Next-generation sequencing technologies are increasingly being applied in clinical settings, however the data are characterized by a range of platform-specific artifacts making downstream analysis problematic and error prone. One major application of NGS is in the profiling of clinically relevant mutations whereby sequences are aligned to a reference genome and potential mutations assessed and scored. Accurate sequence alignment is pivotal in reliable assessment of potential mutations however selection of appropriate alignment tools is a non-trivial task complicated by the availability of multiple solutions each with its own performance characteristics. Using BRCA1 as an example, we have simulated and mutated a test dataset based on Illumina sequencing technology. Our findings reveal key differences in the performances of a range of common commercial and open source tools and will be of importance to anyone using NGS to profile mutations in clinical or basic research.