PRBB Computational Genomics Seminars
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Seminars are scheduled on a bi-weekly basis, taking place on Thursdays from 12:00 to 13:00. The sessions are conducted in a hybrid format: in-person attendance is held in the Aula Room (PRBB, 4th floor), while remote participation is available via Zoom.
Those interested in receiving information regarding forthcoming seminars are invited to subscribe to the mailing list by contacting rut.carbonell@crg.eu
The schedule of sessions is provided below and is updated on a regular basis.
06/11/202512:00R_473.10_AULAPRBB Computational Genomics SeminarsGabriel Santpere BaróEvolutionary Genomics Group. Hospital del Mar Medical Research Institutetbc
10/11/202516:00R_473.10_AULAPRBB Computational Genomics SeminarsSarah Cohen BoulakiaTBCTBC
20/11/202512:00R_473.10_AULAPRBB Computational Genomics SeminarsNaomi WrayUniversity of Oxford"Investigating heterogeneity in major depression using genetics and omics"Abstract:Major depressive disorder (MDD) is recognised to be phenotypically heterogeneous, yet subtyping based on clinical features has remained elusive. I will review recent work in genetics and genomics of MDD. Briefly. genome-wide association studies (GWAS) have now discovered hundreds of associated variants, through combining phenotypically diverse data sets. Integration of GWAS results with single-cell RNAsequencing data infers cell-types and developmental stages where risk variants may play a functional role. Omics technologies are allowing new directions to explore standing hypotheses of...
20/11/202512:00R_473.10_AULAPRBB Computational Genomics SeminarsPeter VisscherUniversity of Oxford"Between-population genetic and phenotypic differences in complex traits"Abstract:Human populations differ in disease prevalences and in average values of phenotypes, but the extent to which differences are caused by genetic or environmental factors is unknown for most complex traits. Comparing phenotypic means across populations is confounded by environmental differences and comparisons based on polygenic predictors can lead to biased inference. Family-based analyses of genetically admixed individuals offer a powerful framework for disentangling the direct and associated effects of genetic ancestry on phenotypes. We leveraged genetic data from admixed adults in the...
04/12/202512:00R_473.10_AULAPRBB Computational Genomics Seminarstbctbctbc
18/12/202512:00R_473.10_AULAPRBB Computational Genomics Seminarstbctbctbc