multiSub | Can read GISAID | Genomics library

multiSub is a Python library typically used in Artificial Intelligence, Genomics applications. multiSub has no bugs, it has no vulnerabilities, it has a Strong Copyleft License and it has low support. However multiSub build file is not available. You can install using 'pip install multiSub' or download it from GitHub, PyPI.

multiSub accepts input sequences in fasta format and meta data in tsv, csv or GISAID (xls or csv) formats. It will make some effort to clean the input data, e.g. skip missing sequences, strip flanking Ns, or remove empty meta data and output warnings if that happens. It can then create one or multiple output files, in NCBI, NCBI-tag, NCBI-ftp, ENA-xml or GISAID-csv format and directly upload to NCBI, ENA or GISAID. The script takes care of the different ways to format the virus names (for example, hCov-19 for GISAID, SARS-CoV-2 for NCBI), translates the different ways to specify the country, checks the date format and adds sequence IDs where needed. It does not support more than the date and isolate and country fields, but other fields can be easily added, just email examples to maxh@ucsc.edu. There is really only a single table and a single fasta file needed. The different export steps will pick out of the meta data table what they need. E.g. the field "Genome Coverage" will be exported by the NCBI Genbank step into a "structured-comment" field "Genome Coverage", and will also end up in the ENA fields "coverage" and GISAID's "covv_coverage". The meta table field names should either follow NCBI standards or be a GISAID file. As a matter of fact, there is an order to the steps: you first need to upload to NCBI Biosamples to obtain Biosamples accessions, then you re-convert to add these IDs to the files, then you can upload the new files to Genbank or SRA, with the Biosamples accessions in them. The examples below should make this clear. Many thanks to Stephan Fuchs and Kyanoush Yahosseini, Robert Koch Institut, Berlin, for sending me their Python ENA uploader code, from which I copied. Also thanks to the ENA Helpdesk and the NCBI Helpdesk for their quick replies. Also to Kelsey Florek and Ethan Wang for bug reports. The NCBI bulk upload draws heavily from examples provided by Danny Park at the Broad Institute. Without all of these people, this program would not have been possible.