Whole genome sequencing (WGS) is becoming the preferred method for molecular genetic diagnosis of rare and unknown diseases and for identifying actionable cancer drivers. Compared to other molecular genetic methods, WGS captures most genomic variation and eliminates the need for sequential genetic testing. While laboratory requirements are similar to conventional molecular genetics, WGS requires a comprehensive computational and storage infrastructure to process data within a clinically relevant timeframe. The output of a single WGS analysis is roughly 5 million variants, and data interpretation involves specialized staff working with clinical specialists to provide standard of care reports. Although standards for variant classification are continuously refined, clinical application still faces unresolved issues. This review provides an overview of WGS in clinical practice, describing the technology, current applications, and challenges related to data processing, interpretation, and clinical reporting. The human genome project laid the foundation for new sequencing technologies and computational methods that enabled the clinical application of genomics. DNA sequencing became available for routine clinical use in the 1990s with the advent of semi-automated four-color dye sequencing. Next Generation Sequencing (NGS) has revolutionized the field, enabling the analysis of entire genomes quickly and cost-effectively. The capacity of NGS has increased significantly, allowing an entire human genome to be sequenced in 2 days for a few hundred dollars. WGS is a valuable source of information in many clinical situations, and archived WGS data can serve as a lifelong companion for patients that can be reanalysed and reinterpreted multiple times along the patient journey. WGS requires a robust computational infrastructure to ensure fast and reliable data processing. The data generated by WGS is significantly larger than that from large gene panels or exomes, requiring specialized software and hardware for processing. The data analysis pipeline includes mapping, calling, and interpretation of variants. Interpretation is performed by dedicated staff using third-party software with a graphical interface for interactive sorting and filtering of data. The creation of standardized variant calling workflows was pioneered by the open-source Genome Analysis Tool Kit (GATK), which forms the basis for many clinical WGS centers. However, commercial solutions and prediction-based approaches are also available. WGS has significant clinical applications in diagnosing rare diseases and identifying actionable somatic variants in tumors. It also serves to uncover polygenic risk scores and pharmacogenetic profiles. WGS can be considered a lifelong investment that may be revisited for different clinical purposes and reanalysed when novel pathogenic variants and disease-causing genes emerge. The diagnostic yield of WGS varies across different patient groups, ranging from a few percent for respiratory and some hematological disorders to 40–50% for hearing and ophthalmologic disorders, intellectual, and neurodevelopmental disorders. WGS has also been effective in oncology for comprehensive tumor characterization, supporting targeted treatment. WGS uncovers actionable tumor variants in approximately two-thirds of metastatic tumors. It has also revealed that a significant number of cancer patients carry predisposingWhole genome sequencing (WGS) is becoming the preferred method for molecular genetic diagnosis of rare and unknown diseases and for identifying actionable cancer drivers. Compared to other molecular genetic methods, WGS captures most genomic variation and eliminates the need for sequential genetic testing. While laboratory requirements are similar to conventional molecular genetics, WGS requires a comprehensive computational and storage infrastructure to process data within a clinically relevant timeframe. The output of a single WGS analysis is roughly 5 million variants, and data interpretation involves specialized staff working with clinical specialists to provide standard of care reports. Although standards for variant classification are continuously refined, clinical application still faces unresolved issues. This review provides an overview of WGS in clinical practice, describing the technology, current applications, and challenges related to data processing, interpretation, and clinical reporting. The human genome project laid the foundation for new sequencing technologies and computational methods that enabled the clinical application of genomics. DNA sequencing became available for routine clinical use in the 1990s with the advent of semi-automated four-color dye sequencing. Next Generation Sequencing (NGS) has revolutionized the field, enabling the analysis of entire genomes quickly and cost-effectively. The capacity of NGS has increased significantly, allowing an entire human genome to be sequenced in 2 days for a few hundred dollars. WGS is a valuable source of information in many clinical situations, and archived WGS data can serve as a lifelong companion for patients that can be reanalysed and reinterpreted multiple times along the patient journey. WGS requires a robust computational infrastructure to ensure fast and reliable data processing. The data generated by WGS is significantly larger than that from large gene panels or exomes, requiring specialized software and hardware for processing. The data analysis pipeline includes mapping, calling, and interpretation of variants. Interpretation is performed by dedicated staff using third-party software with a graphical interface for interactive sorting and filtering of data. The creation of standardized variant calling workflows was pioneered by the open-source Genome Analysis Tool Kit (GATK), which forms the basis for many clinical WGS centers. However, commercial solutions and prediction-based approaches are also available. WGS has significant clinical applications in diagnosing rare diseases and identifying actionable somatic variants in tumors. It also serves to uncover polygenic risk scores and pharmacogenetic profiles. WGS can be considered a lifelong investment that may be revisited for different clinical purposes and reanalysed when novel pathogenic variants and disease-causing genes emerge. The diagnostic yield of WGS varies across different patient groups, ranging from a few percent for respiratory and some hematological disorders to 40–50% for hearing and ophthalmologic disorders, intellectual, and neurodevelopmental disorders. WGS has also been effective in oncology for comprehensive tumor characterization, supporting targeted treatment. WGS uncovers actionable tumor variants in approximately two-thirds of metastatic tumors. It has also revealed that a significant number of cancer patients carry predisposing