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Releases: EI-CoreBioinformatics/mikado

v2.3.4

09 Jun 23:01
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Fix #426: Allow codon usage in Mikado prepare (#433)
Fix #431: Pin marshmallow dependency versions (#433)

Full Changelog: v.2.3.3...v2.3.4

Version 2.3.3

12 Nov 14:55
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Bug fix release

Fixes an issue when all inputs are tagged reference and padding is activated.

Fixes #422

What's Changed

Full Changelog: v2.3.2...v.2.3.3

Version 2.3.2

03 Sep 11:40
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Fix issue processing empty blast tsv files.

Version 2.3.1

20 Aug 13:29
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This release improves the performance of Mikado for dense loci when processing long read data. Also, makes Mikado compatible with SQLAlchemy 1.4.0.

Bugs fixed:

Version 2.3.0

25 May 10:16
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Version 2.3.0

Fix #404: Error in extract_promoter_regions.py helper script

Fix #405: Error in remove_utrs.py helper script

Also fixes a name clashing issue in daijin's configuration object and other small bugs

Version 2.2.5

12 Apr 14:58
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Fix for class2 in daijin pipeline

Fix #401: Cannot run Class2 in Daijin pipeline

v2.2.4

06 Apr 18:00
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Fix the Github Action tests, moving to use only Python 3.7+ (due to AsyncIO), and updated the documentation.

Fix #385: clarified and corrected the tutorial for Daijin.
Fix #389: Mikado now can theoretically output BED12 files from Mikado prepare. This is still
Fix #395: corrected an issue in mikado prepare that left models with incorrect proteins in the input annotations. This caused mikado pick to crash during the padding procedure.
Fix #396: corrected and clarified the errors related to missing configuration files (e.g. incorrect scoring files being provided).
Fix #397: corrected a small bug in mikado prepare, when providing the input files through the CLI rather than through the configuration file.

v2.2.3: OSX

24 Mar 19:00
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Testing Mikado also on OSX, and adding OSX to the supported OSes in Conda.

Fix #392: Mikado was having trouble with pipes in the sequence IDs (either present in the first place or added by NCBI+ when using makeblastdb -parse_seqids).

Version 2.2.2

19 Mar 17:55
40f887b
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Using TMPDIR by default when creating/reading sqlite databases, this is faster than running directly on NFS
Added an option to use /dev/shm for mikado serialise and compare

SQLA patch

17 Mar 11:12
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Pinning sqlalchemy to <1.4.0 until sqlalchemy_utils is updated (see #388).

Moreover, solved a small bug in prepare: setting prepare.exclude_redundant to True in the configuration file had no effect. Now it is equivalent to use the -er switch on the CLI (h/t @swarbred).