🔬 TRACK 15 • 12 MODULAR CHAPTERS CLINICAL NGS • MOLECULAR PATHOLOGY GALAXY PIPELINES • AMP/ASCO/CAP TIERS • MTB

Medical Oncology • Surgical Pathology • Clinical Bioinformatics • Translational Cancer Biology

Precision Cancer Genomics: From Biopsy to Molecular Tumor Board

End-to-End Clinical NGS Workflow: Assay Design, Galaxy Bioinformatic Pipelines, AMP/ASCO/CAP Tiering & Real-World Patient Cases (Lung, Colon, Breast).

Master the complete translational pipeline from clinical specimen handling (FFPE, fresh-frozen, liquid biopsy cfDNA) to actionable clinical decision-making. Learn directly from the combined perspectives of a Wet-Lab Specialist (library QC, hybrid-capture panels, UMI de-duplication), a Bioinformatician (Galaxy somatic pipelines, Mutect2, Panel of Normals, IGV artifact curation), and a Clinical Geneticist (AMP/ASCO/CAP 2017 Tiers I–IV, OncoKB, CIViC, clinical trial matching, and multidisciplinary tumor board reporting).

📦 Production Somatic NGS & Variant Interpretation Stack GATK4 / Mutect2 / BWA / VEP / IGV

# Install Somatic Variant Calling & Clinical Annotation Environment
conda create -n cancer_ngs -c bioconda -c conda-forge gatk4 bwa samtools picard snpeff vep -y
conda activate cancer_ngs

Start Chapter 01 → Explore 12 Modules ↓ Curriculum Roadmap ↓

Curriculum Specifications Track 15

Format & Duration

Self-Paced / Guided • 12 Modular Chapters

Diagnostic Assays

Hybrid-Capture • CGP Panels • cfDNA Liquid Biopsy

Somatic Pipelines

BWA-MEM • GATK4 Mutect2 • PoN • Galaxy GUI

Clinical Tiering

AMP/ASCO/CAP 2017 Tiers I–IV • OncoKB • CIViC

Tumor Board Benchmarks

NSCLC (EGFR/MET) • CRC (KRAS/BRAF) • Breast (BRCA/HRD)

Academic Access

100% Free & Open Access

View 12 Modules ↓

🔬 View 12 Modules Curriculum ↗

🩺 Three Comprehensive Molecular Tumor Board (MTB) Patient Cases

Phase 4 Clinical Translation

Case 1 • Thoracic Oncology

Stage IV Non-Small Cell Lung Cancer

Primary EGFR exon 19 deletion, acquired resistance on Osimertinib via EGFR C797S and MET focal gene amplification, plus cfDNA monitoring for residual disease.

Case 2 • Gastrointestinal Oncology

Metastatic Colorectal Adenocarcinoma

Assessing KRAS / NRAS / BRAF V600E mutational status, MLH1 promoter hypermethylation with Microsatellite Instability-High (MSI-H), and Pembrolizumab immunotherapy triage.

Case 3 • Breast & Gynecologic Oncology

High-Grade Metastatic Breast Cancer

Clonal TP53 missense, deleterious germline/somatic BRCA1 frameshift with high HRD genomic instability score (PARP inhibitor eligibility), and focal ERBB2 (HER2) amplification.

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Who Should Attend

🩺

Medical Oncologists & Fellows Interpreting comprehensive genomic profiling (CGP) reports, targeted off-label therapies, and clinical trial options.

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Molecular Pathologists & Lab Directors Optimizing FFPE tissue extraction, hybrid-capture bait design, liquid biopsy cfDNA limits, and CLIA/CAP compliance.

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Clinical Bioinformaticians Implementing somatic mutation callers (Mutect2, VarDict), custom Panel of Normals (PoN), and artifact filtering.

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Cancer Genomics PhD Scholars Mastering clinical variant classification, OncoKB, CIViC, and multidisciplinary Molecular Tumor Board reporting.

