Releases: aertslab/CREsted
Releases · aertslab/CREsted
1.3.0
1.3.0
This is a big release wherein we introduce our model repository and do a functional refactoring of our tl.Crested
class.
Features
- new
crested.get_model
function to fetch models from crested model repository - new
enformer
andborzoi
model options in the crested zoo, as well as scripts for converting weights to keras format. - new cut site bigwigs option for mouse cortex dataset
- new crested model repository in the readthedocs with model descriptions.
- new pattern clustering plot
pl.patterns.clustermap_with_pwm_logos
that shows PWM logo plots below the heatmap. - Extra parameters options in modisco calculations and plotting regarding allowed seqlets per cluster and top_n_regions selection.
- option to color lines in gene locus scoring plotting
- extra ylim option in
crested.pl.bar.prediction
- gene locus scoring plotting improvements
Bugfixes
- importing bigwigs now correctly accounts for regions that were removed due to chromsizes
Notebooks
- Rewrote the tutorials to use the new functional API (WIP).
- Expanded on the enhancer design section
Functional Refactor of crested.tl.Crested(...) class
In this large refactor we're moving everything from the Crested class that does not use both a model and the AnnDatamodule out to a new _tools.py module where everything will be functional.
All the old functions remain in the Crested class for backward compatibility (for now) but will now raise a deprecation warning.
We're giving up a bit of clarity for ease of use by combining functions that do the same on different inputs into one single function.
Equivalent new functions
tl.Crested.get_embeddings(...)
--->tl.extract_layer_embeddings(...)
tl.Crested.predict(...)
--->tl.predict(...)
tl.Crested.predict_regions(...)
--->tl.predict(...)
tl.Crested.predict_sequence(...)
--->tl.predict(...)
tl.Crested.score_gene_locus(...)
--->tl.score_gene_locus(...)
tl.Crested.calculate_contribution_scores(...)
--->tl.contribution_scores(...)
tl.Crested.calculate_contribution_scores_regions(...)
--->tl.contribution_scores(...)
tl.Crested.calculate_contribution_scores_sequence(...)
--->tl.contribution_scores(...)
tl.Crested.calculate_contribution_scores_enhancer_design(...)
--->tl.contribution_scores(...)
tl.Crested.tfmodisco_calculate_and_save_contribution_scores_sequences
--->tl.contribution_scores_specific(...)
tl.Crested.tfmodisco_calculate_and_save_contribution_scores
--->tl.contribution_scores(...)
tl.Crested.enhancer_design_motif_implementation
--->tl.enhancer_design_motif_insertion
tl.Crested.enhancer_design_in_silico_evolution
--->tl.enhancer_design_in_silico_evolution
New functions
Some utility functions were hidden inside the Crested class but required to be made explicit.
utils.calculate_nucleotide_distribution
(advised for enhancer design)utils.derive_intermediate_sequences
(required for inspecting intermediate results from enhancer design)
New behaviour
- All functions that accept a model can now also accept lists of models, in which case the results will be averaged across models.
- All functions use a similar api, namely they expect some 'input' that can be converted to a one hot encoding (sequences, region names, anndatas with region names), but now the conversion happens behind the scenes so the user doesn't have to worry about this and we don't have a separate function per input format.
1.2.1
1.2.1
Bug Fixes
- Fixed an issue where {func}
crested.pp.change_regions_width
would not actually check for the chromsizes if a Genome was registered.
1.2.0
1.2.0
Features
- {func}
crested.import_bigwigs
now allows BED files with entries for chromsomes which are not in the BigWig. - Better handling of bigwigs track in the backend and new bigwig track reading function {func}
crested.utils.read_bigwig_region
- Overall support for stranded datasets while preserving support for non stranded datasets.
- DVC logging now available with tf backend
- New option to choose the starting sequences for motif implementation and ISE in enhancer design.
- {func}
crested.tl.Crested.score_gene_locus
now accepts an optional genome as input. - output_activation now parameter for all models in zoo.
- {func}
crested.utils.reverse_complement
and {func}crested.utils.fetch_sequences
now available. - Spearman correlation metric implementation
- Pattern plotting QOL updates
- poisson losses implemented at {class}
crested.tl.losses.PoissonLoss
and {class}crested.tl.losses.PoissonMultinomialLoss
- {class}
crested.Genome
and {func}crested.register_genome
for better handling of genome files. - MSECosine loss now uses a multiplier parameter instead of standard multiplication
Tutorials
- Introductory notebook now fully reproducible
Bug Fixes
- {func}
crested.tl.Crested.get_embeddings
now correcly updates .varm if anndata is passed instead of .obsm. - Tangermeme moved out of optional dependencies for tf vs torch breaking mismatches.
- Fixed calculation of contribution scores with torch backend when using incompatible numpy version.
- Fix incorrect None return in
Crested.test()
Breaking Changes
- If providing the same project_name and run_name, the Crested class will now assume that you want to continue training from existing checkpoints.
- 'genome_file' argument name everywhere updated to 'genome'
1.1.0
1.1.0
Features
- enhancer design plotting and calculation functions in the
crested.tl.Crested
object - new module
crested.tl.modisco
with enhancer code analysis functionality - new plots for enhancer code analysis in
crested.pl.patterns
- new plot for sequence prediction in
crested.pl.bar
- hidden utility functions now public in
crested.utils
(such as one hot encoding) - CosineMSELog loss now default in peak_regression configs instead of CosineMSE
- tangermeme tomtom option in tfmodisco functions
- get_embeddings based on layer name in
crested.tl.Crested
crested.utils.EnhancerOptimizer
utility functioncrested.utils.permute_model
utility, useful for using with other toch packagescrested.utils.extract_bigwig_values_per_bp
utility- improved correlation calculation speed in heatmaps
Tutorials
- introductory notebook is updated with new functionality
- new enhancer code analysis tutorial
Bug Fixes
- transfer Learning function now doesn't expect the dense block anymore
- bigwigs importing checks if it can open the file instead of looking for .bw extension
- no more ambiguous names in bed importing
- version requirement for modiscolite
- general pattern matching code bugfixes
Breaking Changes
- utility functions and logging moved to
crested.utils
- tfmodisco functionality moved to
crested.tl.modisco
Other
- general documentation fixes
- style checks now enforced on push
- both tf and torch backend tests on push
1.0.0
Initial release