lide han

[lide han @lhan111]

@bvhalldorsson Great paper. Could you share your SV calling pipeline using DRAGEN 3.7.8, along with the number of duplications detected per individual?

[Matthew Aguirre @aguirre404]

Thrilled to share the bulk of my PhD work, now up on bioRxiv!

This project brings together aspects of network theory, systems biology, and single cell genomics, towards understanding properties of gene regulatory networks (GRNs). Read on for more —> (1/)

https://t.co/RY1syLiS6S

[lide han @lhan111]

https://t.co/1AXg2A4vNs

[lide han @lhan111]

https://t.co/1AXg2A3XXU

[lide han @lhan111]

@jxchong Yes, Eagle2 is appropriate for population based data

[lide han @lhan111]

@jxchong For Eagle 2, the reference-based phasing is performed on a target set with reference panel .If Ntarget < Nref/2, Eagle2 performs only one phasing iteration. The few iteration maybe affect the accuracy

[lide han @lhan111]

@jxchong I agree. The key part for the MIS is Eagle2,a phasing algorithm. When sample size is very small, its mean switch error rate is also very high

[Vanderbilt University Medical Center @VUMCDiscoveries]

Congratulations to @NancyGenetics, director of the @VUMCgenetics, for receiving the 2023 ASHG Leadership Award from the American Society of Human Genetics (@GeneticsSociety).

https://t.co/4LVfOSI5YH

[Douglas Ruderfer @DMRuderfer]

New #preprint on transcriptional convergence in ASD led by @liao_cal with @TalkowskiLab and @kristenbrennand https://t.co/5hNLkyzYxx

[lide han @lhan111]

https://t.co/ziJdtXc6U4

[Jian Yang @jyang1981]

Ting’s paper is out. @TingQi2 Leveraging a powerful new method and large datasets, we established a comprehensive genetic regulation map of RNA splicing, which helped to reveal a distinct and essential role of RNA splicing in common traits and diseases. https://t.co/eXxHNIl3WD

[Douglas Ruderfer @DMRuderfer]

Thrilled and honored to see work led by @MorleyTheodore recognized as an important advance in genomic medicine by @AJHGNews

[Douglas Ruderfer @DMRuderfer]

Congratulations @JDMosley_Moses and @DriestSara! Great to see your important work recognized as a key advance in genomic medicine @VUMChealth @VUMCgenetics @vumcdbmi https://t.co/2lJb0IV42R

[lide han @lhan111]

@Joni_Coleman @Andrew_Grotz In my opinion, ldsc and simple linear model seems to have the similar assumption, however Regenie obtains the summary statistics with whole genome regression model

[lide han @lhan111]

I am happy to be involved in the project.

[Nature Medicine @NatureMedicine]

#Machinelearning of electronic health records identifies individuals who may benefit from #genetic testing @MorleyTheodore @DMRuderfer @lisa_bastarache @lhan111 @jonmorra8 @NancyGenetics @healthdatavic @royperlis https://t.co/zWcOiiBiZr

[Nature Medicine @NatureMedicine]

#Machinelearning of electronic health records identifies individuals who may benefit from #genetic testing @MorleyTheodore @DMRuderfer @lisa_bastarache @lhan111 @jonmorra8 @NancyGenetics @healthdatavic @royperlis https://t.co/zWcOiiBiZr

[Theodore Morley @MorleyTheodore]

Our work on systematized identification of patients who may benefit from genetic testing is now published in @NatureMedicine! I'm grateful to @DMRuderfer, @lisa_bastarache, @lhan111, @jonmorra8, @NancyGenetics, @healthdatavic, @royperlis and our reviewers!
https://t.co/FQkGYa6cca

[lide han @lhan111]

Effective gene expression prediction from sequence by integrating long-range interactions https://t.co/ziPFze6ETU

[GWAS_lit @GWAS_lit]

Polygenic Scores for Cognitive Abilities and their Association with Different Aspects of General Intelligence - a Deep Phenotyping Approach https://t.co/2K9QbtXCrN