Claude-skill-registry hrd-analysis-agent

name: hrd-analysis-agent

install
source · Clone the upstream repo
git clone https://github.com/majiayu000/claude-skill-registry
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/majiayu000/claude-skill-registry "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/data/hrd-analysis-agent" ~/.claude/skills/majiayu000-claude-skill-registry-hrd-analysis-agent && rm -rf "$T"
manifest: skills/data/hrd-analysis-agent/SKILL.md
source content

---name: hrd-analysis-agent description: AI-powered homologous recombination deficiency (HRD) analysis for PARP inhibitor response prediction using genomic scarring signatures and BRCA pathway assessment. license: MIT metadata: author: AI Group version: "1.0.0" created: "2026-01-19" compatibility:

  • system: Python 3.10+ allowed-tools:
  • run_shell_command
  • read_file
  • write_file

keywords:

  • hrd-analysis-agent
  • automation
  • biomedical measurable_outcome: execute task with >95% success rate. ---"

HRD Analysis Agent

The HRD Analysis Agent provides comprehensive analysis of homologous recombination deficiency for predicting response to PARP inhibitors and platinum chemotherapy. It integrates genomic scarring signatures (LOH, TAI, LST), BRCA1/2 status, and HRD gene pathway analysis.

When to Use This Skill

  • When determining HRD status for PARP inhibitor eligibility.
  • To calculate genomic instability scores (GIS) from tumor sequencing.
  • For analyzing BRCA1/2 and HRD gene mutations.
  • When predicting response to PARP inhibitors or platinum chemotherapy.
  • To identify "BRCAness" phenotype in BRCA wild-type tumors.

Core Capabilities

  1. Genomic Scar Scoring: Calculate LOH, TAI, and LST scores from copy number data.

  2. BRCA Pathway Analysis: Assess mutations in BRCA1, BRCA2, and 13 other HRD genes.

  3. HRD Classification: Determine HRD-positive vs. HRD-negative status.

  4. PARP Inhibitor Prediction: Predict response to olaparib, niraparib, rucaparib, talazoparib.

  5. Platinum Sensitivity: Predict platinum chemotherapy sensitivity.

  6. Reversion Detection: Identify BRCA reversion mutations restoring HR function.

HRD Scoring Components

ScoreDefinitionBiological Basis
LOHLoss of heterozygosity regions >15 MbGenomic scarring
TAITelomeric allelic imbalanceEnd-to-end fusions
LSTLarge-scale state transitionsBreak-induced repair
GISCombined LOH + TAI + LSTOverall HRD score

HRD-Positive Threshold: GIS ≥ 42 (Myriad myChoice) or equivalent

HRD Gene Panel

GeneFunctionHRD Contribution
BRCA1HR core componentMajor
BRCA2RAD51 loadingMajor
PALB2BRCA2 partnerModerate-Major
RAD51C/DHR mediatorsModerate
ATMDNA damage sensingModerate
CHEK2Cell cycle checkpointModerate
BARD1BRCA1 partnerModerate
BRIP1Fanconi pathwayModerate
CDK12TranscriptionVariable
RAD51BHR mediatorLow-Moderate

Workflow

  1. Input: Copy number segments, somatic mutations, germline variants.

  2. Scar Calculation: Compute LOH, TAI, LST from segmented CNV data.

  3. Gene Analysis: Assess pathogenic variants in HRD genes.

  4. Score Integration: Calculate composite GIS score.

  5. Classification: Determine HRD status.

  6. Reversion Check: Screen for reversion mutations.

  7. Output: HRD score, classification, gene mutations, treatment recommendations.

Example Usage

User: "Analyze HRD status for this ovarian cancer patient to guide PARP inhibitor selection."

Agent Action:

python3 Skills/Oncology/HRD_Analysis_Agent/hrd_analyzer.py \
    --cnv_segments tumor_segments.tsv \
    --mutations somatic_variants.maf \
    --germline germline_variants.vcf \
    --tumor_type ovarian \
    --purity 0.65 \
    --ploidy 2.1 \
    --output hrd_report.json

Commercial HRD Tests

TestComponentsThresholdFDA Status
myChoice CDxGIS + BRCA≥42 or BRCA+FDA approved
FoundationOneLOH≥16%FDA approved
SOPHiA DDM HRDGIS + BRCA≥42 or BRCA+CE-IVD

Clinical Indications

FDA-Approved PARP Inhibitor Indications:

  • Ovarian: HRD+ or BRCA+ (maintenance, later-line)
  • Breast: gBRCA+ (HER2-, metastatic)
  • Pancreatic: gBRCA+ (maintenance)
  • Prostate: HRR gene mutated (mCRPC)

Response Prediction

StatusPARP ResponsePlatinum Response
BRCA mutatedVery highHigh
HRD+ / BRCA WTHighModerate-High
HRD- / BRCA WTLimitedStandard
Reversion+PoorPoor

AI/ML Components

GIS Calculation:

  • ASCAT/FACETS for allele-specific CNV
  • HRDetect algorithm integration
  • ML refinement of thresholds

Reversion Detection:

  • Frameshift restoration analysis
  • Splice site reversion
  • Secondary deletion removing stop

Response Prediction:

  • Multi-feature model (GIS + genes + expression)
  • HRDetect signature scoring
  • Clinical outcome integration

Resistance Mechanisms

MechanismDetectionImplication
BRCA reversionSequencingAcquired resistance
53BP1 lossExpression/mutationRescued HR
ABCB1 upregulationExpressionDrug efflux
PARP1 lossExpressionTarget loss

Prerequisites

  • Python 3.10+
  • ASCAT/FACETS for CNV
  • HRDetect implementation
  • Germline/somatic variant callers

Related Skills

  • Variant_Interpretation - For BRCA classification
  • Liquid_Biopsy_Analytics_Agent - For ctDNA HRD monitoring
  • Pan_Cancer_MultiOmics_Agent - For multi-omic context

Special Considerations

  1. Tumor Purity: Low purity affects scar detection
  2. Prior Therapy: Platinum may select resistant clones
  3. Germline Testing: Important for family counseling
  4. Reversion Monitoring: Serial testing recommended

Author

AI Group - Biomedical AI Platform