Releases | Open Source Science

https://github.com/aureme/esmecata - esmecata 0.6.5

Fix

Issue with cellular root in esmecata_compression.py.

Modify

Complete the move to ete4.
Move test data files.

- Python
Published by ArnaudBelcour about 1 year ago

https://github.com/aureme/esmecata - esmecata 0.6.4

Add

Function get_domain_or_superkingdom_from_ncbi_tax_database in esmecata.utils to check if domain is called domain or superkingdom in NCBI Taxonomy database.

Fix

Taxonomic rank superkingdom has been renamed to domain in recent version of the NCBI Taxonomy database. Fix several related issues in different parts of EsMeCaTa.
esmecata_gseapy was not working with results from esmecata precomputed due to missing proteome_tax_id.tsv in 2_annotation folder.

- Python
Published by ArnaudBelcour about 1 year ago

https://github.com/aureme/esmecata - esmecata 0.6.3

Fix

KeyError when using precomputed database from EsMeCaTa article (as there is no KEGG_reaction in these databases).

- Python
Published by ArnaudBelcour about 1 year ago

https://github.com/aureme/esmecata - esmecata 0.6.2

Modify

Replace datapane by arakawa for HTML report creation in esmecata_report (issue #20). Make HTMLs standalone (they are a lot bigger but bo not require internet to display).
Replace ete3 by ete4 as ete3 is no longer maintained (issue #18).

- Python
Published by ArnaudBelcour about 1 year ago

https://github.com/aureme/esmecata - esmecata 0.6.1

Fix

Issue with tax synonyms on the same tax rank when filtering rank in proteomes.

Modify

Use taxon ID to search for taxon presence in precomputed database.
Use Trusted publisher to publish on PyPI.

- Python
Published by ArnaudBelcour about 1 year ago

https://github.com/aureme/esmecata - esmecata 0.6.0

Add

New command esmecata_create_db to create database from different output folders of esmecata (from_runs).
Full release of esmecata precomputed associated with the first version of esmecata precomputed database.
Option threshold (-t) to precomputed.
Add --gseapyCutOff option to gseapy_enrichr.
A check after database creation to detect taxon with few predicted proteins compared to higher affiliated taxon.
Check the good format of the gzip file.
Header KEGG_reaction in annotationreference from `annotationuniprotto avoid issues withesmecatacreatedb`.

Fix

Issue with protein IDs from UniParc during annotation (incorrect split on '|').
Fix issue in get_taxon_obs_name function.
Issues in test.

Modify

Add database version in log.
Rename test_workflow.py into test_workflow_uniprot.py, to better reflect what is done.
Update workflow figure.
Update readme.
Update article_data folder and the associated readme.

- Python
Published by ArnaudBelcour over 1 year ago

https://github.com/aureme/esmecata - esmecata 0.5.4

Fix

Issue with proteomes from UniParc during clustering (incorrect split on '|').
Issue in test with updated taxonomic group.

- Python
Published by ArnaudBelcour over 1 year ago

https://github.com/aureme/esmecata - esmecata 0.5.3

Fix

Handle an issue with requests.exceptions.ChunkedEncodingError.

Modify

Remove unused header in output file of gseapy.

- Python
Published by ArnaudBelcour over 1 year ago

https://github.com/aureme/esmecata - esmecata 0.5.2

Add

New way to search proteomes by using UniParc. Some proteomes, when downloaded directly from UniProt are empty. A solution is to search for them in UniParc and retrieved the associated protein sequences.
New plot in report showing proteomes according to tax_rank.
Database number version when creating precomputed database.
The possibility to give a file containing manually selected groups of observation names for esmecata_gseapy gseapy_enrichr.
Tests for esmecata_gseapy gseapy_enrichr.

Fix

Issue in creating heatmap of proteomes (missing taxon rank) in report creation.
Issue when creating database: there was a possibility that a taxon without consensus proteomes and associated annotations was kept.

