GermlineSomaticResultGateChecker

Germline/Somatic Result Gate

Liquid Biopsy жидкостная биопсия cfDNA ctDNA CTC exosomes NGS qPCR

Utility description: Germline/Somatic Result Gate

Germline/Somatic Result Gate Checker — Variant Classification Validation

ℹ️ Utility performs comprehensive verification of variant classification in paired tumor-normal analyses according to AMP/ASCO/CAP, ACMG/AMP and FDA NGS guidance:
• Paired Normal Verification: Confirmation of paired normal sample availability and usage for somatic calls.
• VAF Differential: Verification of statistical significance of VAF difference between tumor and normal.
• Population Frequency Filter: Exclusion of high-frequency gnomAD variants from somatic calls.
• Dual Annotation Check: Guarantee of appropriate annotation (AMP/ASCO/CAP for somatic, ACMG/AMP for germline).
• Artifact Detection: Identification of LOH, clonal hematopoiesis, and discordant classifications.

⚠️ IMPORTANT:
• Somatic variant without paired normal has unacceptably high false-positive rate.
• Variant with gnomAD AF >1% is almost never a somatic driver.
• Germline pathogenic variant missed as somatic deprives patient of prevention and family screening.
• LOH in tumor can mask germline variant as somatic at low normal VAF.

Usage:
GermlineSomaticResultGateChecker.exe → demo mode (console output)
GermlineSomaticResultGateChecker.exe input.csv output.json → evaluate your data

Input format:
PatientID,TumorSampleID,NormalSampleID,PairedNormalAvailable,VariantClassification,TumorVAF_Percent,NormalVAF_Percent,MinSomaticVAF_Diff,GnomAD_AF,MaxGermline_GnomAD_AF,HasLOH_Flag,HasClonalHematopoiesis_Flag,SomaticSignificance_Annotated,GermlinePathogenicity_Annotated,DiscordantClassification,ReviewerNotes

Example:
PAT-001,T-001,N-001,true,Somatic,32.5,0.0,5.0,0.00001,0.01,false,false,true,false,false,

📍 Scope of Application (Usage Where):
• Clinical Oncogenomics: Final check before integrated tumor-normal report release.
• Hereditary Oncology: Identification of germline mutations in tumor panels.
• NGS Pipeline Developers: Validation of somatic calling algorithms.
• Molecular Tumor Boards: Objective basis for complex variant discussion.

— WHY IS THIS NEEDED?
Mixing somatic and germline results is one of the most dangerous errors in molecular oncology.
False-somatic call leads to ineffective targeted therapy prescription.
Missed germline variant deprives patient and family of preventive measures.
Automated gate eliminates systematic classification errors before reaching clinician.

⚠️ CRITICAL:
• Paired Normal: MANDATORY for all somatic calls. Tumor-only = RESEARCH ONLY.
• VAF Diff ≥5%: Lower difference requires manual LOH/subclonality check.
• gnomAD AF <0.01: For somatic calls. Exceedance = likely germline variant.
• Dual Annotation: Somatic without Tier OR germline without ACMG = incomplete report.
• Discordance: Any auto/manual classification contradiction = block until resolution.

Key features:
• Six-parameter classification check
• Adaptive logic for somatic and germline variants
• Integration of VAF, gnomAD, and annotation metrics
• Specific artifact detection (LOH, CHIP)
• Compliance with AMP/ASCO/CAP + ACMG/AMP guidelines

Critical parameters:
• Paired Normal Available: True (for somatic)
• VAF Differential: ≥ Min Threshold
• gnomAD AF: < Max Threshold (for somatic)
• Somatic Annotation: Present (if somatic)
• Germline Annotation: Present (if germline)
• Classification Discordance: False

💡 Usage tips:
1. Paired Samples: Always collect normal tissue/blood concurrently with tumor.
2. VAF Thresholds: Adjust MinSomaticVAF_Diff per sequencing depth and sample type (FFPE vs fresh).
3. gnomAD Version: Use current database version; specify version in report.
4. LOH Analysis: Upon LOH + low normal VAF, verify germline status by independent method.
5. CHIP: For DNMT3A, TET2, ASXL1 variants, always verify blood origin.