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Learning Outcomes

Select optimal clinical NGS assays: hotspot panels vs CGP vs cfDNA liquid biopsy.
Evaluate wet-lab library QC metrics: FFPE deamination, fragment size, uniformity, and UMI deduplication.
Execute end-to-end somatic pipelines with BWA-MEM, Picard, and GATK4 Mutect2 using a Panel of Normals.
Inspect real somatic hotspot alignments (EGFR, KRAS, TP53) and filter sequencing artifacts in IGV.
Annotate and stratify somatic variants according to 2017 AMP/ASCO/CAP consensus Tiers I–IV.
Formulate actionable Molecular Tumor Board consensus reports across real-world Lung, Colon, and Breast patient cases.

🔬 4-PHASE CURRICULUM ARCHITECTURE

Precision Cancer Genomics Roadmap & Benchmarks

Self-paced, hands-on masterclass curriculum structured into 4 foundational phases with production command-line recipes and clinical oncology BAM/VCF benchmarks.

PHASE 1

Assay Strategy & Lab Workflow

Modules 01–03 • CGP, FFPE QC & Pan-Cancer Biomarkers

Diagnostic cancer testing: targeted panels vs CGP vs cfDNA
Somatic vs germline alterations & actionable drivers
Amplicon vs hybrid-capture chemistry & FFPE artifacts
Library QC metrics: Q-scores, insert size, uniformity
Pan-cancer biomarkers: TMB, MSI, VAF, CNV & LOH

PHASE 2

Data Processing & IGV Curation

Modules 04–06 • Formats, Mutect2 & Hotspots

Anatomy of raw sequencing formats: FASTQ Phred+33
Coordinate-sorted BAM flags & VCF 4.2 architecture
GATK Mutect2 architecture & Panel of Normals (PoN)
Filtering low-VAF mutations & FFPE deamination
IGV manual curation: EGFR, KRAS, TP53 hotspots

PHASE 3

Galaxy Somatic Pipeline

Modules 07–09 • BWA-MEM, Filtering & VEP

End-to-end Galaxy pipeline execution from FASTQ to BAM
BWA-MEM paired-end alignment & Picard MarkDuplicates
Somatic calling with Mutect2 & FilterMutectCalls
Variant annotation with Ensembl VEP & SnpEff
COSMIC and ClinVar database integration

PHASE 4

Clinical Tiers & Tumor Board

Modules 10–12 • AMP/ASCO/CAP & Patient Reports

2017 AMP/ASCO/CAP clinical tiering (Tiers I–IV)
OncoKB & CIViC levels of evidence
Complex biomarkers: gene fusions, amplifications, TMB
Molecular Tumor Board case studies (Lung, Colon, Breast)
Clinical reporting standards & therapeutic recommendations

COURSE CURRICULUM

12 Comprehensive Modular Chapters

All modules include Galaxy somatic recipes, Mutect2 command lines, and clinical BAM/VCF benchmarks

MODULE 01 Phase 1: Assays & Lab QC

Module 1: Clinical Cancer NGS & Assay Strategy: Targeted Panels, CGP, WES & Liquid Biopsy

Evolution of diagnostic cancer testing from single-gene assays to Comprehensive Genomic Profiling (CGP) and cell-free DNA (cfDNA) liquid biopsies, somatic vs germline concepts, and driver vs actionable alterations.

🎯 Key Deliverables:

Clinical NGS assay selection flowchart & 10-gene lung panel design
FFPE deamination artifact mitigation & pan-cancer biomarker table

CGP Panels Hybrid Capture FFPE QC UMI Liquid Biopsy

Explore Chapter 01 →

MODULE 02 Phase 1: Assays & Lab QC

Module 2: Wet-Lab Quality Control, Library Metrics & Oncology Panel Design

Amplicon vs hybrid-capture chemistry, FFPE deamination artifacts, library preparation QC metrics (Q-scores, insert size, uniformity), and designing an oncology 10-gene panel.

🎯 Key Deliverables:

Clinical NGS assay selection flowchart & 10-gene lung panel design
FFPE deamination artifact mitigation & pan-cancer biomarker table

CGP Panels Hybrid Capture FFPE QC UMI Liquid Biopsy

Explore Chapter 02 →

MODULE 03 Phase 1: Assays & Lab QC

Module 3: Pan-Cancer Biomarkers: TMB, MSI, VAF, CNV & Loss of Heterozygosity

Mathematical and clinical definitions of Tumor Mutational Burden (TMB), Microsatellite Instability (MSI), Variant Allele Fraction (VAF), Copy Number Alterations (CNV), and Loss of Heterozygosity (LOH).

