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Latest version: v0.7.0

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0.6.0

- outbreaker now uses snipit to create a graphic of SNP diversity relative to the reference, and includes it in the summary report. This requires an environment upgrade to add snipit through pip
- The summary report can now handle the recognition of focal and background sequences when samples are renamed through --rename.
- Still requires teting to verify that --rename with --names_csv works in the same way as above


Minor Version 0.6.1, 02-12-21
- The output summary report is now an optional output to avoid rendering a large report by default with a
very large dataset. This can be enabled with --report. By default the report is not generated.


Minor Version 0.6.2, 07-12-21
- outbreaker -v or outbreaker --version will now show the current version, then exit.
- In the summary report, the trees are automatically scaled with xlim to ensure that the tree labels are always visible, no matter the length of the branch
- In the summary report, a treescale was added for the trees that renders in either the bottom right or top right, depending on where the longest branches are. This was done to avoid having the treescale overlapping a tip lab.


Minor Version 0.6.3, 10-12-21
- --names-csv is now compatible with the summary report
- --filter and --names-csv are now compatible. Previously,, if any sequences were filtered and a names CSV was supplied, there would be an error.
- The reference ncov sequence that is compatible with MAFFT (augur align) is now included under /data/reference/ as ncov_reference.gb

Minor Version 0.6.4, 17-02-22

- outbreaker now retains all sequences if --names-csv is used for renaming and not all sequences are contained in the CSV
- updates to the renaming behavior to be compatible with fastafurious v1.2.0 (additional warning messages)

Minor Version 0.6.5, 28-04-22 (Patch)
- Change behaviour of renaming when no CSV is supplied. Will now use the prefix for the run to generate new names with alphanumerical sequential order (i.e. prefix_1, prefix_2) and will output the name matches as a CSV file
- Above fix changes fixes the error in the SNP distance plot in the HTML report when rename is used but no names CSV is supplied
- Addition of pytests in the CI/CD workflow

Version 0.7.0, 15-06-22

- outbreaker is renamed to spora to be compatible with PyPi
- version change to dplyr dependency for conda env
- Addition of CD GA workflow to pudblish to PyPi on release

0.5.0

- outbreaker now creates an output summary report summarizing the number of input sequences, SNP distance patterns relative to the focal sequences inputs, as well as basic rendering of the phylogenetic trees. The report is flexible: it will modify the outputs accordingly if either background sequences are not supplied or SNPs only analysis is not conducted. requires a majoy environment upgrade, specifically with regards to R and Bioconductor dependencies through conda

0.4.0

- if a previous run of iqtree2 for the SNPs only tree is detected, the console will
allow the user to select how to proceed. Currently the only possible selection is to confirm
overwriting the existing SNPs only tree analysis, or outbreaker will exit. Requires a new environment
installation as the logic uses click through pip.

0.3.0

- focal and background sequences can now be supplied as either .txt list files
of sample names, or as FASTA files containing the actual sequences. outbreaker
will assess the file ending and evaluate whether to create subsets based on the
names (if .txt is passed) or use the FASTA given

0.2.0

- focal and background filtering step can now be used with --filter,
where the sequences can be filtered based on genome completeness and
genome length. The defaults are set to 90% genome completeness and
a genome length of 29500 for ncov

0.1.0

- Initial workflow
- Required inputs: focal sequence list (.txt), COVID-19 reference (.gb),
master fasta sequences from which to subset (.fa, .fasta)
- Optional features include output directory, prefix, SNPS only analysis,
ability to rename headers to custom or match NML specifications,
and toggling constant sites for SNPs only analysis

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