Installation and quick start

Install the package

pip install sjcab_peak2anno_db
conda install stjudecab::sjcab_peak2anno_db

Install the default resource bundle:

sjcab-peak2anno-db install
sjcab-peak2anno-db install def
sjcab-peak2anno-db install default

Install selected components:

sjcab-peak2anno-db install genebed feature blacklists cgi
sjcab-peak2anno-db install -c genebed -c feature

The supported install components are genebed, feature, blacklists, and cgi. The three commands above install the complete default bundle. list shows the bundled registry, while path prints a resource path.

Download/install supported species/versions

sjcab-peak2anno-db download-genebed hg38 v31 -o annotations
sjcab-peak2anno-db download-feature mm10 vM22 -o annotations
sjcab-peak2anno-db install-feature cat def
sjcab-peak2anno-db install-feature dog 115
sjcab-peak2anno-db install-feature vicpac2

Use -j/--processes to process independent GTFs in parallel. GTF downloads are sequential with a short randomized pause, and conversion within each worker is single-process. The worker count is capped at the CPUs allocated to the job:

sjcab-peak2anno-db download-feature cat,dog,horse -j 3

dedup-genebed and filter-genebed support -n/--workers (default 2) to write their independent TSS and TES outputs in parallel.

Python API

import sjcab_peak2anno_db as db

db.install_data()
db.download_and_convert_gencode_gtf("hg38", "v31", output_dir="annotations")
db.download_feature("hg38", "v31", "annotations")

Data lookup and cache behavior

Downloads first search the database {db-path}/cache, then the output directory, then the current working directory. Download URLs are recorded in {db-path}/download_urls.log. Match of gtf file name and species/version listed in {db-path}/installed.tsv. GENCODE, UCSC, and Ensembl resolution details are documented in the GeneBEDs guide.