FragmentomicsQcChecker

Fragmentomics QC

Liquid Biopsy жидкостная биопсия cfDNA ctDNA CTC exosomes NGS qPCR

Utility description: Fragmentomics QC

Fragmentomics QC Checker — cfDNA Fragmentomics Data Quality Control

ℹ️ Utility performs comprehensive fragmentomics data quality verification according to FragmenTech standards and cfDNA epigenomics guidelines:
• Insert Size Profile: Median insert size and nucleosomal peak height (~167 bp) — foundation of fragmentomic signal.
• Short Fragment Ratio: Ratio of short (<150 bp) to long fragments — tumor DNA marker.
• Library Artifacts: Control of adapter dimers and overtrimming — primary sources of technical bias.
• Library Complexity: Number of unique molecules — determines statistical power of analysis.
• Motif Coverage: Sequencing depth for end-motif analysis — requires ≥10× for reliable detection.

⚠️ IMPORTANT:
• Overtrimming artificially shortens fragments and mimics tumor signal.
• Adapter dimers (>2%) contaminate data and reduce effective depth.
• Weak nucleosomal peak indicates sample degradation or library prep issues.
• Motif analysis requires significantly greater depth than standard variant calling.

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

Input format:
SampleID,LibraryPrepMethod,MedianInsertSize_bp,ExpectedMedianInsert_bp,InsertSizeTolerance_bp,ShortFragmentRatio,MinShortFragmentRatio,MaxShortFragmentRatio,NucleosomalPeakHeight,MinNucleosomalPeakHeight,AdapterDimer_Percent,MaxAdapterDimer_Percent,UniqueMolecules_Million,MinUniqueMolecules_Million,MotifCoverage_X,MinMotifCoverage_X,BackgroundNoise_Score,MaxBackgroundNoise,OvertrimmingDetected

Example:
FRAG-001,WGS,168,167,15,0.28,0.15,0.45,5.2,3.0,0.3,2.0,18.5,5.0,25.0,10.0,0.08,0.2,false

📍 Scope of Application (Usage Where):
• Liquid Biopsy Research: QC before cancer fragmentomic analysis.
• Non-Invasive Prenatal Testing (NIPT): Fetal DNA quality assessment by fragmentation.
• MCED Test Development: Validation of fragmentomic features.
• Transplant Monitoring: Donor cfDNA detection by size.

— WHY IS THIS NEEDED?
cfDNA fragmentation is a subtle biological signal easily masked by technical artifacts.
Without strict QC, true tumor fragment shortening cannot be distinguished from overtrimming.
Automated verification guarantees that fragmentomic conclusions are based on quality data.

⚠️ CRITICAL:
• Median Insert 152-182 bp: Outside this range — sample or library issue.
• Nucleosomal Peak ≥3.0: Weak peak = loss of nucleosome positioning.
• Adapter Dimer ≤2%: Above this level, library re-cleanup required.
• Overtrimming = FAIL: Data irreversibly distorted, re-preparation mandatory.
• Motif Coverage ≥10×: Below this threshold, end-motif analysis is statistically unreliable.

Key features:
• Eight-parameter fragmentomics data assessment
• Automatic overtrimming detection
• Integration of physical and bioinformatic metrics
• PASS / WARNING / FAIL classification
• Compliance with FragmenTech consortium standards

Critical parameters:
• Median Insert Size: 152–182 bp
• Nucleosomal Peak Height: ≥ 3.0
• Adapter Dimer: ≤ 2%
• Short Fragment Ratio: 0.15–0.45
• Unique Molecules: ≥ 5M
• Motif Coverage: ≥ 10×
• Overtrimming: Not detected

💡 Usage tips:
1. Trimming: Use conservative trimming parameters; avoid aggressive adapter removal.
2. Size Selection: Apply double SPRI to remove dimers and long fragments.
3. UMI: Always use UMIs for accurate unique molecule counting.
4. Controls: Include reference samples with known fragmentation profile.
5. Trends: Monitor median insert size over time for protocol drift detection.

⚠️ Note: This utility assesses technical quality of fragmentomics data. It does not replace biological interpretation but guarantees that observed patterns reflect biology, not artifacts.

input.csv

SampleID,LibraryPrepMethod,MedianInsertSize_bp,ExpectedMedianInsert_bp,InsertSizeTolerance_bp,ShortFragmentRatio,MinShortFragmentRatio,MaxShortFragmentRatio,NucleosomalPeakHeight,MinNucleosomalPeakHeight,AdapterDimer_Percent,MaxAdapterDimer_Percent,UniqueMolecules_Million,MinUniqueMolecules_Million,MotifCoverage_X,MinMotifCoverage_X,BackgroundNoise_Score,MaxBackgroundNoise,OvertrimmingDetected
FRAG-2026-001,WGS,168,167,15,0.28,0.15,0.45,5.2,3.0,0.3,2.0,18.5,5.0,25.0,10.0,0.08,0.2,false
FRAG-2026-002,Targeted,142,167,15,0.62,0.15,0.45,1.8,3.0,8.5,2.0,2.1,5.0,4.0,10.0,0.35,0.2,true
FRAG-2026-003,WGS,170,167,15,0.32,0.15,0.45,4.8,3.0,0.5,2.0,15.2,5.0,22.0,10.0,0.12,0.2,false

URS & FS — User Requirements and Functional Specification

This document describes the controlled interface and behaviour of FragmentomicsQcChecker for Fragmentomics QC 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.

