Regularly remove old files to maximize available free space.
- Test read/write speeds before running large projects.
- A minimum read/write speed of about 250 MB/s is recommended for good performance.
- For best performance, use hardware capable of read/write speeds greater than 2000 MB/s.
- External Thunderbolt and USB4 SSDs can provide excellent performance for large genome assembly workflows.
- For large external 4 TB drives, fan-cooled enclosures are recommended to help maintain performance and reliability during extended workflows.
Workflow-Specific Recommendations
Select a workflow below to view workflow-specific hardware recommendations.
Reference-Guided and Long-Read De Novo Assembly
Reference-guided and long-read genome assembly workflows benefit from fast SSD or NVMe storage, sufficient RAM, and available disk space for temporary and output files. Performance depends heavily on dataset size, available RAM, storage speed, and workflow complexity.
Recommended Configuration
| Component | Recommendation |
|---|---|
| RAM | 32-64 GB RAM is sufficient for most reference-guided assembly workflows. Larger long-read de novo assembly workflows may require 64+ GB RAM. |
| Storage | High-throughput SSD or NVMe storage strongly recommended |
| System Type | Modern laptop or desktop for smaller datasets; desktop workstation recommended for large eukaryotic genomes |
| Storage Capacity | 1 TB recommended for microbial datasets; 4 TB recommended for larger eukaryotic datasets |
Typical Workflows
- Human exome analysis
- Variant analysis
- Reference-guided genome assembly
- RNA-Seq alignment
- PacBio HiFi assembly
- Oxford Nanopore duplex assembly
- Large contig genome assembly
NGS De Novo Genome Assembly
Short-read de novo assembly workflows are primarily dependent on available RAM and dataset size.
Recommended Configuration
| Component | Recommendation |
|---|---|
| RAM | 32–64+ GB depending on genome size and coverage |
| Storage | SSD recommended |
| System Type | Modern laptop or desktop |
Typical Workflows
- Viral genome assembly
- Microbial genome assembly
- Short-read Illumina and Element workflows
Need Help Choosing a System?
Our team can help recommend hardware configurations based on your workflow, sequencing platform, genome size, and expected dataset scale.
