ASHG18 tweet summary day 5
This article is originally published at https://lcolladotor.github.io/
Continuing from my ASHG18 day 1 post, day 2, day 3 and day4 here’s my list of tweets from day 5.
6C 9:15 am
Jane Loveland
Wish that gene annotation was consistent across databases? Jane Loveland is speaking about the new #MANE project which aims to converge transcript annotation between @GencodeGenes and @NCBI RefSeq in 30 min 09:15-09:30, Room 6C, Talk 302 #ASHG18
— Ensembl (@ensembl) October 20, 2018
Jane Loveland: there are two comprehensive transcript annotations, RefSeq and Gencode. Clinical labs use RefSeq, basically everyone else (e.g. gnomAD, GTEx) uses Gencode. Describes the MANE project to unify these annotations. #ASHG18
— Daniel MacArthur (@dgmacarthur) October 20, 2018
Jane Loveland
— ???????? Leonardo Collado-Torres (@lcolladotor) October 20, 2018
Annotation project leader. #MANE project is based on GRCh38
Matched Annotation NCBI and Ensembl (I think)
Looking for “longest strong” transcripts
Want stable yet updatable pipeline
Many challenges!
#ASHG18 @ensembl @NCBI
Jane Loveland
— ???????? Leonardo Collado-Torres (@lcolladotor) October 20, 2018
Goals for Phase 2: update remaining 47% genes
Challenges: missing data for some genes!
No cage
No polyA
No … (missed it)
A to audience Q: Once they select a transcript, they’ll keep it. #ASHG18
.@princyparsana asked Jane Loveland about overlapping genes. They are addressing this issue! #ASHG18
— ???????? Leonardo Collado-Torres (@lcolladotor) October 20, 2018
6B 10 am
Genevieve Stein-O’Brien
Genevieve Stein-O'Brien describing her package CoGAPS - in Bioconductor - to learn both discrete and continuous axes in single cell data. #ASHG18
— Nick Banovich (@NeBanovich) October 20, 2018
Yu Hu
Yu Hu
— ???????? Leonardo Collado-Torres (@lcolladotor) October 20, 2018
On using single cell RNA-seq data for detecting differential splicing events
Presented SCATS and compared to MISO derived results
Can we recover cluster pattern?
Check sensitivity
SCATS is his thesis projecthttps://t.co/1c52ulw6e3#ASHG18
Mingyao Li and Nancy Zhang were his advisors.
Hierarchical model with normal + (missed it) + log + poisson
20 BC 10:30 am
Stephanie Kravitz
@snkravitz Our textbook model of gene expression is that each parental allele is expressed equally. That is, biallelic expression. However, both genetic and epigenetic mechanisms can lead to monoallelic expression; one or mostly one allele is expressed instead of both.
— Aaron Quinlan (@aaronquinlan) October 20, 2018
#ASHG18
@snkravitz Her goal is to identify autosomal genes that exhibit monoallelic expression.#ASHG18
— Aaron Quinlan (@aaronquinlan) October 20, 2018
@snkravitz Low madRD indicates biallelic expression. High madRD indicates monoallelic expression. madRD robustly distinguishes genes on the X from autosomal.#ASHG18
— Aaron Quinlan (@aaronquinlan) October 20, 2018
@snkravitz Goal is to build a map of tissue-specific genes that exhibit monoallelic expression. Distinguish genetic (e.g., eQTL) and epigenetic effects.
— Aaron Quinlan (@aaronquinlan) October 20, 2018
How does allelic expression modulate the penetrance of disease alleles?#ASHG18
Li Chen
Li Chen
— ???????? Leonardo Collado-Torres (@lcolladotor) October 20, 2018
Looking at eQTL associations with SNVs.
Developed TIVAN pipeline for fine mapping eQTL SNVs. Compared against other methods.
Used GTEx v7 data + eQTL data from other studies (missed the full list)#ASHG18
Li Chen
— ???????? Leonardo Collado-Torres (@lcolladotor) October 20, 2018
Tested model using:
* Cross validation
* Leave-One-Chromosome-Out (LOCO strategy); means crazy ???? in Spanish ???????? ???????? #ASHG18
Li Chen handled very well a question on “have you compared to X new paper?” with “great question, paper X didn’t come up in our literature review but we’kk look into it”
— ???????? Leonardo Collado-Torres (@lcolladotor) October 20, 2018
Li Chen also gave a shoutout to his trainee in computer science who did most of the work #ASHG18
Nicholas Bogard
Nicholas Bogard
— ???????? Leonardo Collado-Torres (@lcolladotor) October 20, 2018
Last talk of the conference! ????????
Using a Deep Neural Net with lots of data. ????
Looked a PolyA signal (PAS) sequence.
