Many individuals with suspected genetic neuromuscular disorders (NMDs) remain undiagnosed despite extensive conventional genetic testing, which generally employs short-read sequencing (SRS) methods. Long-read sequencing (LRS) is a recently introduced technology which offers improved genome coverage and variant detection missed in standard approaches. Therefore, this pilot study aimed to investigate the application of long-read whole genome sequencing (LR-WGS) with the PacBio Revio platform for five participants (four families) with undiagnosed NMDs to identify causal genetic variants. Retrospective participant chart reviews were first conducted to assess phenotype, inheritance patterns, and other clinical factors. Following this, a novel bioinformatics pipeline was developed to enhance variant annotation and prioritization by integrating LRS population data with established genomic population frequency databases and in-silico predictions of deleteriousness. Finally, manual filtration was performed to further refine variant prioritization based on the clinical insights gained from chart reviews. Candidate variants of interest were found in three of four families analyzed (75%), including strong candidates in the FLNC and DMD genes, and a potential candidate in the TTN gene requiring functional validation. This pilot validates the pipeline for analysis of LRS data and provides evidence that LR-WGS could offer improvements over traditional SRS approaches in diagnosing NMDs, particularly in detecting complex variants. Improving accurate molecular diagnosis ultimately leads to better clinical outcomes for affected patients, including personalized treatment strategies and interventions. Future directions include the study of additional participants with NMDs to allow for a more comprehensive evaluation of diagnostic yield and applicability across diverse genetic backgrounds.