%0 Journal Article %J Hum Mutat %D 2020 %T SMN1 copy-number and sequence variant analysis from next-generation sequencing data. %A López-López, Daniel %A Loucera, Carlos %A Carmona, Rosario %A Aquino, Virginia %A Salgado, Josefa %A Pasalodos, Sara %A Miranda, María %A Alonso, Ángel %A Dopazo, Joaquin %K Base Sequence %K DNA Copy Number Variations %K High-Throughput Nucleotide Sequencing %K Humans %K Reproducibility of Results %K Software %K Survival of Motor Neuron 1 Protein %X

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.

%B Hum Mutat %V 41 %P 2073-2077 %8 2020 12 %G eng %N 12 %1 https://www.ncbi.nlm.nih.gov/pubmed/33058415?dopt=Abstract %R 10.1002/humu.24120