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44fb3c3 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 | """decision_engine.py — PeVe v1.1 Deterministic Synthesis Engine"""
from __future__ import annotations
from dataclasses import dataclass, field
from typing import Optional
import numpy as np
from config import (
PEVE_VERSION, THRESHOLD_VERSION,
SPLICE_PROB_HIGH, SPLICE_PROB_MODERATE, SPLICE_PROB_WEAK,
SPLICE_SIGNAL_MIN, SPLICE_DOMINANT_MIN,
ACTIVATION_NORM_HIGH, ACTIVATION_NORM_MODERATE, ACTIVATION_NORM_WEAK,
CONTEXT_ACTIVE_MIN, BIOCHEMICAL_RISK_ACTIVE,
AF_RARITY_THRESHOLD, AF_HIGH_CONFLICT,
BOUNDARY_TOLERANCE, WINDOW_BP, PEAK_OFF_CENTER_FRAC,
)
from prefilter import VariantClass
from af_handler import AFResult, AF_NUMERIC, AF_ZERO, AF_UNKNOWN, AF_UNCERTAIN
# ── Raw layer outputs ─────────────────────────────────────
@dataclass
class SpliceLayerOutput:
splice_prob: float
splice_signal_strength: float
counterfactual_delta: float
saliency_map: Optional[object]
model_available: bool = True
@dataclass
class ContextLayerOutput:
context_pathogenic_prob: float
activation_norm: float
activation_peak_position: int
importance_score: float
model_available: bool = True
@dataclass
class ProteinLayerOutput:
biochemical_risk_score: float
feature_pathogenic_prob: float
shap_feature_contributions: dict
l3_substitution_valid: bool
model_available: bool = True
# ── Band classifiers ──────────────────────────────────────
def _splice_band(p):
if p >= SPLICE_PROB_HIGH: return "High"
if p >= SPLICE_PROB_MODERATE: return "Moderate"
if p >= SPLICE_PROB_WEAK: return "Weak"
return "Inactive"
def _context_band(n):
if n >= ACTIVATION_NORM_HIGH: return "High"
if n >= ACTIVATION_NORM_MODERATE: return "Moderate"
if n >= ACTIVATION_NORM_WEAK: return "Weak"
return "Inactive"
def _near(val, thresh): return abs(val - thresh) <= BOUNDARY_TOLERANCE
def _off_center(pos): return abs(pos - WINDOW_BP//2) > int(WINDOW_BP * PEAK_OFF_CENTER_FRAC)
# ── Activation levels ─────────────────────────────────────
@dataclass
class ActivationLevels:
splice_band: str; rna_active: bool; rna_dominant: bool
context_band: str; context_active: bool
protein_active: bool; l3_valid: bool
rna_boundary: bool; context_boundary: bool; protein_boundary: bool
def compute_activation_levels(splice, context, protein, af_result):
s_band = _splice_band(splice.splice_prob)
rna_active = splice.splice_prob >= SPLICE_PROB_MODERATE and splice.splice_signal_strength >= SPLICE_SIGNAL_MIN
rna_dominant = splice.splice_prob >= SPLICE_DOMINANT_MIN
c_band = _context_band(context.activation_norm)
ctx_active = context.activation_norm >= CONTEXT_ACTIVE_MIN
prot_active = (protein.l3_substitution_valid and
protein.biochemical_risk_score >= BIOCHEMICAL_RISK_ACTIVE and
af_result.satisfies_rarity())
rna_b = _near(splice.splice_prob, SPLICE_PROB_MODERATE) or _near(splice.splice_prob, SPLICE_DOMINANT_MIN) or _near(splice.splice_signal_strength, SPLICE_SIGNAL_MIN)
ctx_b = _near(context.activation_norm, CONTEXT_ACTIVE_MIN) or _near(context.activation_norm, ACTIVATION_NORM_HIGH)
pro_b = _near(protein.biochemical_risk_score, BIOCHEMICAL_RISK_ACTIVE)
return ActivationLevels(s_band, rna_active, rna_dominant, c_band, ctx_active, prot_active,
protein.l3_substitution_valid, rna_b, ctx_b, pro_b)
# ── Conflict detection ────────────────────────────────────
@dataclass
class ConflictReport:
major_conflicts: list = field(default_factory=list)
minor_conflicts: list = field(default_factory=list)
requires_manual_review: bool = False
conflict_score_major: int = 0
conflict_score_minor: int = 0
def compute_review_flag(self):
self.conflict_score_major = len(self.major_conflicts)
self.conflict_score_minor = len(self.minor_conflicts)
self.requires_manual_review = self.conflict_score_major >= 1 or self.conflict_score_minor >= 2
def detect_conflicts(splice, context, protein, af_result, activation, variant_class):
r = ConflictReport()
if splice.splice_prob >= SPLICE_PROB_HIGH and af_result.triggers_high_af_conflict():
r.major_conflicts.append(
f"MAJOR: High splice_prob ({splice.splice_prob:.3f}) + common variant (AF={af_result.global_af:.5f}). "
"Splice-disrupting variant unlikely at this population frequency.")
