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Marit Hetland edited this page Feb 17, 2021 · 14 revisions

susCovONT

Pipeline to generate consensus.fasta files and identify pangolin lineage and nextstrain clade of Sars-CoV-2 genomes from ONT sequencing.

This pipeline takes as input a folder with name <run_name> which contains the folders fast5_pass and fastq_pass from Sars-CoV-2 ONT sequencing together with a CSV-file which links barcode and sample name, and it outputs consensus.fasta files along with <run_name>_report.csv which includes pangolin lineage, nextstrain clade, mutations and QC.

Quick start

python susCovONT --input_dir /path/to/<run_name> --sample_names sample_names.csv

Where:

  • --input_dir: Input directory <run_name> must contain fast5_pass and fastq_pass folders, with the <run_name> corresponding to your run (e.g. 20210213_1359_X5_FAO88697_5cf6e6f0)
  • --sample_names: A CSV-file which connects barcodes with sample names, following the format:
barcode,sample_name
NB01,NEGCONTROL
NB02,E1234567_P1
NB03,V2345678_P1

Note: Basecalling and demultiplexing may also be performed if not already done on GridION/MinIT.

Please see the wiki for more information:

And as an extra bonus:

Note and thanks

Please note that this script was created for use at Stavanger University Hospital, you may need to change it (sprecifically the scripts/config.cfg file) for it to work in your environment.

This pipeline uses tools from the [Artic network's nCoV-2019 novel coronavirus bioinformatics protocol] (https://artic.network/ncov-2019/ncov2019-bioinformatics-sop.html). See also the QC and parameters page and further links here.

Many thanks to the artic, pangolin and nextclade developers for creating the protocols and pipelines!

Repo name

This pipeline was created for the analysis of Sars-CoV-2 data from Oxford Nanopore Technologies (ONT) sequencing at Stavanger University Hospital (SUH/SUS). Hence the name, susCovONT: SUS + Covid-19 + ONT.

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