#ASHG21 SK: Samuel Kim.
Leveraging single-cell ATAC-seq to identify disease-critical fetal and adult brain cell types.
biorxiv.org/content/10.110…
#ASHG21 SK: need to go from disease-critical cell type identification to disease mechanism.
#ASHG21 SK: goals include to identify disease critical cell types from scATAC and impact on different cells types and different stages.
#ASHG21 SK: 28 brain traits. 6 non-brain related control traits. 4 single-cell atlases of the brain. Fetal and adult. scRNA-Seq and scATAC-Seq.
#ASHG21 SK: Use stratified LD score regression (S-LDSC). find two things. Enrichment and standardized effect.
scATAC union of per dataset open chromatin regions
[ missed the scRNA data ]
#ASHG21 SK: identified more significant disease-cell type pairs from scATAC-Seq. 13 cells types appeared in both data.
#ASHG21 SK: confirmed associations of schizophrenia, MDD and ADHD genetic associations with excitatory neuron cell types.
#ASHG21 SK: insomnia associated with photoreceptor cell type [ that's interesting ]

• • •

Missing some Tweet in this thread? You can try to force a refresh
 

Keep Current with Eli Roberson

Eli Roberson Profile picture

Stay in touch and get notified when new unrolls are available from this author!

Read all threads

This Thread may be Removed Anytime!

PDF

Twitter may remove this content at anytime! Save it as PDF for later use!

Try unrolling a thread yourself!

how to unroll video
  1. Follow @ThreadReaderApp to mention us!

  2. From a Twitter thread mention us with a keyword "unroll"
@threadreaderapp unroll

Practice here first or read more on our help page!

More from @thatdnaguy

20 Oct
#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.
Read 15 tweets
20 Oct
#ASHG21 EDF: Elisa De Franco.
loss of the primate specific gene ZNF808 causes pancreatic disease.
#ASHG21 EDF: studying human development to better understand common and rare diseases. specifically interested in diabetes.
#ASHG21 EDF: Mice can offer important insights, but there are fundamental differences between humans and mice.
Read 14 tweets
20 Oct
#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.
Read 11 tweets
20 Oct
#ASHG21 WL: Wenhan Lu.
quantifying the extent of pleiotropy using rare variant association data in 281k human exomes
#ASHG21 WL: have large scale rare variant association in UKBB exomes.
Preprint - medrxiv.org/content/10.110…
Explorer at - genebass.org
#ASHG21 WL: Interested in pleiotropy. Look at variant-level pleiotropy. 349k vars. 5.4k with > 1 phenotype. 152 associated with > 20 phenotypes.
Read 12 tweets
20 Oct
#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.
Read 7 tweets
20 Oct
#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.
Read 14 tweets

Did Thread Reader help you today?

Support us! We are indie developers!


This site is made by just two indie developers on a laptop doing marketing, support and development! Read more about the story.

Become a Premium Member ($3/month or $30/year) and get exclusive features!

Become Premium

Too expensive? Make a small donation by buying us coffee ($5) or help with server cost ($10)

Donate via Paypal Become our Patreon

Thank you for your support!

Follow Us on Twitter!

:(