if (protein.l3_substitution_valid and protein.biochemical_risk_score >= BIOCHEMICAL_RISK_ACTIVE
and af_result.triggers_high_af_conflict()):
r.major_conflicts.append(
f"MAJOR: High biochemical risk ({protein.biochemical_risk_score:.3f}) + common variant "
f"(AF={af_result.global_af:.5f}). Common biochemically disruptive variants are typically tolerated.")
if variant_class.variant_class == "canonical_splice" and not activation.rna_active:
r.major_conflicts.append(
f"MAJOR: Canonical splice site ({variant_class.raw_consequence}) but RNA model inactive "
f"(splice_prob={splice.splice_prob:.3f}). Model/annotation disagreement.")
bnd = []
if activation.rna_boundary: bnd.append(f"splice_prob({splice.splice_prob:.3f})/signal({splice.splice_signal_strength:.3f})")
if activation.context_boundary: bnd.append(f"activation_norm({context.activation_norm:.3f})")
if activation.protein_boundary: bnd.append(f"biochemical_risk({protein.biochemical_risk_score:.3f})")
if bnd: r.minor_conflicts.append(f"MINOR: Boundary proximity — {'; '.join(bnd)} within ±{BOUNDARY_TOLERANCE}.")
if _off_center(context.activation_peak_position):
offset = abs(context.activation_peak_position - WINDOW_BP//2)
r.minor_conflicts.append(f"MINOR: Activation peak {offset}bp from mutation centre (pos={context.activation_peak_position}).")
if activation.context_active and variant_class.raw_consequence in {
"synonymous_variant","intron_variant","upstream_gene_variant","downstream_gene_variant"}:
r.minor_conflicts.append(
f"MINOR: Context active (norm={context.activation_norm:.3f}) but VEP='{variant_class.raw_consequence}' (low impact).")
if af_result.state in {AF_UNKNOWN, AF_UNCERTAIN}:
r.minor_conflicts.append(f"MINOR: AF state={af_result.state} — rarity unconfirmed.")