🎯 Key Deliverables:

Clinical NGS assay selection flowchart & 10-gene lung panel design
FFPE deamination artifact mitigation & pan-cancer biomarker table

CGP Panels Hybrid Capture FFPE QC UMI Liquid Biopsy

Explore Chapter 03 →

MODULE 04 Phase 2: Mutect2 & IGV

Module 4: Oncology File Formats, Phred Scores & Alignment Concepts: FASTQ, BAM & VCF

Anatomy of raw sequencing formats (FASTQ Phred+33), coordinate-sorted BAM/CRAM alignment flags, VCF 4.2 architecture, INFO and FORMAT field parsing, and quality metrics.

🎯 Key Deliverables:

Custom Panel of Normals (PoN) recipe & low-VAF somatic filter script
IGV manual curation guide for EGFR, KRAS, and TP53 cancer hotspots

BWA-MEM GATK Mutect2 PoN IGV Browser Phred+33

Explore Chapter 04 →

MODULE 05 Phase 2: Mutect2 & IGV

Module 5: Somatic Variant Calling Paradigms: Mutect2, Panel of Normals & Low-VAF Detection

Tumor-normal paired vs tumor-only calling, GATK Mutect2 architecture, generating a Panel of Normals (PoN), filtering FFPE deamination, and detecting low-VAF subclonal mutations.

🎯 Key Deliverables:

Custom Panel of Normals (PoN) recipe & low-VAF somatic filter script
IGV manual curation guide for EGFR, KRAS, and TP53 cancer hotspots

BWA-MEM GATK Mutect2 PoN IGV Browser Phred+33

Explore Chapter 05 →

MODULE 06 Phase 2: Mutect2 & IGV

Module 6: Read-Level Verification & Visualizing Somatic Hotspots in IGV

Navigating BAM alignments in the Integrative Genomics Viewer (IGV), inspecting diagnostic cancer hotspots (EGFR L858R, KRAS G13D, TP53), and identifying alignment red flags.

🎯 Key Deliverables:

Custom Panel of Normals (PoN) recipe & low-VAF somatic filter script
IGV manual curation guide for EGFR, KRAS, and TP53 cancer hotspots

BWA-MEM GATK Mutect2 PoN IGV Browser Phred+33

Explore Chapter 06 →

MODULE 07 Phase 3: Galaxy Pipelines

Module 7: Hands-On Somatic Pipeline Execution: FastQC, BWA-MEM & Picard Deduplication

Step-by-step guided execution of an end-to-end somatic bioinformatics pipeline in Galaxy: quality trimming with fastp, BWA-MEM alignment, and Picard MarkDuplicates.

🎯 Key Deliverables:

Reproducible Galaxy workflow from raw FASTQ to filtered somatic BAM
Comprehensive VEP & SnpEff functional annotation matrix

Galaxy GUI Picard MarkDup FilterMutectCalls Ensembl VEP COSMIC

Explore Chapter 07 →

MODULE 08 Phase 3: Galaxy Pipelines

Module 8: Somatic Mutation Discovery: GATK Mutect2 & FilterMutectCalls

Executing Mutect2 on target capture BED regions, integrating Panel of Normals (PoN), calculating contamination with GetPileupSummaries, and executing FilterMutectCalls.

🎯 Key Deliverables:

Reproducible Galaxy workflow from raw FASTQ to filtered somatic BAM
Comprehensive VEP & SnpEff functional annotation matrix

Galaxy GUI Picard MarkDup FilterMutectCalls Ensembl VEP COSMIC

Explore Chapter 08 →

MODULE 09 Phase 3: Galaxy Pipelines

Module 9: Somatic Variant Annotation & Filtering: VEP, SnpEff, gnomAD & COSMIC

Functional annotation using Ensembl VEP and SnpEff, integrating somatic (COSMIC), population (gnomAD), and clinical (ClinVar, OncoKB) databases, and exporting filtered mutation tables.

