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bioRxiv · 10.1101/2020.03.31.014589

SMN1 copy-number and sequence variant analysis from next generation sequencing data

Lopez-Lopez, D.·Loucera, C.·Carmona, R.·Aquino, V.·Salgado, J.·Pasalodos, S.·Miranda, M.·Alonso, A.·Dopazo, J.
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Abstract

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 on Github at: www.github.com/babelomics/SMAca

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Lopez-Lopez, D., Loucera, C., Carmona, R., Aquino, V., Salgado, J., Pasalodos, S., Miranda, M., Alonso, A., Dopazo, J.. 2020-04-01. SMN1 copy-number and sequence variant analysis from next generation sequencing data. https://doi.org/10.1101/2020.03.31.014589

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