Changelog#
Version 1.0.0 (December 2025)#
Spatial Coherence Paradigm - Major Methodology Shift
This release represents a fundamental paradigm shift based on experimental validation:
E200-E211 showed guide-sequence coherence DOES NOT WORK (r ≈ 0)
Computing coherence from guide sequences (GC content, thermodynamic properties, structural features) has no predictive value for experimental outcomes. This approach has been deprecated in v1.0.0.
E213-E216 validated SPATIAL coherence DOES WORK
Measuring spatial coherence of response landscapes predicts perturbation reliability:
Correlation: r = -0.24 to -0.50 with outcome variance
Variance reduction: 32-49% when selecting from stable regions
Validation scale: 115,251 sgRNAs across 6 genes
The key insight: “The guide is the probe, not the structure.” IR coherence measures the SYSTEM’S response consistency, not properties of the perturbation itself.
New Modules
phaselab.landscapes - Core perturbation-response data structures
ResponseLandscape- Generic position → response mappingCoherenceProfile- Per-position coherence values with validationStabilityClass- STABLE, MIXED, AMPLIFYING, IRRELEVANTclassify_regions()- Region classification algorithm
phaselab.spatial - E213-validated tiling screen analysis
analyze_tiling_coherence()- Full coherence analysis pipelineload_tiling_screen()- Data loading utilitiesTilingResult- Structured result with stable/amplifying regions
phaselab.surf - CRISPR-SURF integration
parse_surf_output()- Parse SURF deconvolution outputcompute_surf_coherence()- Coherence on deconvolved dataSURFPipeline- End-to-end SURF + coherence pipelinecompare_raw_vs_surf()- Raw vs deconvolved comparison
phaselab.omics - Genomics assay coherence
analyze_atac_coherence()- ATAC-seq stable accessibilityanalyze_chip_coherence()- ChIP-seq stable bindinganalyze_expression_coherence()- RNA-seq reliable changes
phaselab.microbio - Microbial screen analysis
analyze_tnseq_coherence()- TnSeq essential domainsanalyze_crispri_coherence()- Bacterial CRISPRi screensanalyze_drug_coherence()- Drug dose-response stability
phaselab.chem - Chemical/biochemical systems
analyze_binding_coherence()- Stable binding hot spotsanalyze_reaction_coherence()- Stable reaction conditionsanalyze_screening_coherence()- HTS reliable hits
phaselab.protein.mutscan - Mutational scanning analysis
analyze_mutscan_coherence()- Functional domain identificationlocal_coherence_profile()- Per-residue coherencemap_coherence_to_structure()- PDB B-factor mapping
Quantum Mode Configuration
New quantum execution modes:
from phaselab.quantum import QuantumMode, set_quantum_mode
set_quantum_mode(QuantumMode.OFF) # Classical only (fastest)
set_quantum_mode(QuantumMode.AUDIT) # Classical + quantum validation
set_quantum_mode(QuantumMode.REQUIRED) # Quantum mandatory (slowest)
Breaking Changes
compute_coherence=Truein CRISPR pipeline is deprecated (no effect)weight_coherencedefaults to 0.0 (was 1.0)Guide-sequence coherence functions emit deprecation warnings
SMS trials config now uses spatial coherence by default
Upgrade Guide
Replace guide-sequence coherence:
# OLD (deprecated):
from phaselab.crispr import design_guides
guides = design_guides(seq, tss, compute_coherence=True)
# NEW (v1.0.0):
from phaselab.spatial import analyze_tiling_coherence
result = analyze_tiling_coherence(tiling_landscape)
stable_positions = [r['start'] for r in result.stable_regions]
Version 0.9.5 (December 2025)#
Quantum Discriminator for Late-Stage Guide Selection
This release adds a quantum chemistry module for discriminating between elite CRISPRa guides that are classically indistinguishable. Uses IBM Quantum hardware or simulation to resolve binding energy differences.
