@article {1058,
	title = {A web tool for the design and management of panels of genes for targeted enrichment and massive sequencing for clinical applications.},
	journal = {Nucleic acids research},
	volume = {42},
	year = {2014},
	month = {2014 May 26},
	pages = {W83-W87},
	abstract = {Disease targeted sequencing is gaining importance as a powerful and cost-effective application of high throughput sequencing technologies to the diagnosis. However, the lack of proper tools to process the data hinders its extensive adoption. Here we present TEAM, an intuitive and easy-to-use web tool that fills the gap between the predicted mutations and the final diagnostic in targeted enrichment sequencing analysis. The tool searches for known diagnostic mutations, corresponding to a disease panel, among the predicted patient{\textquoteright}s variants. Diagnostic variants for the disease are taken from four databases of disease-related variants (HGMD-public, HUMSAVAR, ClinVar and COSMIC.) If no primary diagnostic variant is found, then a list of secondary findings that can help to establish a diagnostic is produced. TEAM also provides with an interface for the definition of and customization of panels, by means of which, genes and mutations can be added or discarded to adjust panel definitions. TEAM is freely available at: http://team.babelomics.org.},
	keywords = {Diagnostic, Targeted enrichment sequencing, WES},
	issn = {1362-4962},
	doi = {10.1093/nar/gku472},
	url = {http://nar.oxfordjournals.org/cgi/pmidlookup?view=long\&pmid=24861626},
	author = {Alem{\'a}n, Alejandro and Garcia-Garcia, Francisco and Medina, Ignacio and Joaqu{\'\i}n Dopazo}
}
@article {1051,
	title = {A web-based interactive framework to assist in the prioritization of disease candidate genes in whole-exome sequencing studies.},
	journal = {Nucleic acids research},
	volume = {42},
	year = {2014},
	month = {2014 May 6},
	pages = {W88-W93.},
	abstract = {Whole-exome sequencing has become a fundamental tool for the discovery of disease-related genes of familial diseases and the identification of somatic driver variants in cancer. However, finding the causal mutation among the enormous background of individual variability in a small number of samples is still a big challenge. Here we describe a web-based tool, BiERapp, which efficiently helps in the identification of causative variants in family and sporadic genetic diseases. The program reads lists of predicted variants (nucleotide substitutions and indels) in affected individuals or tumor samples and controls. In family studies, different modes of inheritance can easily be defined to filter out variants that do not segregate with the disease along the family. Moreover, BiERapp integrates additional information such as allelic frequencies in the general population and the most popular damaging scores to further narrow down the number of putative variants in successive filtering steps. BiERapp provides an interactive and user-friendly interface that implements the filtering strategy used in the context of a large-scale genomic project carried out by the Spanish Network for Research in Rare Diseases (CIBERER) in which more than 800 exomes have been analyzed. BiERapp is freely available at: http://bierapp.babelomics.org/},
	keywords = {NGS. prioritization},
	issn = {1362-4962},
	doi = {10.1093/nar/gku407},
	url = {http://nar.oxfordjournals.org/content/42/W1/W88},
	author = {Alem{\'a}n, Alejandro and Garcia-Garcia, Francisco and Salavert, Francisco and Medina, Ignacio and Joaqu{\'\i}n Dopazo}
}
