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

{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()

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'