TY - JOUR T1 - SMN1 copy-number and sequence variant analysis from next-generation sequencing data. JF - Hum Mutat Y1 - 2020 A1 - López-López, Daniel A1 - Loucera, Carlos A1 - Carmona, Rosario A1 - Aquino, Virginia A1 - Salgado, Josefa A1 - Pasalodos, Sara A1 - Miranda, María A1 - Alonso, Ángel A1 - Dopazo, Joaquin KW - Base Sequence KW - DNA Copy Number Variations KW - High-Throughput Nucleotide Sequencing KW - Humans KW - Reproducibility of Results KW - Software KW - Survival of Motor Neuron 1 Protein AB -

Spinal muscular atrophy (SMA) is a severe neuromuscular autosomal recessive disorder affecting 1/10,000 live births. Most SMA patients present homozygous deletion of SMN1, while the vast majority of SMA carriers present only a single SMN1 copy. The sequence similarity between SMN1 and SMN2, 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 to SMN1 duplication 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 at https://www.github.com/babelomics/SMAca.

VL - 41 IS - 12 U1 - https://www.ncbi.nlm.nih.gov/pubmed/33058415?dopt=Abstract ER -