Ion GeneStudio System Models | Thermo Fisher Scientific

Choose your system

	Ion GeneStudio S5 System	Ion GeneStudio S5 Plus System	Ion GeneStudio S5 Prime System
Max. throughput/day (chip type)	15 Gb (one Ion 540 Chip)	30 Gb (two Ion 540 chips)	50 Gb (two Ion 550 chips)
Total sequencing and analysis time at max. throughput	19 hr (Ion 540 Chip)	10 hr (Ion 540 Chip) 11.5 hr (Ion 550 Chip)	6.5 hr (Ion 540 Chip) 8.5 hr (Ion 550 Chip)
Compatible chips	Ion 510, 520, 530, 540 chips	Ion 510, 520, 530, 540, and 550 chips

Detailed system specs

Flexibility in throughput and workflow for a broad range of NGS applications

Chip type	Number of reads	Read length (output) †	Ion GeneStudio S5 System	Ion GeneStudio S5 Plus System	Ion GeneStudio S5 Prime System
Chip type	Number of reads	Read length (output) †	*Turnaround time (sequencing run and analysis time)**
Ion 510 Chip	2–3M	200 bp (0.3–0.5 Gb)	4.5 hr	3 hr	3 hr
Ion 510 Chip	2–3M	400 bp (0.6–1 Gb)	10.5 hr	5 hr	5 hr
Ion 520 Chip	4–6M	200 bp (0.6–1 Gb)	7.5 hr	3.5 hr	3 hr
	4–6M	400 bp (1.2–2 Gb)	12 hr	5.5 hr	5.5 hr
	3–4M	600 bp (0.5–1.5 Gb)	12 hr	5.5 hr	5.5 hr
Ion 530 Chip	15–20M	200 bp (3–4 Gb)	10.5 hr	5 hr	4 hr
	15–20M	400 bp (6-8 Gb)	21.5 hr	8 hr	6.5 hr
	9–12M	600 bp (1.5–4.5 Gb)	21 hr	8 hr	7 hr
Ion 540 Chip	60–80M	200 bp (10–15 Gb)	19 hr	10 hr	6.5 hr
Ion 540 Chip	60–80M	200 bp (20–30 Gb) 2 runs in 1 day	N/A	20 hr	10** hr
Ion 550 Chip	100–130M	200 bp (20–25 Gb)	N/A	11.5 hr	8.5 hr
Ion 550 Chip	100–130M	200 bp (40–50 Gb) 2 runs in 1 day	N/A	N/A	12** hr

† Expected output with >99% aligned/measured accuracy. Output dependent on read length and application.
* Sequencing run times are between 2.5 and 4 hrs.
** Analysis of first run occurs concurrently with the second sequencing run.

Choose your chip

Example of our popular panels and applications	Panel description	Number of samples per run*
Example of our popular panels and applications	Panel description	Ion 510 Chip 2-3M reads	Ion 520 Chip 4-6M reads	Ion 530 Chip 15-20M reads	Ion 540 Chip 60-80M reads	Ion 550 Chip 100-130M reads
Cancer research
Ion AmpliSeq Cancer Hotspot Panel v2	Identify cancer hotspot SNVs from 10 ng of FFPE derived DNA	4	8	26	84	NA
Oncomine Focus Assay	Identify solid tumor-relevant SNVs, indels, CNVs, and gene fusions from 52 genes	4	8	26	NA	NA
Oncomine Comprehensive Assay v3	Enable biomarker discovery of SNVs and indels and full gene sequencing from 161 genes	NA	NA	NA	8	16
Oncomine Lung cfDNA Assay	Detect rare somatic mutations in genes relevant to non-small cell lung cancer	NA	NA	8	32	~60-64
Oncomine Pan-Cancer Cell-Free Assay	Detect rare somatic mutations in genes across multiple cancer types	NA	NA	1	4	7-8
Oncomine Immune Response Research Assay	interrogate genes involved in immune response pathways	NA	4	8	NA	NA
Gene expression
Ion AmpliSeq Transcriptome Human Gene Expression Kit	Research global gene expression levels	NA	NA	2	8	16
Ion AmpliSeq Transcriptome Mouse Gene Expression Kit	Research global gene expression levels	NA	NA	2	8	16
Inherited disease research
Ion AmpliSeq Exome RDY Panel	Discover rare mutations of the whole exome	NA	NA	NA	2	4
Ion AmpliSeq Pharmacogenomics Research Panel (40 genes)	Investigate known variants associated with drug metabolism	48	96	384	384	NA
Ion AmpliSeq On-Demand Panel	Identify variants in genes associated with inherited disease	Up to 384 (varies by number of genes in panel)
Reproductive health research
Ion ReproSeq PGS Kits	Identify aneuploidy in DNA from embryo samples	16	24	96	NA	NA
Infectious disease research
Ion AmpliSeq TB Research Panel	Identify variants associated with antimicrobial resistance in Mycobacterium tuberculosis (TB)	48	84	272	384	NA
Ion AmpliSeq Ebola Research Panel	Identify the presence of Ebola virus	48	84	272	384	NA
Ion 16S Metagenomics Kit	Identify bacterial species in mixed samples	24	48	192	NA	NA
* The number of samples per run/chip serves as a guide, and the actual number of samples loaded will depend on your needs for number of reads and depth of coverage. It is important to note that as the number of libraries per chip increases, it becomes more difficult to balance the reads between libraries. In addition, libraries from FFPE tissue tend to produce more variable results. We suggest combining fewer libraries initially and determining real limits empirically.