ASHG18 tweet summary day 3
This article is originally published at http://lcolladotor.github.io/
Continuing from my ASHG18 day 1 post and day 2, here’s my list of tweets from day 3.
9:15 20BC
Jenna Carlson
Jenna Carlson @PittPubHealth: Population-specific reference panels for genotype imputation, with Samoans as an example, in Room 20BC #ASHG18
— Kevin L. Keys (@_klkeys_) October 18, 2018
Jenna Carlson: creating population-specific reference panels for improved genotype imputation #ASHG18
— Charleston Chiang (@CharlestonCWKC) October 18, 2018
JC: Genotype chips cheap, useful for global health research. Utility of imputed genotypes is key. Must invest in panels with representative populations. #ASHG18
— Kevin L. Keys (@_klkeys_) October 18, 2018
.@jenccarlson Constructed a Samoan reference panel for imputation from 1,195 whole-genome sequenced Samoans as part of TOPMed. For MAF < 0.05, Ave R^2 0.696 with TOPMed ref panel, improves to 0.872 w Samoan-specific reference panel. #ASHG18
— Daniel E. Weeks (@StatGenDan) October 18, 2018
Christopher R. Gignoux
Next is Christopher Gignoux @popgenepi on the global landscape of pharmacogenomic variation as part of their work in the PAGE study #ASHG18
— 23andMe Research (@23andMeResearch) October 18, 2018
Next in 20BC: Chris Gignoux @popgenepi @CUAnschutz will speak about the global landscape of pharmacogenomic variation. #ashg18 https://t.co/Xmqb5RIJyq
— Kevin L. Keys (@_klkeys_) October 18, 2018
Christopher Gignoux: revised version of Population Architecture using Genomics and Epidemiology (PAGE) study now on @biorxivpreprint https://t.co/t1x4qeGSkB #ASHG18
— Brooke LaFlamme (@Brooke_LaFlamme) October 18, 2018
CG: tested selection in pharmaco variants (haplotype length-based, corr with environment). Enviro-WAS takes geographic/climatic/ecological variables and cross with PAGE populations. #ASHG18
— Charleston Chiang (@CharlestonCWKC) October 18, 2018
CG (@popgenepi) describes our framework for conducting association analyses using phenotypes from NASA, World Wildlife Foundation, Berkeley Earth and GIDEON #ashg18
— Elena Sorokin (@ElenaSorokin) October 18, 2018
Q: environmental exposures taken present day. Can you look at historical environment instead?
— Kevin L. Keys (@_klkeys_) October 18, 2018
CG: want to! (who wouldn’t?) but challenging. patterns may be from 30k yr ago…
Q2: what variables?
CG: many types: pathogens, altitude, biome, air pollution, etc.#ashg18
Angela Andaleon
“It’s my pleasure to introduce to you Dr Angela Andaleon” “Not a doctor yet!” “Aspiring doctor Angela Andaleon”
^_^
Angela is presenting the continuation of her undergrad project.
Angela Andaleon: transcriptome-based association study in hispanic cohorts implicates novel genes in lipid traits. #ASHG18
— Charleston Chiang (@CharlestonCWKC) October 18, 2018
AA: Replication cohorts: MESA HIS, GLGC. Ran gene-based association test in PrediXcan, using GTEx model and MESA model https://t.co/6wuD1fQB7l #ASHG18
— 23andMe Research (@23andMeResearch) October 18, 2018
6C 10 am
Zongli Xu
Now: Z. Xu: Blood DNA methylation profiles are altered years before breast cancer diagnosis: Findings from a case-cohort analysis in the Sister Study #ASHG18
— Michael Hoffman (@michaelhoffman) October 18, 2018
Lang Wu
Now: L. Wu: Genetically predicted methylation biomarkers and prostate cancer risk: A methylome-wide association study in over 140,000 European descendants #ASHG18 https://t.co/B4y1LUzB9m
— Michael Hoffman (@michaelhoffman) October 18, 2018
LW: 1/Build CpG methylation prediction models with Framingham Heart Study data 2/Evaluate associations of genetically predicted methylation levels with prostate cancer risk using iCOGS-Oncoarray-GWAS meta results #ASHG18
— Michael Hoffman (@michaelhoffman) October 18, 2018
Hmm, why use a 0.01 \(R^2\) cutoff? Isn’t that super low? Maybe I missed something.
LW: 3/Significant associated CpG sites: assess correlations with expression of nearby genes in FHS. 4/Potential target genes: assess associations of genetically predicted mRNA expression with prostate cancer risk. #ASHG18
— Michael Hoffman (@michaelhoffman) October 18, 2018
Moving to Hawaii to start his career as a PI. He had nice pictures to motivate others to join his lab ;)
11 am 6A
Hailiang Huang
Missed it: got there for the questions.