⚠️ Note: This utility verifies variant CLASSIFICATION, not primary calling. It assumes variant calling is performed correctly and focuses on proper somatic/germline context separation.

input.csv

PatientID,TumorSampleID,NormalSampleID,PairedNormalAvailable,VariantClassification,TumorVAF_Percent,NormalVAF_Percent,MinSomaticVAF_Diff,GnomAD_AF,MaxGermline_GnomAD_AF,HasLOH_Flag,HasClonalHematopoiesis_Flag,SomaticSignificance_Annotated,GermlinePathogenicity_Annotated,DiscordantClassification,ReviewerNotes
PAT-2026-001,T-001,N-001,true,Somatic,32.5,0.0,5.0,0.00001,0.01,false,false,true,false,false,
PAT-2026-001,T-001,N-001,true,Germline,48.0,50.2,5.0,0.0003,0.01,false,false,false,true,false,
PAT-2026-002,T-002,,false,Somatic,12.0,0.0,5.0,0.005,0.01,false,false,false,false,true,No normal available
PAT-2026-003,T-003,N-003,true,Somatic,45.0,2.0,5.0,0.035,0.01,true,false,true,false,false,Verify germline with LOH

URS & FS — User Requirements and Functional Specification

This document describes the controlled interface and behaviour of GermlineSomaticResultGateChecker for Germline/Somatic Result Gate Checker.

Domain limits URS input.csv FS IQ/OQ/PQ

Domain limits and critical parameters

Key fragments from the source description are shown below. Before production use, limits must be verified against the approved specification, registration dossier and local SOPs.

• Variant with gnomAD AF >1% is almost never a somatic driver.
⚠️ CRITICAL:
• VAF Diff ≥5%: Lower difference requires manual LOH/subclonality check.
• gnomAD AF <0.01: For somatic calls. Exceedance = likely germline variant.
Critical parameters:
• VAF Differential: ≥ Min Threshold
• gnomAD AF: < Max Threshold (for somatic)

URS — User Requirements Specification

ID	Requirement	Criticality	Acceptance criterion
URS-001	The utility shall accept an input.csv file for Germline/Somatic Result Gate Checker with headers defined in the data contract.	High	The file is processed without manual header editing.
URS-002	The utility shall perform deterministic QC evaluation without machine learning and without probabilistic conformance decisions.	High	Identical input data, rule version and configuration produce reproducible results.
URS-003	The utility shall validate mandatory fields, data types, ranges, units and domain plausibility.	High	Schema, conversion and range errors are explicitly reported.
URS-004	The utility shall apply domain limits and rules from the description, approved specification, registration dossier and local SOPs.	High	Each check has PASS/WARNING/FAIL and a clear message.
URS-005	The utility shall generate output.json with machine-readable results, source values, warnings, failures and critical findings.	High	JSON is suitable for LIMS/ELN/MES integration and QA/QC review.
URS-006	The utility shall preserve traceability between batch/sample, input file, applied rules and final status.	High	Output contains identifiers, checked parameters and audit metadata.
URS-007	The documentation shall support IQ/OQ/PQ, CSV/CSA and review by internal QA or inspectors.	Medium	URS, FS, input/output contract and test scenarios are supplied with the utility.
URS-008	The utility shall be used as a QC decision-support tool and not as a substitute for approved specifications and QA/QP release decision.	Medium	Documentation states change control and limit-verification expectations.

input.csv contract

#	Field	Type	Sample	Purpose
1	`PatientID`	string / controlled vocabulary	`PAT-2026-001`	Controlled input parameter for deterministic QC rules.
2	`TumorSampleID`	string / controlled vocabulary	`T-001`	Sample or laboratory specimen identifier.
3	`NormalSampleID`	string / controlled vocabulary	`N-001`	Sample or laboratory specimen identifier.
4	`PairedNormalAvailable`	string / controlled vocabulary	`true`	Controlled input parameter for deterministic QC rules.
5	`VariantClassification`	string / controlled vocabulary	`Somatic`	Controlled input parameter for deterministic QC rules.
6	`TumorVAF_Percent`	decimal	`32.5`	Controlled input parameter for deterministic QC rules.
7	`NormalVAF_Percent`	decimal	`0.0`	Controlled input parameter for deterministic QC rules.
8	`MinSomaticVAF_Diff`	decimal	`5.0`	Controlled input parameter for deterministic QC rules.
9	`GnomAD_AF`	decimal	`0.00001`	Controlled input parameter for deterministic QC rules.
10	`MaxGermline_GnomAD_AF`	decimal	`0.01`	Controlled input parameter for deterministic QC rules.
11	`HasLOH_Flag`	string / controlled vocabulary	`false`	Controlled input parameter for deterministic QC rules.
12	`HasClonalHematopoiesis_Flag`	string / controlled vocabulary	`false`	Controlled input parameter for deterministic QC rules.
13	`SomaticSignificance_Annotated`	string / controlled vocabulary	`true`	Controlled input parameter for deterministic QC rules.
14	`GermlinePathogenicity_Annotated`	string / controlled vocabulary	`false`	Controlled input parameter for deterministic QC rules.
15	`DiscordantClassification`	string / controlled vocabulary	`false`	Controlled input parameter for deterministic QC rules.
16	`ReviewerNotes`	string / controlled vocabulary		Controlled input parameter for deterministic QC rules.

