Release Notes¶

0.12.1 | 2022-11-21¶

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.

Only databases in Feather v2 format are supported now (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.

Split some core cisTarget functions out into a separate repository, ctxcore. This is now a required package for pySCENIC.

Major features:

Updated 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

Included new CLI option to add correlation information to the GRN adjacencies file. This can be called with pyscenic add_cor.

Integrate arboreto multiprocessing script into pySCENIC CLI
Skip modules with zero db overlap in cisTarget step
Additional error message if regulons file is empty
Additional error if there is a mismatch between the genes present in the GRN and the expression matrix
Fixed bug in motif url construction when running without pruning

CLI: file compression (optionally) enabled for intermediate files for the major steps: grn (adjacencies matrix), ctx (regulons), and aucell (auc matrix). Compression is used when the file name argument has a .gz ending.

Integrate arboreto multiprocessing script into pySCENIC CLI
Skip modules with zero db overlap in cisTarget step
Additional error message if regulons file is empty
Additional error if there is a mismatch between the genes present in the GRN and the expression matrix
Fixed bug in motif url construciton when running without pruning

CLI: file compression (optionally) enabled for intermediate files for the major steps: grn (adjacencies matrix), ctx (regulons), and aucell (auc matrix). Compression is used when the file name argument has a .gz ending.

Added a helper script arboreto_with_multiprocessing.py that runs the Arboreto GRN algorithms (GRNBoost2, GENIE3) without Dask for compatibility.
Ability to set a fixed seed in both the AUCell step and in the calculation of regulon thresholds (CLI parameter --seed; aucell function parameter seed).
(since 0.9.18) In the modules_from_adjacencies function, the default value of rho_mask_dropouts is changed to False. This now matches the behavior of the R version of SCENIC. The cli version has an additional option to turn dropout masking back on (--mask_dropouts).