Metabolic bone diseases are a diverse group of disorders that impair skeletal strength and development through disrupted bone remodeling or imbalances in calcium, phosphate, and vitamin D metabolism. Many of these conditions are ultra-rare, genetically heterogeneous and remain undiagnosed despite clinical evaluation. This project aims to identify novel gene variants responsible for metabolic bone disorders and to uncover the molecular mechanisms involved in their pathogenesis. To achieve this, we analyze human cohorts or samples using a broad range of high-throughput sequencing methodologies and integrative analyses. As a standard, we employ whole-genome sequencing (WGS) supported by clinical and family-based archival data. We also use methods like whole-exome sequencing (WES), transcriptomics sequencing, methylation profiling, long read sequencing, and optical mapping where needed. Affected patients and family members are also actively recruited through Karolinska University Hospital and collaborating international centers with data sharing agreements in place. Functional follow-up studies using patient-derived cells are guided by genetic findings. Due to the sensitive nature of patient data and the scale of analysis, all processing is needed to be performed within the secure Bianca environment at UPPMAX. Our workflows include raw data processing, alignment, variant calling, joint genotyping, structural variant and CNV detection, RNA-seq analysis, and mitochondrial variant analysis. These steps will be managed using Snakemake, parallelized using slurm arrays, and containerized or centralized tools in UPPMAX to ensure reproducibility and efficient use of compute resources. We also maintain in-house variant databases and version-controlled result tracking. Access to UPPMAX resources is essential for handling the growing volume of sequencing data, ensuring secure storage, and running computationally demanding analyses. The outcomes of this work are expected to improve molecular diagnosis in rare skeletal diseases and contribute to better patient care through precision medicine approaches.