@article {1184,
	title = {267 Spanish exomes reveal population-specific differences in disease-related genetic variation.},
	journal = {Molecular biology and evolution},
	year = {2016},
	month = {2016 Jan 13},
	abstract = {Recent results from large-scale genomic projects suggest that allele frequencies, which are highly relevant for medical purposes, differ considerably across different populations. The need for a detailed catalogue of local variability motivated the whole exome sequencing of 267 unrelated individuals, representative of the healthy Spanish population. Like in other studies, a considerable number of rare variants were found (almost one third of the described variants). There were also relevant differences in allelic frequencies in polymorphic variants, including about 10,000 polymorphisms private to the Spanish population. The allelic frequencies of variants conferring susceptibility to complex diseases (including cancer, schizophrenia, Alzheimer disease, type 2 diabetes and other pathologies) were overall similar to those of other populations. However, the trend is the opposite for variants linked to Mendelian and rare diseases (including several retinal degenerative dystrophies and cardiomyopathies) that show marked frequency differences between populations. Interestingly, a correspondence between differences in allelic frequencies and disease prevalence was found, highlighting the relevance of frequency differences in disease risk. These differences are also observed in variants that disrupt known drug binding sites, suggesting an important role for local variability in population-specific drug resistances or adverse effects. We have made the Spanish population variant server web page that contains population frequency information for the complete list of 170,888 variant positions we found publicly available (http://spv.babelomics.org/), We show that it if fundamental to determine population-specific variant frequencies in order to distinguish real disease associations from population-specific polymorphisms.},
	keywords = {disease, NGS, polymorphisms, Population genomics, prioritization, SNP},
	issn = {1537-1719},
	doi = {10.1093/molbev/msw005},
	url = {https://mbe.oxfordjournals.org/content/early/2016/02/17/molbev.msw005.full},
	author = {Joaqu{\'\i}n Dopazo and Amadoz, Alicia and Bleda, Marta and Garc{\'\i}a-Alonso, Luz and Alem{\'a}n, Alejandro and Garcia-Garcia, Francisco and Rodriguez, Juan A and Daub, Josephine T and Muntan{\'e}, Gerard and Antonio Rueda and Vela-Boza, Alicia and L{\'o}pez-Domingo, Francisco J and Florido, Javier P and Arce, Pablo and Ruiz-Ferrer, Macarena and M{\'e}ndez-Vidal, Cristina and Arnold, Todd E and Spleiss, Olivia and Alvarez-Tejado, Miguel and Navarro, Arcadi and Bhattacharya, Shomi S and Borrego, Salud and Santoyo-L{\'o}pez, Javier and Anti{\v n}olo, Guillermo}
}
@article {1129,
	title = {Babelomics 5.0: functional interpretation for new generations of genomic data.},
	journal = {Nucleic acids research},
	volume = {43},
	number = {W1},
	year = {2015},
	month = {2015 Apr 20},
	pages = {W117-W121},
	abstract = {Babelomics has been running for more than one decade offering a user-friendly interface for the functional analysis of gene expression and genomic data. Here we present its fifth release, which includes support for Next Generation Sequencing data including gene expression (RNA-seq), exome or genome resequencing. Babelomics has simplified its interface, being now more intuitive. Improved visualization options, such as a genome viewer as well as an interactive network viewer, have been implemented. New technical enhancements at both, client and server sides, makes the user experience faster and more dynamic. Babelomics offers user-friendly access to a full range of methods that cover: (i) primary data analysis, (ii) a variety of tests for different experimental designs and (iii) different enrichment and network analysis algorithms for the interpretation of the results of such tests in the proper functional context. In addition to the public server, local copies of Babelomics can be downloaded and installed. Babelomics is freely available at: http://www.babelomics.org.},
	keywords = {babelomics, data integration, gene set analysis, interactome, network analysis, NGS, RNA-seq, Systems biology, transcriptomics},
	issn = {1362-4962},
	doi = {10.1093/nar/gkv384},
	url = {http://nar.oxfordjournals.org/content/43/W1/W117},
	author = {Alonso, Roberto and Salavert, Francisco and Garcia-Garcia, Francisco and Carbonell-Caballero, Jos{\'e} and Bleda, Marta and Garc{\'\i}a-Alonso, Luz and Sanchis-Juan, Alba and Perez-Gil, Daniel and Marin-Garcia, Pablo and S{\'a}nchez, Rub{\'e}n and Cubuk, Cankut and Hidalgo, Marta R and Amadoz, Alicia and Hernansaiz-Ballesteros, Rosa D and Alem{\'a}n, Alejandro and T{\'a}rraga, Joaqu{\'\i}n and Montaner, David and Medina, Ignacio and Dopazo, Joaquin}
