Pyscenic

Updates:

* Add support for running arboreto_with_multiprocessing.py with spawn instead of fork as multiprocessing method.Pool
* Use ravel instead of flatten to avoid unnecessary memory copy in aucell
* Update Docker image file and add separated Docker file for pySCENIC with scanpy.

Updates:
- Only databases in Feather v2 format are supported now ([ctxcore](https://github.com/aertslab/ctxcore) >= 0.2), which allow uses recent versions of pyarrow (>=8.0.0) instead of very old ones (<0.17). Databases in the new format can be downloaded from https://resources.aertslab.org/cistarget/databases/ and end with *.genes_vs_motifs.rankings.feather or *.genes_vs_tracks.rankings.feather.
- Support clustered motif databases.
- Use custom multiprocessing instead of dask, by default.
- Docker image uses python 3.10 and contains only needed pySCENIC dependencies for CLI usage.
- Remove unneeded scripts and notebooks for unused/deprecated database formats.

Major changes:
* Split some core cisTarget functions out into a separate repository, [ctxcore](https://github.com/aertslab/ctxcore). This is now a required package for pySCENIC.
* Documentation updates

* Fix bug in motif url construction (275)
* Fix for export2loom with sparse dataframe (278)
* Fix sklearn t-SNE import (285)
* Updates to Docker image (expose port 8787 for Dask dashboard)

**Major features:**

* Updated [Arboreto](https://github.com/aertslab/arboreto) release (GRN inference step) includes:
* Support for sparse matrices (using the `--sparse` flag in `pyscenic grn`, or passing a sparse matrix to `grnboost2`/`genie3`).
* Fixes to avoid dask metadata mismatch error

* Updated cisTarget:
* Fix for metadata mismatch in ctx prune2df step
* Support for databases Apache Parquet format
* Faster loading from feather databases
* Bugfix: loading genes from a database (previously missing the last gene name in the database)

* Support for Anndata input and output

* Package updates:
* Upgrade to newer pandas version
* Upgrade to newer numba version
* Upgrade to newer versions of dask, distributed

* Input checks and more descriptive error messages.
* Check that regulons loaded are not empty.

* Bugfixes:
* In the regulons output from the cisTarget step, the gene weights were incorrectly assigned to their respective target genes (PR 254).
* Motif url construction fixed when running ctx without pruning
* Compression of intermediate files in the CLI steps
* Handle loom files with non-standard gene/cell attribute names
* Reformat the genesig gmt input/output
* Fix AUCell output to loom with non-standard loom attributes

Updates:
- Included new (optional) CLI option to add correlation information to the GRN adjacencies file. This can be called with `pyscenic add_cor`. (vib-singlecell-nf/vsn-pipelines/issues/254)
- The correlation calculation is subsequently skipped if using this adjacencies + correlations file as the input into `pyscenic ctx`.