Data analysis

DateVersion numberLanguageDeviceChanges
Aug 22 2024DATD_5000_v1_revT_22Aug2016English
22nd August 2024 - "Basecalling algorithms": the basecaller speed benchmarking table has been corrected.
July 31st, 2024DATD_5000_v1_revR_22Aug2016English Download 9th August 2023 - "Basecalling overview" - references to Guppy have been removed; added a description of the Dorado basecall server. - "Basecalling algorithms" - the basecaller speed benchmarking table has been updated. - "Barcoding options" - references to Guppy have been removed; information in "The regions of a barcode" has been updated to include the latest sequencing kits.
June 20th, 2023DATD_5000_v1_revQ_22Aug2016English Download 20th June 2023 The document has been updated with: - Information included about the Dorado basecaller - Guppy basecalling software has been changed to Legacy - Basecalling models and their relative speed - New information and recommendations for modified base calling - Information about file formats has been updated to inlude POD5 output - Information about EPI2ME has been updated
September 12th, 2022DATD_5000_v1_revP_22Aug2016English Download 12th September 2022 "Basecalling algorithms" - minor changes to information about the basecalling models available in Guppy.
June 23rd, 2021DATD_5000_v1_revO_22Aug2016English Download 23rd June 2021 - In "Basecalling algorithms", information about the updated Fast, High Accuracy and the new Super Accurate (sup) basecalling models has been updated. Additionally, there are new benchmarks for basecalling speed and accuracy for these models. There is also an update to the modified base calling models (now available only for 5mC in MinKNOW and Guppy, while models for other base modifications are available from our research tools on GitHub). - In "Live basecalling", there is an update to the 'keep-up' vs 'catch-up' benchmarks for basecalling models on the different sequencing devices. - In "Basecall accuracy", the details about raw read/consensus sequencing accuracy have been removed; this information is now linked out in https://nanoporetech.com/accuracy. - In "Barcoding options", information about the EPI2ME barcode demultiplexing algorithm has been removed, since this will soon be updated to the same algorithm used by Guppy. - In "Read .fast5 files from the instrument" and "Basecalled .fast5 files", the schema for the file structure has been updated. Information about single-read .fast5 files has been removed, as these files are no longer supported. - In "FASTQ and BAM files", new information is included about the content of FASTQ files, as well as BAM file output during alignment experiments. - In "Oxford Nanopore Technologies tools and pipelines", a section has been added to describe the workflows and tutorials available in EPI2ME Labs.
February 21st, 2020DATD_5000_v1_revN_22Aug2016English Download 21st February 2020 Updates to basecalling overview and algorithms: - Updated basecall speeds - New section on basecalling model training - Description of latest Research basecallers
December 24th, 2019DATD_5000_v1_revM_22Aug2016English Download 11th October 2019 - Expanded information on barcode demultiplexing algorithms - Added information about calling modified bases
July 19th, 2019DATD_5000_v1_revL_22Aug2016English Download Updates, including: - Expanded information on basecalling algorithms - Added information about sequencing accuracy - Added information about barcoding options, and modified base detection
May 21st, 2019DATD_5000_v1_revK_22Aug2016English Download Updates, including: - Description of the Flip-Flop basecaller - Update to the .fast5 file structure, including multi-read .fast5 files - Updates to post-basecalling data analysis options, including third-party tools and Bioinformatics tutorials
June 8th, 2018DATD_5000_v1_revJ_22Aug2016English Download Updates corresponding to the latest MinKNOW release, and up-to-date information on basecalling options.
May 19th, 2018DATD_5000_v1_revI_22Aug2016English Download Removed information about the Nanonet basecaller, which is no longer supported by Oxford Nanopore Technologies.