Vision — Epigenetic CRISPR Pipeline | Epigenetic CRISPR Pipeline - Dataspheres AI

Autonomous De Novo Epigenetic CRISPR-Targeting PipelineInitiative: crispr-pipeline | Published: 2026-05-20T17:04:29ZWhat We Are BuildingA three-tier autono...

Autonomous De Novo Epigenetic CRISPR-Targeting Pipeline Initiative: crispr-pipeline | Published: 2026-05-20T17:04:29Z What We Are Building A three-tier autonomous pipeline: FastQ input → sgRNA candidates, fully automated once external dependencies are resolved. Three-Tier Architecture Tier 1 (Multi-omics Ingestion): BWA-meth bisulfite alignment, GATK4 HaplotypeCaller variant calling, MethylDackel CpG extraction. FastQ parser is operational. Alignment and calling are BLOCKED pending tool installation. Tier 2 (CRISPR Target Search): Fully operational. Aho-Corasick PAM site scanner, Doench Rule Set 2 sgRNA scorer, genetic algorithm optimizer. Outputs tier2_candidates.json. Tier 3 (3D Structural Validation): PDB loader operational. FoldX/PyRosetta BLOCKED pending academic license. Self-correction loop BLOCKED on energy calculator. Golden Dataset Validation Tier 1: GIAB NA12878 NISTv4.2.1 — SNP F1 threshold 0.95, Indel F1 threshold 0.90 Tier 2: bioTaskBench CRISPR gold standard — Jaccard threshold 0.90 Tier 3: RCSB Cas9 alanine scan — Pearson r threshold 0.95 vs experimental ΔΔG No Mocks Rule Zero-tolerance on mock implementations. Missing dependencies cause BLOCKED status with explicit resolution paths. No silent fallbacks. No synthetic substitutes. Blocked Dependencies BWA-meth (Tier 1): conda install -c bioconda bwameth GATK4 (Tier 1): github.com/broadinstitute/gatk/releases (Java 17+) MethylDackel (Tier 1): conda install -c bioconda methyldackel FoldX (Tier 3): academic license at foldxsuite.crg.eu PyRosetta (Tier 3): license at els2.comotion.uw.edu hap.py (Validation): conda install -c bioconda hap.py (Linux/WSL2 only) Industry Benchmark Context Frontier models score 0-5% on BioAgent Bench elite agentic bioinformatics tasks. This SDD workflow stress-tests whether structured spec management gives measurable gains on complex multi-tier AI state management.