v1.2.0

• The viral database compression feature is added to fetch module. It is highly recommended as after the (COVID-19) pandemic the viral database grew dramatically and made some downstream analysis computationally expensive.
• The bacterial database is divided in more chucks in order to make sure that the indexing and downstream analysis are done without any problem.
• Accession numbers are added orgs_list.tsv table.

Bugfix version: 1.1.1

A couple of issues were solved in this version

• a bug that failed to create output directory when wolfpack was run on a single file with slashes in the path (i.e., nearly always),
• a bug in tidytable prevented to run if the directory was given with a trailing slash,
• order (a method in pandas now deprecated) has been replaced with sort_values.

Make some tidy tables

This version adds a subcommand implementing a simple feature: creation of two tables obtained by merging stats.tsv and orgs_list.tsv. Useful to plot summaries for the whole run.

VirMet 1.0: production ready, more user friendly

VirMet is now a full fledged python pipeline for viral metagenomics, relying on
some state-of-the-art external tools called via shell for specific
computationally intensive tasks.

It features subcommands to download, update, and index reference databases.
After these preliminary operations matching against viral database for a whole
Illumina MiSeq run is performed in a single call.
Coverage plots for specific viruses can be drawn to support or exclude their
presence.

More information are available on the documentation page.

First release candidate

Old version of VirMet (v0.3.3) is being used regularly at our institute, but it relies on locally installed resources that were not documented at all.

In the new version the fundamental concepts have not changed, but the program has been entirely rewritten to be an almost pure python application, though relying on external tools called via shell.