Release Notes#

1.2.1#

Fixed an issue where crested.pp.change_regions_width() would not actually check for the chromsizes if a Genome was registered.

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 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.
crested.tl.Crested.score_gene_locus() now accepts an optional genome as input.
output_activation now parameter for all models in zoo.
crested.utils.reverse_complement() and crested.utils.fetch_sequences() now available.
Spearman correlation metric implementation
Pattern plotting QOL updates
poisson losses implemented at crested.tl.losses.PoissonLoss and crested.tl.losses.PoissonMultinomialLoss
crested.Genome and crested.register_genome() for better handling of genome files.
MSECosine loss now uses a multiplier parameter instead of standard multiplication

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()

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’

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 function
crested.utils.permute_model utility, useful for using with other toch packages
crested.utils.extract_bigwig_values_per_bp utility
improved correlation calculation speed in heatmaps

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