#ASHG21 RB: Richard Border.
Widespread evidence of systematic bias in estimates of genetic correlation due to assortative mating.
[ I think this is the preprint. Don't hold me to it. ] biorxiv.org/content/10.110…
#ASHG21 RB: interested in characterizing what extent two traits share similarity across traits.
#ASHG21 RB: Can compute the polygenic scores for each trait and see how they compare. Or correlation of effect correlations. Many ways to look at genetic correlations.
#ASHG21 RB: We'll use effect correlation and score correlation. Expect them to be essentially the same thing. But this correlation depends on random mating. Can have trouble if mates are chosen due to phenotypic similarity. [ extremely important point ]
#ASHG21 RB: Examples include height, years of education. Across traits anxiety is cross correlated with schizophrenia and some others.
#ASHG21 RB: Knowing the spousal correlation you can do a decent job predicting genetic correlation.
#ASHG21 RB: true polygenic scores for different traits can become correlated due to similar phenotypic mate selection even if molecularly they shouldn't be correlated.
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#ASHG21 BMG: Bailey Martin-Giacalone.
Germline variants in cancer predisposition genes predict survival for children with rhabdomyosarcoma (RMS)
#ASHG21 BMG: RMS most common soft tissue cancer of childhood. Usually two subtypes. alveolar RMS (ARMS) ~80% have a PAX3/7-FOX01 fusion. Embryonal RMS (ERMS) have heterogeneous somatic mutation landscape.
#ASHG21 BMG: risk factors for survival include histology, primary site, fusion status, metastasis, age at diagnosis. tumor size. ERMS cases have better outcome. In fusion negative RMS with TP53 mutation have worse survival.
#ASHG21 JS: Jonathan Sebat.
a phenotypic spectrum of autisim attributable to... [ too fast I missed it ]
#ASHG21 JS: combined 3 cohorts. Two WGS cohorts and the SPARK study. 11k families. 37,375 individuals. Called with GATK best practices. Imputed genotypes from SPARK combined with PLINK. Calculated polygenic scores.
#ASHG21 JS: autism enriched in de novo mutations, rare inherited variants, and increased PRS scores.
#ASHG21 MO: Meritxell Oliva.
Genetic regulation of DNA methylation across tissues reveals thousands of molecular links to complex traits.
#ASHG21 MO: GTEx looks at gene expression, regulation, and its relationship to genetic variation. The v8 set has eQTL data. 15,201 RNA-Seq samples from 838 post-mortem donors. 49 tissues.
#ASHG21 MO: A mQTLs are variants associated with DNA methylation. GWAS-QTL colocalization can help prioritize the causal genes at a GWAS locus.