r.compute_review_flag()
return r
# ── Mechanism constants ───────────────────────────────────
DOMINANT_RNA = "RNA_Splicing"
DOMINANT_PROTEIN = "Protein_Biochemical"
DOMINANT_CONTEXT = "Sequence_Context"
DOMINANT_AMBIGUITY = "Mechanism_Ambiguity"
DOMINANT_TRUNCATION = "Protein_Truncation"
DOMINANT_INSUFFICIENT = "Insufficient_Evidence"
DOMINANT_OOS = "Out_Of_Scope"
DOMINANT_CONFLICT_REVIEW = "Conflict_Manual_Review"
# ── Synthesis result ──────────────────────────────────────
@dataclass
class SynthesisResult:
dominant_mechanism: str
final_classification: str
supporting_mechanisms: list
activation_levels: ActivationLevels
conflict_report: ConflictReport
reasoning_steps: list
transcript_ambiguity: bool
af_uncertainty: bool
version: str = PEVE_VERSION
threshold_version: str = THRESHOLD_VERSION
def _mkr(dom, cls, sup, act, conf, steps, vc, af):
return SynthesisResult(dom, cls, sup, act, conf, steps,
vc.transcript_conflict, af.state in {AF_UNKNOWN, AF_UNCERTAIN})
# ── Main synthesis ────────────────────────────────────────
def synthesize(splice, context, protein, af_result, variant_class):
act = compute_activation_levels(splice, context, protein, af_result)
conf = detect_conflicts(splice, context, protein, af_result, act, variant_class)
steps = []
sup = []
# Conflict override
if conf.requires_manual_review and conf.conflict_score_major >= 1:
steps.append(f"CONFLICT OVERRIDE: {conf.conflict_score_major} major conflict(s). Classification suppressed.")
return _mkr(DOMINANT_CONFLICT_REVIEW, "Conflict — Manual Review Required", [], act, conf, steps, variant_class, af_result)
# Out of scope
if variant_class.out_of_scope:
steps.append(f"Variant class '{variant_class.variant_class}' is outside PeVe v1.1 scope.")
return _mkr(DOMINANT_OOS, "Out of Scope — See Flags", [], act, conf, steps, variant_class, af_result)
# Truncation gate
if variant_class.variant_class in {"frameshift","stop_gained","start_lost"}:
steps.append(f"Variant class '{variant_class.variant_class}' — protein truncation. L3 substitution metrics excluded.")
if act.rna_active:
steps.append(f"RNA also active (splice_prob={splice.splice_prob:.3f}) — possible NMD-relevant splice signal.")
sup.append(DOMINANT_RNA)
return _mkr(DOMINANT_TRUNCATION, "Protein Truncation", sup, act, conf, steps, variant_class, af_result)
if variant_class.transcript_conflict:
steps.append("Transcript conflict: consequence differs across transcripts. Both mechanisms elevated.")
# Rule 1: RNA High → dominant
if act.rna_dominant:
steps.append(f"RULE 1: RNA HIGH (splice_prob={splice.splice_prob:.3f}≥{SPLICE_DOMINANT_MIN}, signal={splice.splice_signal_strength:.3f}). RNA dominant.")
if act.protein_active: sup.append(DOMINANT_PROTEIN); steps.append(f" Supporting: Protein active (risk={protein.biochemical_risk_score:.3f}).")
if act.context_active: sup.append(DOMINANT_CONTEXT); steps.append(f" Supporting: Context active (norm={context.activation_norm:.3f}).")
return _mkr(DOMINANT_RNA, "Pathogenic — RNA Splice Mechanism", sup, act, conf, steps, variant_class, af_result)
# Rule 1b: RNA Moderate + Protein Active → ambiguity
if act.rna_active and act.protein_active:
steps.append(f"RULE 1b: RNA MODERATE (splice_prob={splice.splice_prob:.3f}) + Protein ACTIVE (risk={protein.biochemical_risk_score:.3f}). Mechanism Ambiguity.")
return _mkr(DOMINANT_AMBIGUITY, "Mechanism Ambiguity — Manual Review Recommended",
[DOMINANT_RNA, DOMINANT_PROTEIN], act, conf, steps, variant_class, af_result)
# Rule 2: Protein dominant
if act.protein_active:
steps.append(f"RULE 2: RNA inactive. Protein ACTIVE (risk={protein.biochemical_risk_score:.3f}, AF={af_result.global_af}).")
if act.context_active: sup.append(DOMINANT_CONTEXT); steps.append(f" Supporting: Context active (norm={context.activation_norm:.3f}).")
if act.rna_active:
sup.append(DOMINANT_RNA)
steps.append(f" Note: Moderate RNA signal present (splice_prob={splice.splice_prob:.3f}). mechanism_ambiguity_flag added.")
conf.minor_conflicts.append("MINOR: Moderate RNA signal alongside Protein-dominant call.")