Core Claim:
IR-enhanced quantum VQE on current IBM hardware can resolve binding energy differences between CRISPRa guides that are indistinguishable under classical scoring, providing a physically grounded late-stage discriminator for therapeutic guide selection.
New Components:
Effective Binding Hamiltonian: H = H_HB + H_stack + H_charge + H_constraint
Watson-Crick hydrogen bonding (G-C: -0.18 eV, A-T: -0.12 eV)
π-π stacking stabilization
Backbone electrostatics with screening
12-qubit seed region encoding
Quantum VQE Execution:
EfficientSU2 ansatz (2 reps, linear entanglement)
COBYLA optimizer with 30 max iterations
1000 shots per measurement
Hardware support: ibm_torino, ibm_brisbane, etc.
GO/NO-GO Threshold: R̄ > e⁻² ≈ 0.135 for execution quality
New API:
from phaselab.crispr import (
run_quantum_discriminator,
design_guides_with_quantum_discriminator,
DiscriminatorStatus,
DISCRIMINATOR_GATES,
)
# Run discriminator on degenerate guides
result = run_quantum_discriminator(
guides=elite_guides,
dna_context=promoter_sequence,
use_hardware=False, # True for IBM Quantum
)
print(result.summary())
# Quantum-resolved ranking with energy separations
Pre-Quantum Gates:
min_mit_score: 50
max_exonic_ot: 0
min_delta_r: 0.30
min_phase_coherence: 0.90
Status Codes: QUANTUM_SUCCESS, NO_DEGENERACY, INSUFFICIENT_GUIDES, QUANTUM_FAILED
Version 0.9.4 (December 2025)#
Three Breakthrough Paths for CRISPRa Guide Ranking
This release adds three complementary scoring paths for CRISPRa guide selection:
Path A: Binding Energy Landscape - Quantum chemistry for relative binding energetics using effective Hamiltonians with Watson-Crick base pairing.
Path B: Transcriptional Phase Alignment - IR dynamics for phase perturbation modeling using vectorized Kuramoto oscillator simulation.
Path C: Off-Target Landscape Geometry - Coherence contrast between on-target and off-target binding for specificity scoring.
Multi-Evidence Fusion: Combines all three paths using weighted geometric mean for unified guide ranking.
from phaselab.crispr import (
compute_binding_energy,
compute_phase_alignment,
compute_offtarget_geometry,
compute_multi_evidence_score,
)
# Combined scoring
result = compute_multi_evidence_score(
guide_sequence=guide,
promoter_sequence=promoter,
tss_position=tss,
guide_position=guide_pos,
)
print(f"Combined score: {result.combined_score:.3f}")
Version 0.9.3 (December 2025)#
CRISPRa Binding Register Model - Major Methodology Correction
This release corrects a fundamental assumption in CRISPRa guide enumeration that caused systematic exclusion of experimentally validated guides in GC-dense promoters.
The Problem: Standard CRISPR pipelines use rigid PAM-spacer anchoring
(guide_start = pam_start - guide_length) derived from cutting-era Cas9 work.
This assumption is invalid for CRISPRa/dCas9 binding, where:
Binding tolerates non-canonical PAMs
The functional binding register can shift ±1-2bp
GC-dense promoters have overlapping PAM-like motifs
The Fix: v0.9.3 introduces:
NucleaseRole enum: Explicit
BINDINGvsCUTTINGmodeRelaxed PAM patterns: e.g., SaCas9 NNGRRN (binding) vs NNGRRT (cutting)
Sliding binding register: ±2bp enumeration in BINDING mode
Configurable guide length: Override defaults (e.g., 20bp with SaCas9)
Validation: Chang et al. 2022 sg2 winner (CCTGGCACCCGAGGCCACGA) was
systematically excluded by all prior versions. v0.9.3 correctly recovers it at
TSS-80 with the NNGRRN PAM pattern.