• Short Fragment Ratio: Ratio of short (<150 bp) to long fragments — tumor DNA marker.
• Motif Coverage: Sequencing depth for end-motif analysis — requires ≥10× for reliable detection.
• Adapter dimers (>2%) contaminate data and reduce effective depth.
⚠️ CRITICAL:
• Nucleosomal Peak ≥3.0: Weak peak = loss of nucleosome positioning.
• Adapter Dimer ≤2%: Above this level, library re-cleanup required.
• Motif Coverage ≥10×: Below this threshold, end-motif analysis is statistically unreliable.
Critical parameters:
• Nucleosomal Peak Height: ≥ 3.0
• Adapter Dimer: ≤ 2%
• Unique Molecules: ≥ 5M
• Motif Coverage: ≥ 10×

URS — User Requirements Specification

ID	Requirement	Criticality	Acceptance criterion
URS-001	The utility shall accept an input.csv file for Fragmentomics QC 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	`SampleID`	string / controlled vocabulary	`FRAG-2026-001`	Sample or laboratory specimen identifier.
2	`LibraryPrepMethod`	string / controlled vocabulary	`WGS`	Method or process approach; controlled reference value.
3	`MedianInsertSize_bp`	decimal	`168`	Controlled input parameter for deterministic QC rules.
4	`ExpectedMedianInsert_bp`	decimal	`167`	Controlled input parameter for deterministic QC rules.
5	`InsertSizeTolerance_bp`	decimal	`15`	Controlled input parameter for deterministic QC rules.
6	`ShortFragmentRatio`	decimal	`0.28`	Component ratio; structural or formulation CQA.
7	`MinShortFragmentRatio`	decimal	`0.15`	Component ratio; structural or formulation CQA.
8	`MaxShortFragmentRatio`	decimal	`0.45`	Component ratio; structural or formulation CQA.
9	`NucleosomalPeakHeight`	decimal	`5.2`	Controlled input parameter for deterministic QC rules.
10	`MinNucleosomalPeakHeight`	decimal	`3.0`	Controlled input parameter for deterministic QC rules.
11	`AdapterDimer_Percent`	decimal	`0.3`	Controlled input parameter for deterministic QC rules.
12	`MaxAdapterDimer_Percent`	decimal	`2.0`	Controlled input parameter for deterministic QC rules.
13	`UniqueMolecules_Million`	integer / decimal	`18.5`	Controlled input parameter for deterministic QC rules.
14	`MinUniqueMolecules_Million`	integer / decimal	`5.0`	Controlled input parameter for deterministic QC rules.
15	`MotifCoverage_X`	decimal	`25.0`	Controlled input parameter for deterministic QC rules.
16	`MinMotifCoverage_X`	decimal	`10.0`	Controlled input parameter for deterministic QC rules.
17	`BackgroundNoise_Score`	decimal	`0.08`	Controlled input parameter for deterministic QC rules.
18	`MaxBackgroundNoise`	decimal	`0.2`	Controlled input parameter for deterministic QC rules.
19	`OvertrimmingDetected`	string / controlled vocabulary	`false`	Controlled input parameter for deterministic QC rules.

SampleID,LibraryPrepMethod,MedianInsertSize_bp,ExpectedMedianInsert_bp,InsertSizeTolerance_bp,ShortFragmentRatio,MinShortFragmentRatio,MaxShortFragmentRatio,NucleosomalPeakHeight,MinNucleosomalPeakHeight,AdapterDimer_Percent,MaxAdapterDimer_Percent,UniqueMolecules_Million,MinUniqueMolecules_Million,MotifCoverage_X,MinMotifCoverage_X,BackgroundNoise_Score,MaxBackgroundNoise,OvertrimmingDetected
FRAG-2026-001,WGS,168,167,15,0.28,0.15,0.45,5.2,3.0,0.3,2.0,18.5,5.0,25.0,10.0,0.08,0.2,false
FRAG-2026-002,Targeted,142,167,15,0.62,0.15,0.45,1.8,3.0,8.5,2.0,2.1,5.0,4.0,10.0,0.35,0.2,true
FRAG-2026-003,WGS,170,167,15,0.32,0.15,0.45,4.8,3.0,0.5,2.0,15.2,5.0,22.0,10.0,0.12,0.2,false

