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Garvan Institute Long Read Sequencing Benchmark Data

bioinformatics genomic life sciences long read sequencing

Description

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.

Update Frequency

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.

License

CC BY-NC 4.0

Documentation

https://github.com/GenTechGp/gtgseq

Managed By

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).

Contact

gtgseq team

How to Cite

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

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Resources on AWS

  • Description
    Currently, the dataset contains two reference samples that will be useful for benchmarking and comparing bioinformatics tools for genome analysis. Raw signal data output by the sequencer is provided for these datasets in BLOW5 format. Basecalls are available in bgzip compressed FASTQ format. Alignments are available in BAM format. More information can be found at https://github.com/GenTechGp/gtgseq/blob/main/docs/data.md.
    Resource type
    S3 Bucket
    Amazon Resource Name (ARN)
    arn:aws:s3:::gtgseq
    AWS Region
    us-west-2
    AWS CLI Access (No AWS account required)
    aws s3 ls --no-sign-request s3://gtgseq/
    Explore
    Browse Bucket

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