conf.compute_review_flag()
return _mkr(DOMINANT_PROTEIN, "Pathogenic — Protein Biochemical Mechanism", sup, act, conf, steps, variant_class, af_result)
# Rule 3: Context dominant
if act.context_active:
if variant_class.variant_class == "substitution_synonymous":
steps.append(f"RULE 3 BLOCKED: Context active but synonymous variant — context alone cannot classify pathogenic.")
else:
steps.append(f"RULE 3: RNA+Protein inactive. Context ACTIVE (norm={context.activation_norm:.3f}).")
return _mkr(DOMINANT_CONTEXT, "Uncertain — Sequence Context Signal Only", [], act, conf, steps, variant_class, af_result)
# Rule 4: Insufficient evidence
steps.append(
f"RULE 4: No mechanism active. RNA={act.splice_band} Context={act.context_band} "
f"Protein active={act.protein_active} (L3 valid={act.l3_valid}, rare={af_result.satisfies_rarity()})."
)
if conf.requires_manual_review:
steps.append(f"Minor conflict threshold reached ({conf.conflict_score_minor} minor). Upgrading to Review.")
return _mkr(DOMINANT_CONFLICT_REVIEW, "Conflict — Manual Review Required", [], act, conf, steps, variant_class, af_result)
return _mkr(DOMINANT_INSUFFICIENT, "Likely Benign or Insufficient Evidence", [], act, conf, steps, variant_class, af_result)
# ── Narrative builder ─────────────────────────────────────
def build_narrative(result, splice, context, protein, af_result, variant_class):
lines = [f"PeVe v{PEVE_VERSION} Structured Reasoning Narrative", "="*60]
lines.append(f"Variant class: {variant_class.variant_class.replace('_',' ').title()}")
lines.append(f"RNA: splice_prob={splice.splice_prob:.3f} (band={result.activation_levels.splice_band}), "
f"signal={splice.splice_signal_strength:.3f}. "
+ ("ACTIVE." if result.activation_levels.rna_active else "INACTIVE."))
lines.append(f"Context: activation_norm={context.activation_norm:.3f} (band={result.activation_levels.context_band}). "
+ ("ACTIVE." if result.activation_levels.context_active else "INACTIVE."))
if result.activation_levels.l3_valid:
af_str = f"AF={af_result.global_af:.6f}" if af_result.global_af is not None else f"AF_state={af_result.state}"
lines.append(f"Protein: biochemical_risk={protein.biochemical_risk_score:.3f}, {af_str}. "
+ ("ACTIVE." if result.activation_levels.protein_active else "INACTIVE."))
else:
lines.append("Protein substitution metrics: NOT APPLICABLE for this variant class.")
lines.append("")
lines.append(f"Dominant mechanism: {result.dominant_mechanism.replace('_',' ')}")
lines.append(f"Final classification: {result.final_classification}")
if result.supporting_mechanisms:
lines.append(f"Supporting: {', '.join(m.replace('_',' ') for m in result.supporting_mechanisms)}")
if result.conflict_report.major_conflicts:
lines.append("\nMAJOR CONFLICTS:")
lines.extend(f" • {c}" for c in result.conflict_report.major_conflicts)
if result.conflict_report.minor_conflicts:
lines.append("MINOR CONFLICTS / BOUNDARY FLAGS:")
lines.extend(f" • {c}" for c in result.conflict_report.minor_conflicts)
if result.transcript_ambiguity:
lines.append("⚠ Transcript conflict: consequence differs across transcripts.")
if variant_class.flags:
lines.append("\nPre-filter flags:")
lines.extend(f" • {f}" for f in variant_class.flags)
if result.conflict_report.requires_manual_review:
lines.append("\n⛔ MANUAL REVIEW REQUIRED.")
lines.append("="*60)
lines.append(f"PeVe v{PEVE_VERSION} | Thresholds {THRESHOLD_VERSION} | No probability averaging.")
return "\n".join(lines)
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