bioinformatics genomic life sciences long read sequencing
The dataset contains reference samples that will be useful for benchmarking and comparing bioinformatics tools for genome analysis. Currently, there are two samples, which are NA12878 (HG001) and NA24385 (HG002), sequenced on an Oxford Nanopore Technologies (ONT) PromethION using the latest R10.4.1 flowcells. Raw signal data output by the sequencer is provided for these datasets in BLOW5 format, and can be rebasecalled when basecalling software updates bring accuracy and feature improvements over the years. Raw signal data is not only for rebasecalling, but also can be used for emerging bioinformatics tools that directly analyse raw signal data. We also provide the basecalled data alongside the raw signal data and will continue to provide updated basecalls when there is a major update to the basecalling software. In the future, we plan to extend this open dataset with additional samples, including sequencing runs from vendors other than ONT.
We plan to extend this open dataset with additional samples, including sequencing runs from vendors other than ONT. We will continue to provide updated basecalls when there is a major update to the basecalling software.
https://github.com/GenTechGp/gtgseq
Genomic Technologies Group, Garvan Institute of Medical Research (https://www.garvan.org.au/research/labs-groups/genomic-technologies-lab)
See all datasets managed by Genomic Technologies Group, Garvan Institute of Medical Research (https://www.garvan.org.au/research/labs-groups/genomic-technologies-lab).
Garvan Institute Long Read Sequencing Benchmark Data was accessed on DATE
from https://registry.opendata.aws/gtgseq. Gamaarachchi, H., Samarakoon, H., Jenner, S.P. et al. Fast nanopore sequencing data analysis with SLOW5. Nat Biotechnol 40, 1026–1029 (2022). https://doi.org/10.1038/s41587-021-01147-4
arn:aws:s3:::gtgseq
us-west-2
aws s3 ls --no-sign-request s3://gtgseq/