ClonotypeTrackingChecker

Clonotype Tracking

Liquid Biopsy жидкостная биопсия cfDNA ctDNA CTC exosomes NGS qPCR

Utility description: Clonotype Tracking

Clonotype Tracking Checker — Longitudinal Clonotype Tracking

ℹ️ Utility performs analysis of T- and B-cell clonotype dynamics over time according to AIRR Community standards and immune monitoring requirements:
• Clonotype Identification: Unique identification by CDR3 sequence and V/J genes.
• Fold Change Analysis: Calculation of frequency change magnitude relative to baseline.
• Significance Assessment: Classification into EXPANDED / CONTRACTED / TRACKED based on fold change threshold.
• Read Support Control: Filtering of false-positive expansions with insufficient sequencing depth.

⚠️ IMPORTANT:
• Clonotype expansion without sufficient reads may be PCR bias artifact.
• Longitudinal analysis requires strict normalization between timepoints.

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

Input format:
PatientID,Timepoint,ClonotypeID,ReceptorType,CDR3_Sequence,V_Gene,J_Gene,Frequency_Percent,ReadCount,TotalReads_InSample,Baseline_Frequency_Percent,FoldChange_Threshold,Min_Read_Count

Example:
PAT-001,Week12,CLN-A1,TCR-beta,CASSLAGTDTQYF,TRBV20-1,TRBJ2-3,1.20,1200,100000,0.05,2.0,10

📍 Scope of Application (Usage Where):
• Immuno-oncology: Monitoring response to checkpoint inhibitors and CAR-T therapy.
• Vaccinology: Assessment of antigen-specific T-cell response.
• Autoimmune Diseases: Tracking pathogenic clones.
• Transplantology: Monitoring alloreactivity and GVHD.

— WHY IS THIS NEEDED?
Immune repertoire is dynamic, and single snapshot does not reflect functional response.
Only longitudinal tracking allows distinguishing true antigen-specific expansion from stochastic fluctuations.
Automated tracking eliminates subjectivity of manual interpretation of thousands of clonotypes.

⚠️ CRITICAL:
• Read Threshold: Clones with <10 reads are unreliable for quantitative comparison.
• Fold Change Threshold: Typically ≥2x for significant expansion, but depends on depth.
• Normalization: Frequencies must be normalized to total productive reads.
• CDR3 Definition: Use strict clonotype definition (CDR3aa + V + J).

Key features:
• Automatic fold change calculation across all timepoints
• Dynamics classification (Expanded/Contracted/Stable)
• Read count quality control
• Support for TCR and BCR repertoires
• Compliance with AIRR-seq standards

Critical parameters:
• Fold Change: ≥ Threshold for expansion
• Read Count: ≥ Min Read Count
• Frequency: Normalized frequency (%)
• CDR3+VJ: Unique clonotype identifier

💡 Usage tips:
1. Sequencing Depth: Aim for >100K productive reads per sample.
2. UMI: Use UMIs to eliminate PCR duplicates and enable accurate molecule counting.
3. Baseline: Always include pre-treatment sample as reference.
4. Multiple Testing: Apply FDR correction when analyzing thousands of clonotypes.
5. Visualization: Complement report with ridge plots or streamgraphs for clarity.

⚠️ Note: This utility is a quantitative immune repertoire analysis tool. It does not replace functional clone characterization (tetramer staining, ELISPOT) but prioritizes candidates for further validation.

