Genomeblocks

Fluent building blocks for regulatory genomics.

• Loci: craft and manipulate candidate regulatory element (CRE) sets with set algebra.
• Genes: parse GTF / UCSC RefSeq and annotate CREs with promoter-anchored gene models.
• Architecture: chromatin-contact graphs over CREs — build from BEDPE loops, overlay mcool matrices, normalize, annotate, find hubs.
• signal: threaded bigWig extraction, TMM normalization, comparative heatmaps.
• motifs: JASPAR motif scanning over a FASTA genome and enrichment.
• Atlas: GIGGLE-style enrichment of a region set against a ChIP-Atlas index.
• browser: IGV-like, fully-vectorial region viewer.

📖 Documentation: birkiy.github.io/genomeblocks — start with the AR & FOXA1 walkthrough.

Quick Start

from genomeblocks import Architecture, Genes, Loci

cre = (Loci.make("atac.narrowPeak")
           .slop(100)
           .sort()
           .merge())

se = cre.intersect(Loci.make("H3K27ac_SE.bed"))

arch = (Architecture.make(cre, "RNAP_loops.bedpe", r=2500)
                    .add_mcool(cre, "RNAP.mcool", resolution=5000)
                    .normalize(cre))

genes  = Genes.make("gencode.v38.annotation.gtf", promoter_r=1000)
counts = genes.annotations(se & cre).groupby("annotation").size()

Setup

conda env create -f environment.yml
conda activate genomeblocks
pip install -e .

For a pip-only install (no graph-tool → no Architecture):

pip install genomeblocks

See the documentation for installation details, a full quickstart, module guides, and an API reference.

License

MIT — see LICENSE.