AbstractSpinal Muscular Atrophy (SMA) is a severe neuromuscular autosomal recessive disorder affecting 1/10,000 live births. Most SMA patients present homozygous deletion ofSMN1, while the vast majority of SMA carriers present only a singleSMN1copy. The sequence similarity betweenSMN1andSMN2, and the complexity of the SMN locus makes the estimation of the SMN1 copy-number by next generation sequencing (NGS) very difficult Here, we present SMAca, the first python tool to detect SMA carriers and estimate the absolute SMN1 copy-number using NGS data. Moreover, SMAca takes advantage of the knowledge of certain variants specific toSMN1duplication to also identify silent carriers. This tool has been validated with a cohort of 326 samples from the Navarra 1000 Genomes project (NAGEN1000). SMAca was developed with a focus on execution speed and easy installation. This combination makes it especially suitable to be integrated into production NGS pipelines. Source code and documentation are available on Github at:www.github.com/babelomics/SMAca