input.csv

PatientID,Timepoint,ClonotypeID,ReceptorType,CDR3_Sequence,V_Gene,J_Gene,Frequency_Percent,ReadCount,TotalReads_InSample,Baseline_Frequency_Percent,FoldChange_Threshold,Min_Read_Count
PAT-001,Baseline,CLN-A1,TCR-beta,CASSLAGTDTQYF,TRBV20-1,TRBJ2-3,0.05,50,100000,0.05,2.0,10
PAT-001,Week4,CLN-A1,TCR-beta,CASSLAGTDTQYF,TRBV20-1,TRBJ2-3,0.45,450,100000,0.05,2.0,10
PAT-001,Week12,CLN-A1,TCR-beta,CASSLAGTDTQYF,TRBV20-1,TRBJ2-3,1.20,1200,100000,0.05,2.0,10
PAT-001,Baseline,CLN-B2,TCR-beta,CSARDRGNNQPQHF,TRBV5-1,TRBJ1-5,0.10,100,100000,0.10,2.0,10
PAT-001,Week12,CLN-B2,TCR-beta,CSARDRGNNQPQHF,TRBV5-1,TRBJ1-5,0.12,120,100000,0.10,2.0,10

URS & FS — User Requirements and Functional Specification

This document describes the controlled interface and behaviour of ClonotypeTrackingChecker for Clonotype Tracking 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.

⚠️ CRITICAL:
• Read Threshold: Clones with <10 reads are unreliable for quantitative comparison.
• Fold Change Threshold: Typically ≥2x for significant expansion, but depends on depth.
• Normalization: Frequencies must be normalized to total productive reads.
Critical parameters:
• Fold Change: ≥ Threshold for expansion
• Read Count: ≥ Min Read Count
1. Sequencing Depth: Aim for >100K productive reads per sample.

URS — User Requirements Specification

ID	Requirement	Criticality	Acceptance criterion
URS-001	The utility shall accept an input.csv file for Clonotype Tracking 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-001`	Controlled input parameter for deterministic QC rules.
2	`Timepoint`	string / controlled vocabulary	`Baseline`	Time parameter for process, incubation, storage or analytical workflow.
3	`ClonotypeID`	string / controlled vocabulary	`CLN-A1`	Controlled input parameter for deterministic QC rules.
4	`ReceptorType`	string / controlled vocabulary	`TCR-beta`	Controlled input parameter for deterministic QC rules.
5	`CDR3_Sequence`	string / controlled vocabulary	`CASSLAGTDTQYF`	Controlled input parameter for deterministic QC rules.
6	`V_Gene`	string / controlled vocabulary	`TRBV20-1`	Controlled input parameter for deterministic QC rules.
7	`J_Gene`	string / controlled vocabulary	`TRBJ2-3`	Controlled input parameter for deterministic QC rules.
8	`Frequency_Percent`	decimal	`0.05`	Controlled input parameter for deterministic QC rules.
9	`ReadCount`	integer / decimal	`50`	Count parameter used for microbiological, particulate or cellular control.
10	`TotalReads_InSample`	string / controlled vocabulary	`100000`	Sample or laboratory specimen identifier.
11	`Baseline_Frequency_Percent`	decimal	`0.05`	Controlled input parameter for deterministic QC rules.
12	`FoldChange_Threshold`	decimal	`2.0`	Controlled input parameter for deterministic QC rules.
13	`Min_Read_Count`	integer / decimal	`10`	Count parameter used for microbiological, particulate or cellular control.

PatientID,Timepoint,ClonotypeID,ReceptorType,CDR3_Sequence,V_Gene,J_Gene,Frequency_Percent,ReadCount,TotalReads_InSample,Baseline_Frequency_Percent,FoldChange_Threshold,Min_Read_Count
PAT-001,Baseline,CLN-A1,TCR-beta,CASSLAGTDTQYF,TRBV20-1,TRBJ2-3,0.05,50,100000,0.05,2.0,10
PAT-001,Week4,CLN-A1,TCR-beta,CASSLAGTDTQYF,TRBV20-1,TRBJ2-3,0.45,450,100000,0.05,2.0,10
PAT-001,Week12,CLN-A1,TCR-beta,CASSLAGTDTQYF,TRBV20-1,TRBJ2-3,1.20,1200,100000,0.05,2.0,10

