GRC Sequencing Instrumentation
Illumina NovaSeq 6000 Sequencer
Learn more about the NovaSeq6000 system
NovaSeq 6000 Performance Specifications
NovaSeq Applications:
- Whole Genome Sequencing
- Whole Exome Sequencing
- Whole Transcriptome Sequencing
Illumina NextSeq 550
Learn more about the NextSeq 550 System
NextSeq 550 Performance Specifications
NextSeq 550 Applications:
- Gene Expression Profiling
- Exome Sequencing
- Whole Genome Sequencing
Illumina MiSeq
Learn more about the MiSeq System
MiSeq performance specifications
MiSeq Applications:
- Amplicon Sequencing
- 16s (microbiome)
- Targeted/Custom Panels
- Rep-seq
- Targeted Amplicon Panels
- TruSeq Cancer Amplicon (LINK)
- TruSight Myeloid Panel (LINK)
- Small Genome Sequencing
Recommended Reads Per Library:
| Application |
Reads per Library |
| mRNA-Seq |
20 - 25 Million |
| Total RNA-Seq |
40 - 50 Million |
| Small RNA-Seq |
20 Million |
| Low Input RNA-Seq |
20 - 25 Million |
| Chip-Seq |
15 Million |
| ATAC-Seq |
50 Million |
| Whole Genome (10X) |
125 Million Pairs |
| Whole Genome (4X) |
50 Million Pairs |
| Whole Genome Bisulfite-Seq (10X) |
125 Million Pairs |
| Whole Exome Sequencing (100X) |
50 Million Pairs |
| Single Cell (10X v3) |
100,000 per Cell |
**The above recommendations are based on Human/Mouse/Rat genomes for simplicity and empirical results from GRC experience. Other organisms may require different sequencing depths (more or less samples per lane). The amount of sequencing performed and the type (single vs pair) is organism and application specific. These recommendations are guidelines and by no means meant to be strict cutoffs. Internal GRC data and cumulative data analysis over the past formed the basis for these suggestions with the sole purpose to help investigators select the most appropriate experiment type for their research goals.
Comparison of Sequencers at the GRC
Illumina HiSeq2500 Sequencer - Obsolesced 2019
Learn more about the HiSeq2500 system
Contact us or use the Sequencing Platform Comparison Tool to find the right alternative for your research needs.
Data Analysis
The GRC currently has 2 bioinformaticians on staff with experience in NGS data analysis methods and workflows. For more information please visit the GRC Bioinformatics Page or contact us.