RT Journal Article
T1 SMN1 copy-number and sequence variant analysis from next-generation sequencing data.
A1 Lopez-Lopez, Daniel
A1 Loucera, Carlos
A1 Carmona, Rosario
A1 Aquino, Virginia
A1 Salgado, Josefa
A1 Pasalodos, Sara
A1 Miranda, María
A1 Alonso, Ángel
A1 Dopazo, Joaquín
K1 SMA
K1 next generation sequencing
K1 pipeline
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.
YR 2020
FD 2020-10-14
LK http://hdl.handle.net/10668/16425
UL http://hdl.handle.net/10668/16425
LA en
DS RISalud
RD Apr 11, 2025