Modify

Update parameter description for SPARQL option to indicate the value to query SPARQL UniProt Endpoint.
Rename esmecata_gseapy gseapy_taxon into esmecata_gseapy gseapy_enrichr to reflect the changes in the command.
Modify how esmecata_gseapy gseapy_enrichr works by adding a grouping parameters allowing to choose either groups according to taxon_rank or with a file created by the user and containing manually selected groups of observation names.
Update readme according to the different changes made in this release.

TODO

Investigate and solve memory leak when mapping UniParc IDs to UniProt with bioservices.
Add handling of UniParc IDs with SPARQL queries.

- Python
Published by ArnaudBelcour over 1 year ago

https://github.com/aureme/esmecata - esmecata 0.5.1

Add

Metadata file for esmecata_gseapy gseapy_taxon.

Fix

Several issues in esmecata_gseapy gseapy_taxon.
Issues in tests due to UniProt updates.

Modify

Update metadata files for annotation and eggnog by adding missing dependencies.

- Python
Published by ArnaudBelcour over 1 year ago

https://github.com/aureme/esmecata - esmecata 0.5.0

WARNING: Changes in the structure of the python package of EsMeCaTa. If you have been importing the package in Python, you will need to modify your import.

Add

New command esmecata_report to create a report from the output folder of EsMeCaTa. Scripts of esmecata_report allow to create html, pdf and tsv reports from EsMeCaTa (work of @alimatai and @PaulineGHG). This command has several subcommands:
- (1) create_report to create a report from the output folder of the esmecata workflow subcommand (only way to have the complete HTML report).
- (2) create_report_proteomes to create report files from output of esmecata proteomes subcommand.
- (3) create_report_clustering to create report files from output of esmecata clustering subcommand.
- (4) create_report_annotation to create report files from output of esmecata annotation subcommand.
New command esmecata_gseapy to create enrichment analysis of functions predicted by EsMeCaTa according to taxon rank.
New optional dependencies required for esmecata_report: datapane, plotly, kaleido, ontosunburst. As datapane is no more maintained, an alternative with panel is currently developed.
New optional dependencies required for esmecata_gseapy: gseapy and orsum.
New file indicating the EC numbers and GO Terms for the different observation name of the dataset (file function_table.tsv).
New subcommand esmecata precomputed. This subcommand uses a precomputed database to make predictions from the input file (using EsMeCaTa default parameters). It has been added to avoid creating the same prediction every run and to have a fast way to make predictions with EsMeCaTa. It is necessary to download the precompiled database before using it. At the moment of this release, the database is not available, these scripts are present for testing purposes.
Prototype for precomputed database creation: several scripts are added in esmecata/precomputed folder to create the input and the precomputed database.
Check that the proteome files are not completely empty, which could cause problems with mmseqs2.
Tests for precomputed database, report creation, database creation and eggnog annotation. Add mock on sevral functions to perform the test. Required pytest-mock.
Add readme in test folder.

Fix

Issue in proteomes SPARQL query (missing PREFIX).

Modify

Modification of the structure of the EsMeCaTa package, now divided into 4 main folders: (1) esmecata/core (for the script previously contained in the EsMeCaTa folder) and used for the workflow, (2) esmecata/report to generate a report from the esmecata output folder, (3) esmecata/gseapy to perform enrichment analysis on the esmecata output, and (4) esmecata/precomputed to create precomputed database (in development).
Change the name of intermediary files in clustering and annotation to avoid issues with ambiguous taxon names.
Modify test according to changes of packaging structure.
Modify the behaviour of annotation by eggnog-mapper. Now it merges protein sequences from clustering into bigger files (associated with superkingdom). This increases the performance of eggnog-mapper. Modification made with @megyl. Use --tax_scope with eggnog-mapper.
Update article_data folder.
Update CI tests of github workflow according to the new tests and the new dependencies.

Remove

Remove esmecata analysis subcommand as it was not used and not very useful.

- Python
Published by ArnaudBelcour over 1 year ago

https://github.com/aureme/esmecata - esmecata 0.4.2

Fix

Issue in pyproject.toml and how the package is installed with pip.

- Python
Published by ArnaudBelcour over 2 years ago

https://github.com/aureme/esmecata - esmecata 0.4.1

Fix

Some issues on the PyPI page of the package (due to change from setup.py to pyproject.toml).

