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Seminars, events & talks

Wednesday, 8th November, 2017, 12:00

PsyGeNET: a knowledge resource on psychiatric diseases and their genes

Psychiatric disorders constitute one of the main causes of disability worldwide. During the past years, considerable research on the genetic architecture of such diseases has been conducted, although little understanding of their etiology has been achieved. The difficulty to access up-to-date, relevant genotype-phenotype information has hampered the application of this wealth of knowledge to translational research and clinical practice in order to improve diagnosis and treatment of psychiatric patients. PsyGeNET has been developed with the aim of supporting research on the genetic architecture of psychiatric diseases, by providing integrated and structured accessibility to their genotype-phenotype association data, together with a set of analysis and visualization tools.

PsyGeNET contains up-to-date information on genes associated with mood disorders (depression, bipolar disorder), psychosis (schizophrenia) and substance use disorders (alcohol, cannabis and cocaine use disorders, substance-induced depressive disorder and psychoses). The current version of PsyGeNET (version 2.0) contains 3,771 associations between 1,549 genes and 117 psychiatric disease concepts. PsyGeNET offers several metrics for the prioritization of the information, including the Evidence Index that takes into account the negative evidence found in publications for a particular gene-disease association. The PsyGeNET database has been developed by extracting gene-disease associations from the literature with the text mining tool BeFree (https://bitbucket.org/ibi_group/befree), followed by a process of curation by a team of 22 domain experts. A web-based annotation tool supported the curation process. The data is accessible through a web interface (http://www.psygenet.org/) and the psygenet2r Bioconductor package (https://bioconductor.org/packages/release/bioc/html/psygenet2r.html). Moreover, the psygenet2r package implements several functions to visualize and analyze the PsyGeNET data in a clear and meaningful way and allows performing comorbidity analysis based on shared genes. Due to its special focus on psychiatric diseases and comprehensiveness, PsyGeNET represents a valuable resource for the analysis of the molecular underpinning of psychiatric disorders and their comorbidities.

Speaker: Alba Gutiérrez-Sacristán

Room Aula room 473.10 (4th floor)



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