PoissonQuantificationChecker

URS & FS — User Requirements and Functional Specification

This document describes the controlled interface and behaviour of PoissonQuantificationChecker for Poisson Quantification Checker.

Domain limits and critical parameters

• Performs statistical verification of digital PCR/BEAMing quantification per CLSI EP25-A, MIQE-dPCR, FDA dPCR guidance and dMIQE standards: lambda assessment (optimal 0.1–0.8 mol/partition; >0.8 violates Poisson assumption requiring dilution), goodness-of-fit (χ² p≥0.05 confirms Poisson model), overdispersion factor (variance/mean ≤1.5 for random partitioning), 95% CI width (≤25% for quantitative, 25–50% semi-quantitative, >50% qualitative only), rain fraction (≤2%), cluster separation adequacy,
• ⚠️ Critical: λ > 0.8 = SYSTEMATIC QUANTIFICATION ERROR (underestimation). Saturation (all partitions positive) = quantification IMPOSSIBLE. Overdispersion indicates aggregation or non-random partitioning. Wide CI at low positive counts is statistical consequence, not necessarily failure. For MRD/liquid biopsy, λ often <0.1; acceptable but CI will be wide. Tool verifies STATISTICAL CORRECTNESS only; does not replace analytical validation. Results must be interpreted within validated assay perform

URS — User Requirements Specification

input.csv contract

SampleID,AssayName,Technology,TotalPartitions,PositivePartitions,NegativePartitions,Lambda_Observed,Lambda_Target_Min,Lambda_Target_Max,Concentration_copies_uL,CI95_Lower_copies_uL,CI95_Upper_copies_uL,CI95_Width_Percent,MaxCI95_Width_Percent,ChiSquare_GoodnessOfFit_P,MinChiSquare_P,Overdispersion_Factor,MaxOverdispersion,RainFraction_Percent,MaxRainFraction_Percent,ClusterSeparation_Adequate,SignalToNoise_Ratio,MinSignalToNoise,NumReplicates,ReplicateCV_Percent,MaxReplicateCV_Percent,OutlierReplicate_Detected,PositiveControl_Pass,NegativeControl_Pass,NoTemplateControl_Pass,AssayLOD_copies_uL,AssayLOQ_copies_uL,BelowLOD,BelowLOQ
POIS-2026-001,KRAS_G12D_ddPCR,ddPCR_droplet,20000,4500,15500,0.256,0.1,0.8,128.0,124.2,131.9,6.0,25,0.42,0.05,1.05,1.5,0.8,2.0,true,35.0,10,4,8.5,25,false,true,true,true,0.5,2.0,false,false
POIS-2026-002,EGFR_T790M_BEAMing,BEAMing,50000,38000,12000,1.427,0.1,0.8,713.5,580.0,890.0,43.4,25,0.001,0.05,2.8,1.5,5.5,2.0,false,6.0,10,3,35.0,25,true,true,true,true,0.5,2.0,false,false
POIS-2026-003,BRAF_V600E_ddPCR,ddPCR_chip,770,5,765,0.0065,0.1,0.8,0.85,0.28,1.98,200.0,25,0.85,0.05,1.1,1.5,0.2,2.0,true,28.0,10,4,65.0,25,false,true,true,true,0.5,2.0,false,true

Input validation rules

FS — Functional Specification

Example output.json

{
  "utilityId": "poissonquantificationchecker",
  "utilityFolder": "PoissonQuantificationChecker",
  "package": "LiquidBiopsy",
  "overallStatus": "PASS|WARNING|FAIL",
  "sourceFile": "input.csv",
  "processedAtUtc": "2026-06-10T00:00:00Z",
  "checks": [
    {
      "parameter": "SampleID",
      "value": "POIS-2026-001",
      "status": "PASS|WARNING|FAIL",
      "message": "Deterministic rule-based check result",
      "ruleReference": "FS-RULE-001"
    },
    {
      "parameter": "AssayName",
      "value": "KRAS_G12D_ddPCR",
      "status": "PASS|WARNING|FAIL",
      "message": "Deterministic rule-based check result",
      "ruleReference": "FS-RULE-002"
    },
    {
      "parameter": "Technology",
      "value": "ddPCR_droplet",
      "status": "PASS|WARNING|FAIL",
      "message": "Deterministic rule-based check result",
      "ruleReference": "FS-RULE-003"
    },
    {
      "parameter": "TotalPartitions",
      "value": "20000",
      "status": "PASS|WARNING|FAIL",
      "message": "Deterministic rule-based check result",
      "ruleReference": "FS-RULE-004"
    },
    {
      "parameter": "PositivePartitions",
      "value": "4500",
      "status": "PASS|WARNING|FAIL",
      "message": "Deterministic rule-based check result",
      "ruleReference": "FS-RULE-005"
    },
    {
      "parameter": "NegativePartitions",
      "value": "15500",
      "status": "PASS|WARNING|FAIL",
      "message": "Deterministic rule-based check result",
      "ruleReference": "FS-RULE-006"
    },
    {
      "parameter": "Lambda_Observed",
      "value": "0.256",
      "status": "PASS|WARNING|FAIL",
      "message": "Deterministic rule-based check result",
      "ruleReference": "FS-RULE-007"
    },
    {
      "parameter": "Lambda_Target_Min",
      "value": "0.1",
      "status": "PASS|WARNING|FAIL",
      "message": "Deterministic rule-based check result",
      "ruleReference": "FS-RULE-008"
    },
    {
      "parameter": "Lambda_Target_Max",
      "value": "0.8",
      "status": "PASS|WARNING|FAIL",
      "message": "Deterministic rule-based check result",
      "ruleReference": "FS-RULE-009"
    },
    {
      "parameter": "Concentration_copies_uL",
      "value": "128.0",
      "status": "PASS|WARNING|FAIL",
      "message": "Deterministic rule-based check result",
      "ruleReference": "FS-RULE-010"
    },
    {
      "parameter": "CI95_Lower_copies_uL",
      "value": "124.2",
      "status": "PASS|WARNING|FAIL",
      "message": "Deterministic rule-based check result",
      "ruleReference": "FS-RULE-011"
    },
    {
      "parameter": "CI95_Upper_copies_uL",
      "value": "131.9",
      "status": "PASS|WARNING|FAIL",
      "message": "Deterministic rule-based check result",
      "ruleReference": "FS-RULE-012"
    }
  ],
  "criticalFindings": [],
  "warnings": [],
  "audit": {
    "inputHash": "sha256:<calculated at runtime>",
    "rulesVersion": "<utility executable version>",
    "documentation": "PoissonQuantificationChecker.documentation.html"
  }
}

Traceability matrix

IQ/OQ/PQ test scenarios

QA/QC and change control

• Do not rename columns without updating validator, documentation and test set.
• Retain input.csv, output.json, executable version and checksum.
• Before production use, perform IQ/OQ/PQ or equivalent CSV/CSA verification.
• Critical limits shall be verified against the approved specification, registration dossier and local SOPs.
• The utility provides structured QC decision support; final release decision remains with QA/QP and approved procedures.