- Python
Published by ArnaudBelcour over 2 years ago

https://github.com/aureme/esmecata - esmecata 0.4.0

WARNING: * change in intermediary files of clustering and annotation in order to reduce disk space used by EsMeCaTa and the number of operations performed by the methods. Instead of assigning one file per observation name, this new version assigns one file per taxon used by EsMeCaTa. This removes a lot of redundant work that slowed EsMeCaTa and could lead to issue. * annotation with eggnog-mapper is now the default workflow methods of EsMeCaTa. The previous annotation methods with UniProt has been moved to annotation_uniprot and workflow_uniprot.

Add

Add sub-commands annotation_uniprot and workflow_uniprot to use the old method of protein annotation.
Add check subcommand that performs the first step of EsMeCaTa without downloading the proteomes. This is helpful when you want to have a glimpse on the available knowledge for your dataset.
Error message if incorrect extension is given as input to esmecata.

Fix

Missing import in proteomes.
Github Actions.

Modify

Modify intermediary files to associate them with taxon name selected by EsMeCaTa instead of the observation name (based on an idea of @PaulineGHG). This change replaces tsv files, that were created for each observation names. Now they will be created for each taxon instead. This means that observation names with the same taxon will be associated with the same file. This reduces the redundancy of the file and decreases the number of operations made by EsMeCaTa.
Modify how the log json files are created so if a run failed, a new log json file is created instead of erasing the previous ones.
Move from setup.py and setup.cfg to pyproject.toml.
Update readme and tutorial.
Update license year.

Remove

Remove sub-commands annotation_eggnog and workflow_eggnog which are now the default sub-commands annotation and workflow.

- Python
Published by ArnaudBelcour over 2 years ago

https://github.com/aureme/esmecata - esmecata 0.3.0

Add a new way to annotate protein clusters using eggnog-mapper. From test on metagenomcis data, it is more accurate than the methods with UniProt. Also modify the default option of EsMeCaTa for option with better results on tested data (minimal number of proteomes from 1 to 5 and clustering threshold from 0.95 to 0.5).

Add

Add a new method to annotate protein clusters using eggnog-mapper: new script eggnog.py, new commands annotation_eggnog and workflow_eggnog.
Add option to query uniprot dat files during annotation (--annotation-files, needs biopython>=1.81).
Add an option to use bioservices for annotation queries (--bioservices, requires bioservices>=1.11.2).
Add more tests for proteomes selection.
Add an option to update taxonomic affiliations (--update-affiliations).
Show the failedIDs during mapping for annotation.
Add an option to specify eggnog-mapper tmp fodler (--eggnog-tmp). By default, it is in esmecata output folder.
Add KEGG reaction in annotation_reference file when using eggnog-mapper.
Add a function to compare Input taxa information to esmecata taxa information (taxa name, taxa ID, taxa rank) + precise OTUs associated. Thanks to @PaulineGHG.

Fix

Do not use already annotated proteins when using annotation files.
Fix issue in esmecata proteomes, not using non-reference proteome.
Fix issue with missing reference proteome when parsing SPARQL results.
Fix issue in main with cli.
Fix an issue with minimal-nb-proteomes and non-reference proteomes.

Modify

Modify default options to --minimal-nb-proteomes of 5 (from 1 in previous version) and -t (clustering threshold from 0.95 to 0.5).
Modify rank_limit option to make it more understandable. Only taxon ranks inferior or equal to the one given will be kept.
Remove several output folders (proteomes result, clustering fasta_consensus and clustering fasta_representative) to reduce size of EsMeCaTa results.
Rename tmp_proteome into proteomes.
Remove FROM in SPARQL queries to speed up the queries (could speed up SPARQL queries).
Change header for annotation files, especially: 'gos', 'ecs', 'interpros', 'rhea_ids' into 'GO', 'EC', 'InterPro', 'Rhea'.
Add column cluster_members in annotation reference file and renamed column protein into protein_cluster.
Do not create fasta file when there are no protein clusters.
Update license year.
Update esmecata worfklow picture.
Update the doc of esmecata.

- Python
Published by ArnaudBelcour over 2 years ago