Built a APA reporter library (generated over 3 million unique PAS)
Built APARENT: APA regression net with computational collaborator#ASHG18
Nicholas Bogard
— ???????? Leonardo Collado-Torres (@lcolladotor) October 20, 2018
Looked at predicted results from APARENT and proximal/distal PAS (pPAS/dPAS). SNVs, ClinVar, CES (a short sequence) mutation impact
Also looked at the distribution of predicted cuts#ASHG18
Other
Plewcczynski #ASHG18 Now collab with JAX; 4D Nucleome NIH project described here https://t.co/CP6ZmPR1ta Sequence infl chromatin structure
— Dale Yuzuki (@DaleYuzuki) October 20, 2018
.@tuuliel discussed v8 of GTEx release which should be out this coming winter. ~17K samples, 54 tissues, 838 donors. 24K eQTLs but only <200 trans-eQTLs. #ASHG18 #ASHG2018
— Jason Miller (@JEMgenes) October 20, 2018
DW: PsychENCODE and other consortia genomics data integrated to understand functional genomics of brain disorders. Brain transcriptome and epigenome, single-cell data, QTL data. Build a deep neural network to predict disorders #ASHG18
— Michael Hoffman (@michaelhoffman) October 20, 2018
.@taibo_li introducing biological networks as a data structure in his single cell co-expression network talk. Tool (with cute cat mascot): https://t.co/fX1aF1FJxQ #ASHG18
— Avery Davis Bell PhD (@averydavisbell) October 20, 2018
Diversity
As I was leaving, I said that I was off to visit the poster of an old PhD student in my lab. He asked, “Your lab?” and I clarified that no, I meant the lab I worked in. He then responded, “That makes sense - you’re too hot to be a PI!” 2/5
— Jacqueline Dron (@jsdron) October 20, 2018
If you want, you can still do something now. Like find his name from the app map/poster number, double check on google, then report him. See https://t.co/Lwb70wbqLo for info on how to report this person.
— ???????? Leonardo Collado-Torres (@lcolladotor) October 20, 2018
Though I can understand if you don’t want to relieve this exp. #ASHG18
We are so very sorry to hear of this, and encourage you to report violations of our code of conduct through our online system: https://t.co/4j0ChnHbXW Reports will be taken seriously and addressed in a timely manner.
— ASHG (@GeneticsSociety) October 20, 2018
SOMEONE MIND CLUIN' ME IN ON WHAT A 'BUZZ WORD' IS?? SOUNDS LIKE BUZZARD, BUT I KNOW THEM ARE ONLY RESERVED FER THE CARCASSES OF NO GOOD SCOUNDRELS THAT GO 'ROUND HARASSIN' WOMEN TRAINEES AT THEIR POSTERS. #ASHG18 https://t.co/dGHtEFNm1L
— The Sheriff of ASHG (@genome_sheriff) October 20, 2018
Take home message of #ASHG18 is we need more #GWAS for different populations!
— Şeyma Katrinli (@SeymaKatrinli) October 20, 2018
"Genomics has a diversity problem" - genetic #diversity in #GWAS peaked and stagnated in 2014, more diverse GWAS and new methods are needed to avoid potential for #polygenicriskscores to increase #healthdisparities @GeneticsSociety #ASHG18 pic.twitter.com/bWy34u0qp1
— Terence Wong (@terencecwong) October 20, 2018
Misc
Am I the only person that prefers ‘protein truncating variant’ instead of ‘Loss of function’? So many great talks/examples at #ASHG18 where LOF is not an accurate description but LOF still seems to be the default name.
— Janson white (@JansonWhite) October 20, 2018
LOL I'm not typing that equation #ASHG18
— Michael Hoffman (@michaelhoffman) October 20, 2018
It is so fun seeing big, confident smiles on the faces of trainees after giving a great talk. The best.#ASHG18
— Aaron Quinlan (@aaronquinlan) October 20, 2018
From Ambrose Wonkam on genetic medicine research in Africa, to @genetisaur & @barbara_dutty on probs calculating PRS with euro data in non-euro’s, and Azeez Butali’s cleft palate GWAS, one main #ashg18 takeway is the value of genomic research in African populations @AfSHGenetics
— Sarah Spendlove (@spendlove_sarah) October 20, 2018
How can I take a computational talk serious if the first slide has a 3D pie chart? #ASHG18
— Wouter De Coster (@wouter_decoster) October 20, 2018
#ASHG18 Nathan Abell says wet lab + dry lab = moist lab.
— Testing enthusiast (@apicoplast) October 20, 2018
#ASHG18 do bioinformatic methods have to have all-caps names? Why are our method yelling?
— Testing enthusiast (@apicoplast) October 20, 2018
???? ???? ????????
— The Sheriff of ASHG (@genome_sheriff) October 20, 2018
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???????????????? ????????
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???????? ????????
HOWDY, I'M THE SHERIFF OF HORIZONTAL GENE FLOW #ASHG18
The end
And that’s a wrap!
LCG present at #ASHG18 ???????? Great to catch up! @lcgunam @CinthyaZepeda @AleMedinaRivera @fellgernon @mariaGTAC @cgonzagaj pic.twitter.com/LadvPtaFur
— Claudia Gonzaga-Jauregui (@cgonzagaj) October 20, 2018
Acknowledgments
This blog post was made possible thanks to:
References
[1] C. Boettiger. knitcitations: Citations for ‘Knitr’ Markdown Files. R package version 1.0.10. 2019. URL: https://CRAN.R-project.org/package=knitcitations.
[2] G. Csárdi, R. core, H. Wickham, W. Chang, et al. sessioninfo: R Session Information. R package version 1.1.1. 2018. URL: https://CRAN.R-project.org/package=sessioninfo.
[3] A. Oleś, M. Morgan, and W. Huber. BiocStyle: Standard styles for vignettes and other Bioconductor documents. R package version 2.14.4. 2020. URL: https://github.com/Bioconductor/BiocStyle.
[4] Y. Xie, A. P. Hill, and A. Thomas. blogdown: Creating Websites with R Markdown. ISBN 978-0815363729. Boca Raton, Florida: Chapman and Hall/CRC, 2017. URL: https://github.com/rstudio/blogdown.
Reproducibility
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