🎯 Key Deliverables:

Reproducible Galaxy workflow from raw FASTQ to filtered somatic BAM
Comprehensive VEP & SnpEff functional annotation matrix

Galaxy GUI Picard MarkDup FilterMutectCalls Ensembl VEP COSMIC

Explore Chapter 09 →

MODULE 10 Phase 4: Tiers & Tumor Board

Module 10: Somatic Interpretation Frameworks: AMP/ASCO/CAP Tiers & ClinGen Criteria

Clinical classification of somatic variants under AMP/ASCO/CAP 2017 guidelines (Tiers I–IV, Evidence Levels A–D), ClinGen/CGC/VICC oncogenicity specifications, and managing VUSs.

🎯 Key Deliverables:

Four-tier clinical actionability classification (Tiers I–IV)
Complete Molecular Tumor Board consensus report for NSCLC & CRC

AMP/ASCO/CAP OncoKB CIViC Molecular Tumor Board

Explore Chapter 10 →

MODULE 11 Phase 4: Tiers & Tumor Board

Module 11: Complex Alterations: Gene Fusions, Amplifications & Immunotherapy Eligibility

Detecting actionable oncogenic gene fusions (ALK, ROS1, NTRK), focal gene amplifications (ERBB2, MET), and integrating TMB/MSI for immune checkpoint inhibitor selection.

🎯 Key Deliverables:

Four-tier clinical actionability classification (Tiers I–IV)
Complete Molecular Tumor Board consensus report for NSCLC & CRC

AMP/ASCO/CAP OncoKB CIViC Molecular Tumor Board

Explore Chapter 11 →

MODULE 12 Phase 4: Tiers & Tumor Board

Module 12: Molecular Tumor Board (MDT) Simulation: Real Patient Cases & Clinical Reporting

Presenting real lung, colon, and breast cancer cases to a Multidisciplinary Tumor Board (MDT), resolving co-mutations and resistance mechanisms, and drafting clinical reports.

🎯 Key Deliverables:

Four-tier clinical actionability classification (Tiers I–IV)
Complete Molecular Tumor Board consensus report for NSCLC & CRC

AMP/ASCO/CAP OncoKB CIViC Molecular Tumor Board

Explore Chapter 12 →

Peer-Reviewed Foundations

📚 Foundational Literature & Methodology Benchmarks

Primary clinical variant curation, AMP/ASCO/CAP guidelines & Mutect2 citations for Track 15

📋 Clinical Variant Curation & AMP/ASCO/CAP Guidelines

Li MM, Datto M, Duncavage EJ, et al. (2017). Standards and guidelines for the interpretation and reporting of sequence variants in cancer: a joint consensus recommendation of AMP, ASCO, and CAP. Journal of Molecular Diagnostics 19(1):4–23. doi:10.1016/j.jmoldx.2016.10.002
Chakravarty D, Gao J, Phillips SM, et al. (2017). OncoKB: a precision oncology knowledge base. JCO Precision Oncology 2017:PO.17.00011. doi:10.1200/PO.17.00011
Griffith M, Spies NC, Krysiak K, et al. (2017). CIViC is a community knowledgebase for expert crowdsourcing the clinical interpretations of variants in cancer. Nature Genetics 49(2):170–174. doi:10.1038/ng.3774
Merker JD, Oxnard GR, Compton C, et al. (2018). Circulating tumor DNA analysis in patients with cancer: American Society of Clinical Oncology and College of American Pathologists joint review. Journal of Clinical Oncology 36(16):1631–1641. doi:10.1200/JCO.2017.76.8671

🔬 Somatic Mutation Calling & Cancer Pipelines

Benjamin D, Sato T, Cibulskis K, et al. (2019). Calling somatic SNVs and indels with Mutect2. bioRxiv:861054. doi:10.1101/861054
McLaren W, Gil L, Hunt SE, et al. (2016). The Ensembl Variant Effect Predictor. Genome Biology 17:122. doi:10.1186/s13059-016-0974-4
Tate JG, Bamford S, Jubb HC, et al. (2019). COSMIC: the Catalogue Of Somatic Mutations In Cancer. Nucleic Acids Research 47(D1):D941–D947. doi:10.1093/nar/gky1015
Van der Auwera GA, O'Connor BD. (2020). Genomics in the Cloud: Using Docker, GATK, and WDL in Terra. O'Reilly Media.

Looking for Other Bioinformatics Specializations?

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Browse All 20 Curricula (252 Chapters) → Track 05: Clinical Genomics & Diagnostics → Track 08: ACMG/AMP Variant Interpretation →