@article {705,
	title = {SMN1 copy-number and sequence variant analysis from next-generation sequencing data.},
	journal = {Hum Mutat},
	volume = {41},
	year = {2020},
	month = {2020 12},
	pages = {2073-2077},
	abstract = {<p>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.</p>},
	keywords = {Base Sequence, DNA Copy Number Variations, High-Throughput Nucleotide Sequencing, Humans, Reproducibility of Results, Software, Survival of Motor Neuron 1 Protein},
	issn = {1098-1004},
	doi = {10.1002/humu.24120},
	author = {L{\'o}pez-L{\'o}pez, Daniel and Loucera, Carlos and Carmona, Rosario and Aquino, Virginia and Salgado, Josefa and Pasalodos, Sara and Miranda, Mar{\'\i}a and Alonso, {\'A}ngel and Dopazo, Joaquin}
}