}
@article {1171,
	title = {Exome sequencing reveals a high genetic heterogeneity on familial Hirschsprung disease.},
	journal = {Scientific reports},
	volume = {5},
	year = {2015},
	month = {2015},
	pages = {16473},
	abstract = {Hirschsprung disease (HSCR; OMIM 142623) is a developmental disorder characterized by aganglionosis along variable lengths of the distal gastrointestinal tract, which results in intestinal obstruction. Interactions among known HSCR genes and/or unknown disease susceptibility loci lead to variable severity of phenotype. Neither linkage nor genome-wide association studies have efficiently contributed to completely dissect the genetic pathways underlying this complex genetic disorder. We have performed whole exome sequencing of 16 HSCR patients from 8 unrelated families with SOLID platform. Variants shared by affected relatives were validated by Sanger sequencing. We searched for genes recurrently mutated across families. Only variations in the FAT3 gene were significantly enriched in five families. Within-family analysis identified compound heterozygotes for AHNAK and several genes (N = 23) with heterozygous variants that co-segregated with the phenotype. Network and pathway analyses facilitated the discovery of polygenic inheritance involving FAT3, HSCR known genes and their gene partners. Altogether, our approach has facilitated the detection of more than one damaging variant in biologically plausible genes that could jointly contribute to the phenotype. Our data may contribute to the understanding of the complex interactions that occur during enteric nervous system development and the etiopathology of familial HSCR.},
	keywords = {babelomics, Hirschprung, NGS, prioritization},
	issn = {2045-2322},
	doi = {10.1038/srep16473},
	url = {http://www.nature.com/articles/srep16473},
	author = {Luz{\'o}n-Toro, Berta and Gui, Hongsheng and Ruiz-Ferrer, Macarena and Sze-Man Tang, Clara and Fern{\'a}ndez, Raquel M and Sham, Pak-Chung and Torroglosa, Ana and Kwong-Hang Tam, Paul and Espino-Pais{\'a}n, Laura and Cherny, Stacey S and Bleda, Marta and Enguix-Riego, Mar{\'\i}a Del Valle and Joaqu{\'\i}n Dopazo and Anti{\v n}olo, Guillermo and Garcia-Barcel{\'o}, Maria-Merc{\`e} and Borrego, Salud}
}
@article {1003,
	title = {Genome Maps, a new generation genome browser.},
	journal = {Nucleic acids research},
	volume = {41},
	number = {W1},
	year = {2013},
	month = {2013 Jun 8},
	pages = {W41-W46},
	abstract = {Genome browsers have gained importance as more genomes and related genomic information become available. However, the increase of information brought about by new generation sequencing technologies is, at the same time, causing a subtle but continuous decrease in the efficiency of conventional genome browsers. Here, we present Genome Maps, a genome browser that implements an innovative model of data transfer and management. The program uses highly efficient technologies from the new HTML5 standard, such as scalable vector graphics, that optimize workloads at both server and client sides and ensure future scalability. Thus, data management and representation are entirely carried out by the browser, without the need of any Java Applet, Flash or other plug-in technology installation. Relevant biological data on genes, transcripts, exons, regulatory features, single-nucleotide polymorphisms, karyotype and so forth, are imported from web services and are available as tracks. In addition, several DAS servers are already included in Genome Maps. As a novelty, this web-based genome browser allows the local upload of huge genomic data files (e.g. VCF or BAM) that can be dynamically visualized in real time at the client side, thus facilitating the management of medical data affected by privacy restrictions. Finally, Genome Maps can easily be integrated in any web application by including only a few lines of code. Genome Maps is an open source collaborative initiative available in the GitHub repository (https://github.com/compbio-bigdata-viz/genome-maps). Genome Maps is available at: http://www.genomemaps.org.},
	keywords = {BAM, genome viewer, HTML5, javascript, Next Generation Sequencing, NGS, SVG, VCF},
	issn = {1362-4962},
	doi = {10.1093/nar/gkt530},
	url = {http://nar.oxfordjournals.org/content/41/W1/W41},
	author = {Medina, Ignacio and Salavert, Francisco and S{\'a}nchez, Rub{\'e}n and De Maria, Alejandro and Alonso, Roberto and Escobar, Pablo and Bleda, Marta and Joaqu{\'\i}n Dopazo}
}