PatientID,TumorSampleID,NormalSampleID,PairedNormalAvailable,VariantClassification,TumorVAF_Percent,NormalVAF_Percent,MinSomaticVAF_Diff,GnomAD_AF,MaxGermline_GnomAD_AF,HasLOH_Flag,HasClonalHematopoiesis_Flag,SomaticSignificance_Annotated,GermlinePathogenicity_Annotated,DiscordantClassification,ReviewerNotes
PAT-2026-001,T-001,N-001,true,Somatic,32.5,0.0,5.0,0.00001,0.01,false,false,true,false,false,
PAT-2026-001,T-001,N-001,true,Germline,48.0,50.2,5.0,0.0003,0.01,false,false,false,true,false,
PAT-2026-002,T-002,,false,Somatic,12.0,0.0,5.0,0.005,0.01,false,false,false,false,true,No normal available

Input validation rules

ID	Field	Rule	Criticality
VR-001	`PatientID`	The field shall match an approved dictionary or accepted string representation.	High
VR-002	`TumorSampleID`	The field shall match an approved dictionary or accepted string representation.	High
VR-003	`NormalSampleID`	The field shall match an approved dictionary or accepted string representation.	High
VR-004	`PairedNormalAvailable`	The field shall match an approved dictionary or accepted string representation.	Medium
VR-005	`VariantClassification`	The field shall match an approved dictionary or accepted string representation.	Medium
VR-006	`TumorVAF_Percent`	The field shall match an approved dictionary or accepted string representation.	Medium
VR-007	`NormalVAF_Percent`	The field shall match an approved dictionary or accepted string representation.	Medium
VR-008	`MinSomaticVAF_Diff`	The field shall match an approved dictionary or accepted string representation.	Medium
VR-009	`GnomAD_AF`	The field shall match an approved dictionary or accepted string representation.	Medium
VR-010	`MaxGermline_GnomAD_AF`	The field shall match an approved dictionary or accepted string representation.	Medium
VR-011	`HasLOH_Flag`	The field shall match an approved dictionary or accepted string representation.	Medium
VR-012	`HasClonalHematopoiesis_Flag`	The field shall match an approved dictionary or accepted string representation.	Medium
VR-013	`SomaticSignificance_Annotated`	The field shall match an approved dictionary or accepted string representation.	Medium
VR-014	`GermlinePathogenicity_Annotated`	The field shall match an approved dictionary or accepted string representation.	Medium
VR-015	`DiscordantClassification`	The field shall match an approved dictionary or accepted string representation.	Medium
VR-016	`ReviewerNotes`	The field shall match an approved dictionary or accepted string representation.	Medium

FS — Functional Specification

ID	Function	Implementation
FS-001	CLI execution	Support execution modes: demo mode without arguments and production mode input.csv output.json.
FS-002	CSV import	Read input.csv in UTF-8/CSV-compatible format and validate header and expected columns.
FS-003	Schema validation	Check mandatory fields, column count, unknown key fields and empty mandatory values.
FS-004	Type conversion	Convert numeric, flag and text values; invalid format is recorded as a row-level error.
FS-005	Domain rule engine	Apply rules for Germline/Somatic Result Gate Checker, including critical limits from the description and approved specification.
FS-006	Status aggregation	Produce final status: FAIL for critical failure, WARNING for non-critical deviation, PASS for conformance.
FS-007	JSON export	Write output.json with detailed checks, source values, warnings, failures and critical findings.
FS-008	Audit support	Keep result structure suitable for review, deviation investigation and calculation reproduction.
FS-009	Integration contract	Support the scenario LIMS/ELN/MES → input.csv → utility → output.json → portal/admin review.
FS-010	Error handling	Return explicit messages for missing file, empty CSV, invalid schema, output write failure and invalid format.

