The Integrative Genomics Viewer (IGV) is a lightweight, intuitive visualization tool designed to explore large-scale genomic datasets on standard desktop computers. Developed by researchers from the Broad Institute, MIT, and Harvard, IGV supports flexible integration of various genomic data types, including aligned sequence reads, mutations, copy number, RNAi screens, gene expression, methylation, and genomic annotations. It uses multi-resolution file formats to enable real-time exploration of datasets of all sizes, with minimal resource consumption. IGV allows users to navigate datasets seamlessly, from whole-genome views to base-pair resolution, and supports loading data from local or remote sources, including cloud-based resources. Key features include the ability to visualize diverse data types across multiple samples, correlate these datasets with clinical and phenotypic variables, and use sample metadata for grouping, sorting, and filtering. IGV is particularly useful for next-generation sequencing (NGS) datasets, offering detailed views of aligned reads, SNPs, and paired-end reads, and highlighting genomic rearrangements. The software is open-source and freely available, making it accessible to a wide range of users.The Integrative Genomics Viewer (IGV) is a lightweight, intuitive visualization tool designed to explore large-scale genomic datasets on standard desktop computers. Developed by researchers from the Broad Institute, MIT, and Harvard, IGV supports flexible integration of various genomic data types, including aligned sequence reads, mutations, copy number, RNAi screens, gene expression, methylation, and genomic annotations. It uses multi-resolution file formats to enable real-time exploration of datasets of all sizes, with minimal resource consumption. IGV allows users to navigate datasets seamlessly, from whole-genome views to base-pair resolution, and supports loading data from local or remote sources, including cloud-based resources. Key features include the ability to visualize diverse data types across multiple samples, correlate these datasets with clinical and phenotypic variables, and use sample metadata for grouping, sorting, and filtering. IGV is particularly useful for next-generation sequencing (NGS) datasets, offering detailed views of aligned reads, SNPs, and paired-end reads, and highlighting genomic rearrangements. The software is open-source and freely available, making it accessible to a wide range of users.