Exome Sequencing Data Analysis for Clinical Reporting

Syllabus Overview

Class 1: Introduction to Whole Exome Sequencing

• Objective: Understand the basics of whole exome sequencing and its applications.

✓ Overview of WES, target enrichment strategies, and its clinical and research

applications.

✓ Comparison of WES with whole-genome sequencing (WGS).

✓ Key challenges and considerations for WES.

✓ Applications of WES in disease research, diagnostics, and personalized medicine.

✓ Homework: Read articles on WES and its applications in genomics.

Class 10: Quality Control and Preprocessing of WES Data

• Objective: Learn quality control and preprocessing steps for raw WES data.

✓ Quality control of FASTQ files using FastQC.

✓ Adapter trimming and cleaning of reads using Trimmomatic.

✓ Overview of paired-end sequencing data and differences in germline vs. somatic

workflows.

✓ Homework: Preprocess raw WES data using Trim Galore.

Class 11: Alignment and Post-Processing for WES Data

• Objective: Align and post-process WES data for variant calling.

✓ Aligning WES data using BWA-MEM.

✓ Post-alignment processing: sorting, marking duplicates, and base recalibration

(BQSR) using GATK.

✓ Introduction to SAM/BAM file formats and their handling.

✓ Homework: Align a sample WES dataset and perform post-processing steps.

Class 12: Germline Variant Calling with GATK

• Objective: Perform germline variant calling and filtering.

✓ Overview of GATK HaplotypeCaller for germline variant detection.

✓ Joint genotyping for multiple germline samples.

✓ Filtering variants using hard filters and VQSR (variant quality score recalibration).

✓ Homework: Perform germline variant calling and filtering using sample data.

Class 13: Somatic Variant Calling with GATK and Other Tools

• Objective: Detect somatic variants using tumor-normal paired samples.

✓ Prepare Input Data

✓ Create a Panel of Normals

✓ Somatic variant calling with Mutect2 (GATK).

✓ Filtering and refining somatic variant calls.

✓ Homework: Run somatic variant calling on tumor-normal data using Mutect2.

Class 14: Variant Annotation and Interpretation

• Objective: Annotate and interpret germline and somatic variants.

✓ Annotating variants with tools like ANNOVAR, VEP, SnpEff.

✓ Database integration: gnomAD, ClinVar, COSMIC, TCGA.

✓ Understanding variant effect predictions (SIFT, PolyPhen, CADD).

✓ Homework: Annotate germline and somatic variants and interpret their biological

relevance.

Class 15: Prioritization of Variants

• Objective: Prioritize variants for clinical or research applications.

✓ Discuss variant prioritization criteria: population frequency, pathogenicity, functional

impact.

✓ Using bioinformatics tools to prioritize variants (e.g., CADD, MutationTaster).

✓ Case studies: Variant interpretation in disease contexts.

✓ Homework: Prioritize variants from an annotated dataset based on clinical/research

criteria.

Class 16: Reporting and Visualization of WES Analysis Results

• Objective: Generate reports and visualizations of variant analysis results.

✓ Creating reports summarizing identified variants, their annotations, and

prioritization.

✓ Visualizing important variants using tools like IGV or Circos.

✓ Preparing a comprehensive report for clinical or research purposes.

✓ Homework: Prepare a final report with annotated, prioritized variants and

visualizations.