This product includes DNA extraction from a human stool sample, library preparation and shotgun metagenomic sequencing.
Product specifications:
- Platform: MGI DNBSEQ T7 sequencer.
- Read length: paired-end 100 bp (PE100).
- Data output: 30 million reads per sample (15 million read pairs, equivalent to 3Gb +/-5%).
- File format: de-multiplexed and compressed FASTQ files.
- Data quality: >85% bases with Q30 or higher.
- Delivery time: 8 - 10 weeks (for a batch size of 24 samples).
Turnaround Times: Returning a full batch size of samples will increase the chances of a quicker turnaround times please note that our turnaround times are estimations and only appilcable for batched returns
Data Transfer and Storage:
- Results can be transferred via SFTP, either using our servers or yours, according to your preference.
- In order to keep costs as low as possible, depenanting on the file size each data download will incur the 'data transfer cost'. For Microbiome Shotgun Metagenomics on MGI T7 this is £3.98.
- Data will be kept on our servers for 60 days to download. After this time data may be archived or deleted, unless you pay for the yearly storage option.
- The yearly storage option will mean we retain a copy of all data for the specified time. If the fee is not renewed yearly, we may delete your data. We are not liable in any way for data loss or corruption.
- Under our fair usage policy, data can only be retrieved once. Additional retrievals will incur the data transfer cost.
- Data access may not be instant and may be subject to a retrieval period
Customise setup and Experimental Designs: For customised workflows and experimental designs, please contact us at support@hurdle.bio for further assistance.
International Orders and Custom Order Quanities :For larger and or international orders outside of the UK, please contact us at support@hurdle.bio
Bioinformatics Services: If you are interested in bioinformatic services downstream of the raw lab data results, please reach out to us at support@hurdle.bio for more details
