At the GRCF High Throughput Sequencing Center, our goal is to provide the research community at Johns Hopkins University with access to ‘next generation’ sequencing platforms. We currently feature three HiSeq 2500 instruments two MiSeq instruments, and a NovaSeq6000. We do our best to sequence samples in a timely manner, but our primary focus is on generating high quality data.
We offer simple, per lane and per flow cell pricing, along with end to end service for whole exome/custom targeted projects, RNASeq, and whole genome. Illumina is now offering v1.5 reagents for NovaSeq, which lowers cost for runs
Illumina is now offering v1.5 reagents for NovaSeq, which lowers cost for runs
NovaSeq runs are fixed, but include additional cycles for dual indexed libraries.
Per lane loading is possible on NovaSeq, but adds $150 in cost per lane.
|SP: ~1.6 billion paired reads, ~800 million single reads||S1: ~3.2 billion paired reads, ~1.6 billion single reads||S2: ~8.2 billion paired reads, ~4.1 billion single reads||S4: ~20 billion paired reads, ~10 billion single reads|
|100 cycle: $3600||100 cycle: $6000||100 cycle: $9300|
|200 cycle: $4300||200 cycle: $7000||200 cycle: $11100||200 cycle: $15000|
|300 cycle: $4600||300 cycle: $7500||300 cycle: $11600||300 cycle: $17400|
|500 cycle: $5800|
HiSeq2500 Flowcell Pricing (Rapid Mode)
|Single Read Flowcell: ~300 million reads||Paired End Flowcell: ~600 million reads|
|50 bp: $2000 per flowcell||50 bp (x2): $3400 per flowcell|
|75 bp: $2400 per flowcell||75 bp (x2): $4000 per flowcell|
|100 bp: $2800 per flowcell||100 bp (x2): $4400 per flowcell|
|150 bp: $3600 per flowcell||150 bp (x2): $5400 per flowcell|
Non-standard read lengths are also available for Per Flowcell orders. Please inquire about pricing.
High Output Runs are available, but you should consider the NovaSeq for high throughput applications, as the cost per base will be cheaper.
Completed Libraries: For NovaSeq runs, please submit at least 50ul of your sample at 4nM. Please submit 10μl of your sample at 2nM for HiSeq/MiSeq. Samples must be pooled. We will do a QC check via Bioanalyzer to increase the likelihood of quality data, but you should quantitate your sample as accurately as possible. Nanodrop is not reliable. qPCR is by far the most accurate, but intercalating dye methods can be used.
Library Prep: $250/sample. Please provide us with ~500ng of high molecular weight DNA or total RNA >6.5 for this price. There are a host of options for lower input/lower quality that may add cost. Please contact us to discuss sample submission.
Our facility features the HiSeq 2500 platform. We almost exclusively run our instruments in Rapid Run Mode, due to the fast run times and low error rates. Yield is dependent upon several factors:
- Read Length: the longer the read, the more data.
- Read Type: paired end reads yield twice the data as single read.
- Optimal Cluster density: it is imperative to accurately quantitate your library to ensure high data yield. We do our best to QC libraries before sequencing, but we cannot pool samples for you.
- High Quality Library: libraries that contain a high level of adapter dimers will yield significantly less data, particularly on the NovaSeq6000. Similarly, over amplified libraries can negatively impact yield.
- Uniform Base composition: while less of an issue than in the past, libraries that have uneven base composition tend to pose problems with the HiSeq analysis software. These issues can be mitigated using several strategies, but the net effect will be lower data yield per lane than a balanced library.
Please see Illumina’s HiSeq 2500 and NovaSeq6000 Specification page for current data yields. While we regularly achieve greater than ‘spec’ yields from the HiSeq2500 and NovaSeq6000, typicially matching yields, it is best to be conservative when planning your experiments.
Per lane/flowcell sequencing: Data will be returned in Sanger FASTQ format via our high speed aspera server
End to end services: alignment files, variant calls, and any intermediate files you wish via aspera serverPlace Order