New CRISPRa Design API
from phaselab.crispr import design_crispra_guides, Nuclease, NucleaseRole
# Design CRISPRa guides with explicit binding mode
result = design_crispra_guides(
gene_symbol="Rai1",
promoter_sequence=promoter_seq,
tss_position=600,
nuclease=Nuclease.SACAS9,
relaxed_pam=True, # BINDING mode (default for CRISPRa)
guide_length=20, # Override default 21bp
)
# Access results
for guide in result.tier_a_guides[:5]:
print(f"{guide['sequence']} TSS{guide['tss_relative_position']:+d}")
Key Insight (Publishable):
CRISPRa guide effectiveness is invariant to small PAM-guide register shifts in GC-dense promoters. Computational pipelines that enforce rigid spacer anchoring systematically miss experimentally validated guides.
This is not a bug fix - it’s a modeling correction that reflects the biological reality of dCas9 binding tolerance.
Version 0.9.2 (December 2025)#
Dominance-Based Ranking System
Lexicographic sorting on (0mm, 1mm, 2mm) off-targets
Hard gates exclude guides entirely (not just penalized)
Tier system: A (0/0/0), B (0/0/1-2), C (other)
Policy-explicit ranking with reproducibility manifests
RankingPolicy System
CUTTING_STRICT: Maximum safety for knockoutBINDING_STRICT: For CRISPRa/CRISPRi binding applicationsEXPLORATORY: Relaxed constraints for research (not therapeutic)
Version 0.9.1 (December 2025)#
CRISPOR-Style Composite Scoring
New
crispor_composite_score()function with mismatch distance weightingOff-target penalties: 0-1mm (critical), 2mm (important), 3-4mm (minimal)
Properly handles the “MIT 98 / CFD 98 trap” from high-OT guides
rank_guides_crispor_style()for batch ranking with automatic exclusions
U6/Pol III Compatibility Checks
poly_t_penalty()detects TTTT runs that terminate U6 transcriptionis_repeat_region()identifies tandem and dinucleotide repeatsu6_compatibility_check()comprehensive promoter compatibility
API Additions
from phaselab.crispr import (
# CRISPOR composite scoring (v0.9.1)
crispor_composite_score,
rank_guides_crispor_style,
OFFTARGET_MISMATCH_WEIGHTS,
CRISPORMetrics,
# U6/Pol III compatibility (v0.9.1)
poly_t_penalty,
is_repeat_region,
u6_compatibility_check,
)
Version 0.9.0 (December 2025)#
SMS Trials Module
Complete therapeutic trial framework for Smith-Magenis Syndrome
CRISPRa RAI1 activation trial with therapeutic window validation
CRISPRi modifier gene suppression trials (PER1, CRY1, CLOCK)
Knockout model validation trials (research use only)
Base editing trials for RAI1 point mutation correction
Prime editing trials for regulatory motif repair
Circadian rescue simulation with sleep/wake prediction
AAV delivery feasibility assessment for CNS targeting
SMS Pipeline Orchestrator
Integrated GO/NO-GO decision system
Multi-trial coordination with claim level propagation
Automatic falsification test generation
Wet lab recommendations and validation priorities
Falsification Test Framework
Test A: Ranking validity (PhaseLab vs random controls)
Test B: Risk prediction (CAUTION guides should fail more)
Test C: Dosage prediction (expression correlation)
Test D: UNKNOWN bucket calibration
API Additions
from phaselab.trials.sms import (
SMSPipeline,
SMSTrialConfig,
run_sms_crispra_trial,
run_sms_crispri_trial,
run_circadian_rescue_simulation,
run_delivery_assessment,
)
Version 0.8.0 (December 2025)#
Claim Level System
Four-tier evidence classification: STRONG_COMPUTATIONAL, CONTEXT_DEPENDENT, EXPLORATORY, UNKNOWN
Claim level propagation through all pipelines
Prevents over-claiming from computational predictions
Fusion Module
Multi-source data integration with uncertainty quantification
Virtual assay stack for enhanced guide scoring
Tissue-specific modeling integration