Input validation rules

ID	Field	Rule	Criticality
VR-001	`SampleID`	The field shall match an approved dictionary or accepted string representation.	High
VR-002	`LibraryPrepMethod`	The field shall match an approved dictionary or accepted string representation.	High
VR-003	`MedianInsertSize_bp`	The field shall match an approved dictionary or accepted string representation.	High
VR-004	`ExpectedMedianInsert_bp`	The field shall match an approved dictionary or accepted string representation.	Medium
VR-005	`InsertSizeTolerance_bp`	The field shall match an approved dictionary or accepted string representation.	Medium
VR-006	`ShortFragmentRatio`	The field shall match an approved dictionary or accepted string representation.	Medium
VR-007	`MinShortFragmentRatio`	The field shall match an approved dictionary or accepted string representation.	Medium
VR-008	`MaxShortFragmentRatio`	The field shall match an approved dictionary or accepted string representation.	Medium
VR-009	`NucleosomalPeakHeight`	The field shall match an approved dictionary or accepted string representation.	Medium
VR-010	`MinNucleosomalPeakHeight`	The field shall match an approved dictionary or accepted string representation.	Medium
VR-011	`AdapterDimer_Percent`	The field shall match an approved dictionary or accepted string representation.	Medium
VR-012	`MaxAdapterDimer_Percent`	The field shall match an approved dictionary or accepted string representation.	Medium
VR-013	`UniqueMolecules_Million`	The field shall match an approved dictionary or accepted string representation.	Medium
VR-014	`MinUniqueMolecules_Million`	The field shall match an approved dictionary or accepted string representation.	Medium
VR-015	`MotifCoverage_X`	The field shall match an approved dictionary or accepted string representation.	Medium
VR-016	`MinMotifCoverage_X`	The field shall match an approved dictionary or accepted string representation.	Medium
VR-017	`BackgroundNoise_Score`	The field shall match an approved dictionary or accepted string representation.	Medium
VR-018	`MaxBackgroundNoise`	The field shall match an approved dictionary or accepted string representation.	Medium
VR-019	`OvertrimmingDetected`	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 Fragmentomics QC 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": "fragmentomicsqcchecker",
  "utilityFolder": "FragmentomicsQcChecker",
  "package": "LiquidBiopsy",
  "overallStatus": "PASS|WARNING|FAIL",
  "sourceFile": "input.csv",
  "processedAtUtc": "2026-06-10T00:00:00Z",
  "checks": [
    {
      "parameter": "SampleID",
      "value": "FRAG-2026-001",
      "status": "PASS|WARNING|FAIL",
      "message": "Deterministic rule-based check result",
      "ruleReference": "FS-RULE-001"
    },
    {
      "parameter": "LibraryPrepMethod",
      "value": "WGS",
      "status": "PASS|WARNING|FAIL",
      "message": "Deterministic rule-based check result",
      "ruleReference": "FS-RULE-002"
    },
    {
      "parameter": "MedianInsertSize_bp",
      "value": "168",
      "status": "PASS|WARNING|FAIL",
      "message": "Deterministic rule-based check result",
      "ruleReference": "FS-RULE-003"
    },
    {
      "parameter": "ExpectedMedianInsert_bp",
      "value": "167",
      "status": "PASS|WARNING|FAIL",
      "message": "Deterministic rule-based check result",
      "ruleReference": "FS-RULE-004"
    },
    {
      "parameter": "InsertSizeTolerance_bp",
      "value": "15",
      "status": "PASS|WARNING|FAIL",
      "message": "Deterministic rule-based check result",
      "ruleReference": "FS-RULE-005"
    },
    {
      "parameter": "ShortFragmentRatio",
      "value": "0.28",
      "status": "PASS|WARNING|FAIL",
      "message": "Deterministic rule-based check result",
      "ruleReference": "FS-RULE-006"
    },
    {
      "parameter": "MinShortFragmentRatio",
      "value": "0.15",
      "status": "PASS|WARNING|FAIL",
      "message": "Deterministic rule-based check result",
      "ruleReference": "FS-RULE-007"
    },
    {
      "parameter": "MaxShortFragmentRatio",
      "value": "0.45",
      "status": "PASS|WARNING|FAIL",
      "message": "Deterministic rule-based check result",
      "ruleReference": "FS-RULE-008"
    },
    {
      "parameter": "NucleosomalPeakHeight",
      "value": "5.2",
      "status": "PASS|WARNING|FAIL",
      "message": "Deterministic rule-based check result",
      "ruleReference": "FS-RULE-009"
    },
    {
      "parameter": "MinNucleosomalPeakHeight",
      "value": "3.0",
      "status": "PASS|WARNING|FAIL",
      "message": "Deterministic rule-based check result",
      "ruleReference": "FS-RULE-010"
    },
    {
      "parameter": "AdapterDimer_Percent",
      "value": "0.3",
      "status": "PASS|WARNING|FAIL",
      "message": "Deterministic rule-based check result",
      "ruleReference": "FS-RULE-011"
    },
    {
      "parameter": "MaxAdapterDimer_Percent",
      "value": "2.0",
      "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": "FragmentomicsQcChecker.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