Input validation rules

ID	Field	Rule	Criticality
VR-001	`PatientID`	The field shall match an approved dictionary or accepted string representation.	High
VR-002	`Timepoint`	The field shall match an approved dictionary or accepted string representation.	High
VR-003	`ClonotypeID`	The field shall match an approved dictionary or accepted string representation.	High
VR-004	`ReceptorType`	The field shall match an approved dictionary or accepted string representation.	Medium
VR-005	`CDR3_Sequence`	The field shall match an approved dictionary or accepted string representation.	Medium
VR-006	`V_Gene`	The field shall match an approved dictionary or accepted string representation.	Medium
VR-007	`J_Gene`	The field shall match an approved dictionary or accepted string representation.	Medium
VR-008	`Frequency_Percent`	The field shall match an approved dictionary or accepted string representation.	Medium
VR-009	`ReadCount`	The field shall match an approved dictionary or accepted string representation.	Medium
VR-010	`TotalReads_InSample`	The field shall match an approved dictionary or accepted string representation.	Medium
VR-011	`Baseline_Frequency_Percent`	The field shall match an approved dictionary or accepted string representation.	Medium
VR-012	`FoldChange_Threshold`	The field shall match an approved dictionary or accepted string representation.	Medium
VR-013	`Min_Read_Count`	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 Clonotype Tracking 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": "clonotypetrackingchecker",
  "utilityFolder": "ClonotypeTrackingChecker",
  "package": "LiquidBiopsy",
  "overallStatus": "PASS|WARNING|FAIL",
  "sourceFile": "input.csv",
  "processedAtUtc": "2026-06-10T00:00:00Z",
  "checks": [
    {
      "parameter": "PatientID",
      "value": "PAT-001",
      "status": "PASS|WARNING|FAIL",
      "message": "Deterministic rule-based check result",
      "ruleReference": "FS-RULE-001"
    },
    {
      "parameter": "Timepoint",
      "value": "Baseline",
      "status": "PASS|WARNING|FAIL",
      "message": "Deterministic rule-based check result",
      "ruleReference": "FS-RULE-002"
    },
    {
      "parameter": "ClonotypeID",
      "value": "CLN-A1",
      "status": "PASS|WARNING|FAIL",
      "message": "Deterministic rule-based check result",
      "ruleReference": "FS-RULE-003"
    },
    {
      "parameter": "ReceptorType",
      "value": "TCR-beta",
      "status": "PASS|WARNING|FAIL",
      "message": "Deterministic rule-based check result",
      "ruleReference": "FS-RULE-004"
    },
    {
      "parameter": "CDR3_Sequence",
      "value": "CASSLAGTDTQYF",
      "status": "PASS|WARNING|FAIL",
      "message": "Deterministic rule-based check result",
      "ruleReference": "FS-RULE-005"
    },
    {
      "parameter": "V_Gene",
      "value": "TRBV20-1",
      "status": "PASS|WARNING|FAIL",
      "message": "Deterministic rule-based check result",
      "ruleReference": "FS-RULE-006"
    },
    {
      "parameter": "J_Gene",
      "value": "TRBJ2-3",
      "status": "PASS|WARNING|FAIL",
      "message": "Deterministic rule-based check result",
      "ruleReference": "FS-RULE-007"
    },
    {
      "parameter": "Frequency_Percent",
      "value": "0.05",
      "status": "PASS|WARNING|FAIL",
      "message": "Deterministic rule-based check result",
      "ruleReference": "FS-RULE-008"
    },
    {
      "parameter": "ReadCount",
      "value": "50",
      "status": "PASS|WARNING|FAIL",
      "message": "Deterministic rule-based check result",
      "ruleReference": "FS-RULE-009"
    },
    {
      "parameter": "TotalReads_InSample",
      "value": "100000",
      "status": "PASS|WARNING|FAIL",
      "message": "Deterministic rule-based check result",
      "ruleReference": "FS-RULE-010"
    },
    {
      "parameter": "Baseline_Frequency_Percent",
      "value": "0.05",
      "status": "PASS|WARNING|FAIL",
      "message": "Deterministic rule-based check result",
      "ruleReference": "FS-RULE-011"
    },
    {
      "parameter": "FoldChange_Threshold",
      "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": "ClonotypeTrackingChecker.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