Clinical Variant Interpretation with the Integrative Genomics Viewer (IGV) for Molecular Pathologists

Eitan Halper-Stromberg; Suguna Narayan; Vincent Laufer; Melvin Limson; Tracy Busse; Jeremy P. Segal; Dara L. Aisner; Jennifer J.D. Morrissette; Helga Thorvaldsdottir; James T. Robinson; Somak Roy; Melissa Y. Tjota

doi:10.3791/71808

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Method Article

Clinical Variant Interpretation with the Integrative Genomics Viewer (IGV) for Molecular Pathologists

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DOI:

10.3791/71808

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August 14th, 2026

Eitan Halper-Stromberg^*¹ , Suguna Narayan^*² , Vincent Laufer^*² , Melvin Limson³ , Tracy Busse³ , Jeremy P. Segal⁴ , Dara L. Aisner⁵ , Jennifer J.D. Morrissette⁶ , Helga Thorvaldsdottir⁷ , James T. Robinson⁸ , Somak Roy⁹ , Melissa Y. Tjota⁴

¹University of Pennsylvania, Department of Pathology and Laboratory Medicine, ²University of Michigan, Department of Pathology, ³Genomics Organization for Academic Laboratories (GOAL), ⁴University of Chicago, Department of Pathology, ⁵University of Colorado, Department of Pathology, ⁶University of Pennsylvania, Department of Pathology and Laboratory Medicine, ⁷Broad Institute of MIT and Harvard, ⁸University of California San Diego, Department of Medicine, ⁹Cincinnati Children's Hospital Medical Center, Division of Pathology and Laboratory Medicine

^* These authors contributed equally

Summary

The integrative genomics viewer (IGV) software offers a rich, intuitive window into the underlying data for clinical variant calling. Here we present five vignettes that demonstrate how to perform swift differentiation between genuine pathogenic events and artifacts, ultimately reinforcing diagnostic confidence for practitioners engaged in molecular sign-out of next-generation sequencing assays.

Abstract

The integrative genomics viewer (IGV) is a pivotal tool in clinical genomics, enabling the visualization and interpretation of complex sequencing data. Bringing clinical knowledge to bear with visual evaluation of sequencing results is the primary means by which molecular pathologists and other professionals assess and finalize cases. A variety of software tools can assist, but their relationship to the underlying data must be understood and applied systematically. This study includes essential background on next-generation sequencing (NGS) data file types (e.g., FASTQ, BAM, VCF) with a discussion of their format and purpose. We then describe features of IGV that derive nuances from these files. We utilize a series of curated practical cases based on clinical vignettes through which the reader will interact with clinical NGS sequencing data using the IGV software to review various types of clinically relevant variants relative to the human reference genome. These clinical vignettes have been curated to describe examples of some of the complexities of interpretation of genomic data, and how utilizing IGV as part of a routine workflow can provide additional interpretive information for variants beyond routine bioinformatic software algorithm variant calls. The visual inspection of genomic variants utilizing the tools within IGV can unmask subtle contextual cues (i.e., variant allele frequency, strand bias, tissue-specific context) that can influence the interpretation of genomic variants. Although this study focuses on using IGV for the detection and interpretation of somatic variants, the provided applications can be extrapolated for use in the germline setting, including analysis of complex variants and detection of mosaicism.

Introduction

Oncology care has been transformed in recent years by the use of next-generation sequencing (NGS) technologies to inform diagnosis, prognosis, and therapy selection¹. NGS testing has become the standard of care in multiple tumor types for 1) establishing a diagnosis of a molecularly defined tumor, 2) using tumor-type agnostic biomarker results for therapy decisions, and 3) determining risk stratification for specific tumor types²^,³. Accurate and timely results from NGS and other biomarker testing have become a critical component for patient care and planning in oncology.