Version 0.7.0 (November 2025)#
Enhanced Pipeline
design_enhanced_guides()with modality-specific scoringFull modality support: CRISPRa, CRISPRi, Knockout, Base Editing, Prime Editing
Tissue-specific scoring for brain, liver, blood, muscle
API Additions
from phaselab.crispr.enhanced_pipeline import (
design_enhanced_guides,
EnhancedGuideConfig,
Modality,
)
Version 0.6.1 (December 2025)#
Coherence Mode Parameter
Added
mode="heuristic"(fast) vsmode="quantum"(VQE) parameterHeuristic mode is now default for speed
Quantum mode provides research-grade accuracy
Honest Coherence Weighting
Heuristic coherence demoted to tie-breaker weight (0.05 vs 0.30)
Prevents over-reliance on proxy metrics
Two-stage scoring: hard safety gates + soft ranking
Risk Mass Metrics
Added
risk_mass_close: Off-targets within 100bp of TSSAdded
risk_mass_exonic: Off-targets in exonic regionsAdded
tail_risk_score: Aggregate tail risk metric
Evidence Levels
Level A: Hardware-validated (IBM Quantum)
Level B: VQE-simulated (quantum mode)
Level C: Heuristic only (capped influence)
Score Capping
Unvalidated guides capped to prevent misleading rankings
Evidence level affects maximum achievable score
Version 0.6.0 (November 2025)#
ATLAS-Q Integration
Full integration with ATLAS-Q tensor network simulator
IR measurement grouping (5x variance reduction)
Real circular statistics coherence (replaces heuristic)
Coherence-Aware VQE
VQE optimization with real-time coherence tracking
GO/NO-GO classification during optimization
Optional GPU acceleration via Triton kernels
Rust Backend Support
Optional Rust backend for 30-77x faster simulation
Automatic fallback to Python if Rust unavailable
CRISPOR Integration
IR-enhanced off-target analysis
Off-target entropy metrics
Coherence contrast scoring
Unified ATLAS-Q Coherence
Single coherence computation path for all CRISPR modalities
Consistent API across CRISPRa, CRISPRi, knockout, editing
Version 0.5.0 (October 2025)#
Real ATAC-seq Integration
BigWig file support for tissue-specific accessibility
CpG methylation modeling for CRISPRa efficiency
Nucleosome Occupancy
NuPoP-like algorithm for nucleosome prediction
Integration with guide scoring
Multi-Guide Synergy
Combinatorial CRISPR design
Pairwise synergy prediction
Guide set optimization
Enhancer Targeting
Enhancer identification and scoring
CRISPRa enhancer guide design
Promoter vs enhancer comparison
AAV Delivery Modeling
Serotype selection
Delivery efficiency prediction
Immunogenicity assessment
Validation Reports
Comprehensive validation report generation
Evidence summary and confidence scoring
Version 0.4.0 (September 2025)#
Complete CRISPR Toolkit
CRISPR knockout (Cas9 cutting)
CRISPRi (transcriptional repression)
All modalities hardware-validated on IBM Torino
Therapeutic Dosage Optimization
Haploinsufficiency models
Dose-response prediction
Therapeutic window estimation
Version 0.3.0 (August 2025)#
Multi-Tissue Circadian Models
Inter-tissue coupling
Tissue-specific parameters
SCN-peripheral synchronization
Drug Response Modeling
Chronotherapy optimization
Dosing schedule prediction
Response curve modeling
Expanded CRISPR Editors
Base editing (ABE/CBE)
Prime editing (pegRNA design)
Bystander prediction
Version 0.2.0 (July 2025)#
Protein Folding Coherence
Folding reliability assessment
Coherence-structure correlation
Engineering applications
Tissue-Specific Chromatin
ENCODE integration
Cell-type specific accessibility
Tissue-aware guide scoring
Version 0.1.0 (June 2025)#
Initial Release
Core coherence metrics (R, V_phi)
GO/NO-GO classification
Basic CRISPRa guide design
SMS circadian clock model
IBM Quantum integration