@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 {21919703,
	title = {Assessing Differential Expression Measurements by Highly Parallel Pyrosequencing and DNA Microarrays: A Comparative Study.},
	journal = {Omics : a journal of integrative biology},
	year = {2013},
	month = {2011 Sep 15},
	abstract = {<p>Abstract To explore the feasibility of pyrosequencing for quantitative differential gene expression analysis we have performed a comparative study of the results of the sequencing experiments to those obtained by a conventional DNA microarray platform. A conclusion from our analysis is that, over a threshold of 35 normalized reads per gene, the measurements of gene expression display a good correlation with the references. The observed concordance between pyrosequencing and DNA microarray platforms beyond the threshold was of 0.8, measured as a Pearson{\textquoteright}s correlation coefficient. In differential gene expression the initial aim is the quantification the differences among transcripts when comparing experimental conditions. Thus, even in a scenario of low coverage the concordance in the measurements is quite acceptable. On the other hand, the comparatively longer read size obtained by pyrosequencing allows detecting unconventional splicing forms.</p>},
	doi = {10.1089/omi.2011.0065},
	url = {http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3545353/},
	author = {Ari{\~n}o, Joaqu{\'\i}n and Casamayor, Antonio and P{\'e}rez, Juli{\'a}n Perez and Pedrola, Laia and Alvarez-Tejado, Miguel and Marb{\`a}, Martina and Santoyo, Javier and Joaqu{\'\i}n Dopazo}
}
