@article {701,
	title = {CSVS, a crowdsourcing database of the Spanish population genetic variability.},
	journal = {Nucleic Acids Res},
	volume = {49},
	year = {2021},
	month = {2021 01 08},
	pages = {D1130-D1137},
	abstract = {<p>The knowledge of the genetic variability of the local population is of utmost importance in personalized medicine and has been revealed as a critical factor for the discovery of new disease variants. Here, we present the Collaborative Spanish Variability Server (CSVS), which currently contains more than 2000 genomes and exomes of unrelated Spanish individuals. This database has been generated in a collaborative crowdsourcing effort collecting sequencing data produced by local genomic projects and for other purposes. Sequences have been grouped by ICD10 upper categories. A web interface allows querying the database removing one or more ICD10 categories. In this way, aggregated counts of allele frequencies of the pseudo-control Spanish population can be obtained for diseases belonging to the category removed. Interestingly, in addition to pseudo-control studies, some population studies can be made, as, for example, prevalence of pharmacogenomic variants, etc. In addition, this genomic data has been used to define the first Spanish Genome Reference Panel (SGRP1.0) for imputation. This is the first local repository of variability entirely produced by a crowdsourcing effort and constitutes an example for future initiatives to characterize local variability worldwide. CSVS is also part of the GA4GH Beacon network. CSVS can be accessed at: http://csvs.babelomics.org/.</p>},
	keywords = {Alleles, Chromosome Mapping, Crowdsourcing, Databases, Genetic, Exome, Gene Frequency, Genetic Variation, Genetics, Population, Genome, Human, Genomics, Humans, Internet, Precision Medicine, Software, Spain},
	issn = {1362-4962},
	doi = {10.1093/nar/gkaa794},
	author = {Pe{\~n}a-Chilet, Maria and Rold{\'a}n, Gema and Perez-Florido, Javier and Ortuno, Francisco M and Carmona, Rosario and Aquino, Virginia and L{\'o}pez-L{\'o}pez, Daniel and Loucera, Carlos and Fernandez-Rueda, Jose L and Gallego, Asunci{\'o}n and Garcia-Garcia, Francisco and Gonz{\'a}lez-Neira, Anna and Pita, Guillermo and N{\'u}{\~n}ez-Torres, Roc{\'\i}o and Santoyo-L{\'o}pez, Javier and Ayuso, Carmen and Minguez, Pablo and Avila-Fernandez, Almudena and Corton, Marta and Moreno-Pelayo, Miguel {\'A}ngel and Morin, Mat{\'\i}as and Gallego-Martinez, Alvaro and Lopez-Escamez, Jose A and Borrego, Salud and Anti{\v n}olo, Guillermo and Amigo, Jorge and Salgado-Garrido, Josefa and Pasalodos-Sanchez, Sara and Morte, Beatriz and Carracedo, {\'A}ngel and Alonso, {\'A}ngel and Dopazo, Joaquin}
}
@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}
}