Example output.json

{
  "utilityId": "germlinesomaticresultgatechecker",
  "utilityFolder": "GermlineSomaticResultGateChecker",
  "package": "LiquidBiopsy",
  "overallStatus": "PASS|WARNING|FAIL",
  "sourceFile": "input.csv",
  "processedAtUtc": "2026-06-10T00:00:00Z",
  "checks": [
    {
      "parameter": "PatientID",
      "value": "PAT-2026-001",
      "status": "PASS|WARNING|FAIL",
      "message": "Deterministic rule-based check result",
      "ruleReference": "FS-RULE-001"
    },
    {
      "parameter": "TumorSampleID",
      "value": "T-001",
      "status": "PASS|WARNING|FAIL",
      "message": "Deterministic rule-based check result",
      "ruleReference": "FS-RULE-002"
    },
    {
      "parameter": "NormalSampleID",
      "value": "N-001",
      "status": "PASS|WARNING|FAIL",
      "message": "Deterministic rule-based check result",
      "ruleReference": "FS-RULE-003"
    },
    {
      "parameter": "PairedNormalAvailable",
      "value": "true",
      "status": "PASS|WARNING|FAIL",
      "message": "Deterministic rule-based check result",
      "ruleReference": "FS-RULE-004"
    },
    {
      "parameter": "VariantClassification",
      "value": "Somatic",
      "status": "PASS|WARNING|FAIL",
      "message": "Deterministic rule-based check result",
      "ruleReference": "FS-RULE-005"
    },
    {
      "parameter": "TumorVAF_Percent",
      "value": "32.5",
      "status": "PASS|WARNING|FAIL",
      "message": "Deterministic rule-based check result",
      "ruleReference": "FS-RULE-006"
    },
    {
      "parameter": "NormalVAF_Percent",
      "value": "0.0",
      "status": "PASS|WARNING|FAIL",
      "message": "Deterministic rule-based check result",
      "ruleReference": "FS-RULE-007"
    },
    {
      "parameter": "MinSomaticVAF_Diff",
      "value": "5.0",
      "status": "PASS|WARNING|FAIL",
      "message": "Deterministic rule-based check result",
      "ruleReference": "FS-RULE-008"
    },
    {
      "parameter": "GnomAD_AF",
      "value": "0.00001",
      "status": "PASS|WARNING|FAIL",
      "message": "Deterministic rule-based check result",
      "ruleReference": "FS-RULE-009"
    },
    {
      "parameter": "MaxGermline_GnomAD_AF",
      "value": "0.01",
      "status": "PASS|WARNING|FAIL",
      "message": "Deterministic rule-based check result",
      "ruleReference": "FS-RULE-010"
    },
    {
      "parameter": "HasLOH_Flag",
      "value": "false",
      "status": "PASS|WARNING|FAIL",
      "message": "Deterministic rule-based check result",
      "ruleReference": "FS-RULE-011"
    },
    {
      "parameter": "HasClonalHematopoiesis_Flag",
      "value": "false",
      "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": "GermlineSomaticResultGateChecker.documentation.html"
  }
}

Traceability matrix

URS	FS	Test	Evidence
URS-001	FS-001, FS-002	OQ-001	Verify execution and import of valid input.csv.
URS-002	FS-005, FS-006	OQ-004	Repeat the same dataset and compare output.json.
URS-003	FS-003, FS-004, FS-010	OQ-002, OQ-003	Verify missing columns and invalid types.
URS-004	FS-005, FS-006	OQ-004, PQ-001	Verify critical deviations on real/boundary data.
URS-005	FS-007, FS-009	OQ-005	Verify JSON schema and downstream-system suitability.
URS-006	FS-008	OQ-006	Verify identifiers and audit metadata.
URS-007	FS-008, FS-010	IQ-001, OQ-007	Verify documentation completeness and control evidence.
URS-008	FS-005, FS-008	PQ-002	Verify review workflow and no replacement of QA decision.

IQ/OQ/PQ test scenarios

ID	Scenario	Expected result
IQ-001	Verify executable, input.csv, documentation and checksum availability.	Delivery set is complete; version is recorded.
OQ-001	Valid sample row from input.csv.	PASS or acceptable WARNING according to rules.
OQ-002	Remove a mandatory CSV column.	Schema error or FAIL with missing-column reference.
OQ-003	Place a non-numeric value into a numeric field.	Type-conversion error with row/field reference.
OQ-004	Set a critical parameter outside the limit.	FAIL and critical finding.
OQ-005	Verify output.json structure.	All mandatory sections are present and JSON is valid.
OQ-006	Verify batch/sample traceability.	Input and result identifiers match.
PQ-001	Verify 3–5 real user batches/samples.	Result is confirmed by QC/QA review.
PQ-002	Verify deviation workflow and manual QA decision.	Utility supports review but does not replace approved decision.

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.

Included in packages

Liquid Biopsy QC Suite

QC and pre-analytical control package for liquid biopsy workflows: cfDNA/ctDNA, CTC, EV/exosomes, methylation, NGS/qPCR/ddPCR, sample quality, contamination, sensitivity and reporting checks.

Open