Bioinformatics Pipeline for Whole-Exome Sequencing (WES) and Whole-Genome Sequencing (WGS) in Cancer Genomics

This documentation summarizes bioinformatics workflows, updated WGS/WES pipeline recommendations, and key findings from two pivotal studies: Yang et al. (2024) on pharmacogenomic profiling of intra-tumor heterogeneity in liver cancer using organoid biobanks, and Ljungström et al. (2016) on whole-exome sequencing in relapsing chronic lymphocytic leukemia revealing recurrent RPS15 mutations. It includes study contexts, major results, and interpretation guidelines for ITH-aware somatic variant detection, clonal evolution analysis, and clinical implications in heterogeneous cancers.

Note

The original studies employed sequencing pipelines tailored to their experimental contexts. Yang et al. (2024) utilized modern tools like bwa-mem2 and GATK v4 for multi-region organoid profiling in primary liver cancer (PLC), emphasizing transcriptomic integration for drug response signatures. Ljungström et al. (2016) used earlier versions (e.g., BWA v0.7, GATK v2) for paired pre/post-relapse WES in CLL, focusing on subclonal shifts and novel drivers like RPS15.

In this documentation, workflows have been adapted and modernized for general-purpose WGS/WES bioinformatics, incorporating current best practices (as of 2025) such as BWA-MEM2 alignment to GRCh38, GATK4 Mutect2 for somatic calling, FACETS for purity/ploidy estimation, SciClone for subclonal inference, and lower VAF thresholds (e.g., ≥0.05) to enhance sensitivity, reproducibility, and applicability to cancers with high ITH or evolutionary dynamics.

Contents

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