Tarjinder Singh
Tarjinder Singh
— ?? Dr. Leonardo Collado-Torres (@fellgernon) October 18, 2018
Looking at rare variants using exome sequencing that explain schizophrenia risk.
Genes with increased risk: TRIO (loss of function) and (missed it), GRIN2A (example of common and rare variant info being concordant).
#ASHG18
They built a browser for seeing the rare variants and the exome data. Not available yet.
Rujia Dai
Rujia Dai
— ?? Dr. Leonardo Collado-Torres (@fellgernon) October 18, 2018
Cell types + schizophrenia disorder + bipolar disorder. Used psychENCODE data
Estimated cell types in different brain regions. Identified cell type-specific co-expression modules.
#ASHG18
Rujia Dai
— ?? Dr. Leonardo Collado-Torres (@fellgernon) October 18, 2018
Oligodendrocyte, microglia, neuron upper cortex, neuron deeper cortex, astrocytes
SCZD and BP are more related in the neurons from the upper cortex #ASHG18
Ying Ji
Used GTEx and BrainSpan data.
— ?? Dr. Leonardo Collado-Torres (@fellgernon) October 18, 2018
Step 1. Identified risk genes using a method from an upcoming paper at Nature Genetics by Quan Wang, Rui Chen, et al.
Step 2. Genome wide prediction: risk and background genes. #ASHG18
Ying Li
— ?? Dr. Leonardo Collado-Torres (@fellgernon) October 18, 2018
Gpred and Bpred genes (GTEx and BrainSpan) enriched for SCZD gene lists. Small overlap between them.
Used CommonMind Consortium SCZD DEGs list. Bpred tend to be upregulated in SCzD cases.#ASHG18
Bpred and Gpred genes have different expression over development: they intersect at birth.
Kiran Girdhar
Kiran Girdhar
— ?? Dr. Leonardo Collado-Torres (@fellgernon) October 18, 2018
H3K27ac and H3K4me3 modifications (ChIP-seq) + flow sorted neurons, non-neurons and homogenate data
See Girdhar et al, Nature Neuroscience (I think), 2018
#ASHG18
Kiran Girdhar
— ?? Dr. Leonardo Collado-Torres (@fellgernon) October 18, 2018
Used standard peak calling software.
Explored variation explained for each mark.
Performed differential binding analysis for each mark among SCZD cases and controls. #ASHG18
- Looked at enhancers too.
- Question from the audience about the differential shapes of the peaks between cases and controls.
- Will look at QTLs after ASHG18.
Siwei Zhang
Looked at SNPs associated with ATAC-seq data (ASoC ?).
Used CRISPR to perturbe noncoding variants linked to SCZD risk: the ASoC SNPs.
Then used single cell (10x Genomics) to measure expression.
Siwei Zhang
— ?? Dr. Leonardo Collado-Torres (@fellgernon) October 18, 2018
Looked at SNPs associated with ATAC-seq data (ASoC ?).
Used CRISPR to perturbe noncoding variants linked to SCZD risk: the ASoC SNPs.
Then used single cell (10x Genomics) to measure expression. #ASHG18
Other (morning)
#ASHG18 LE: use miRNA, TF expression, lncRNA, methylation, CNV and SNP data to predict gene expression, TF expression most important predictor then methylation then miRNA in cancer samples
— John Thompson (@Single_Molecule) October 18, 2018
Andy Clark using microbiome to improve GWAS analysis and "this is getting a bit geeky for those that like linear mixed models"... #ASHG18
— Ana Viñuela (@anavinuela) October 18, 2018
E. Davenport: phenotype ~ covariates + relatedness + microbiome <= model microbiome beta diversity as an additional random effect. Biggest microbiome var up to 25% for height, weight, BMI. Controlling for microbiome can improve power to detect phenotype/SNP association. #ASHG18
— Daniel E. Weeks (@StatGenDan) October 18, 2018
Afternoon awards
Eric Lander
Eric Lander: your #scientific #career is not the papers you publish but the people you meet. #AcademicTwitter #ASHG18
— Erin Haskell (@mycoacia) October 18, 2018
EL: The challenge ahead is to move rapidly from variants to function. "I don't want to just tell history - I think we are entering into a period that is as generative...as the period where much of the foundation was laid" #ASHG18
— 23andMe Research (@23andMeResearch) October 18, 2018
@eric_lander on career planning to trainees like myself: don’t worry too much it will mostly be happy accidents.
— Rachel Ungar (@raungar) October 19, 2018
already as a first year grad student thankful for a list of people that have led me here. #ASHG18
Jan M. Friedman
Jan Friedman is the recipient of the Arno Motulsky-Barton Childs Award for Excellence in Human Genetics for increasing genetic education in medical schools #ASHG18
— 23andMe Research (@23andMeResearch) October 18, 2018
JF: When the society was first founded, education was not a major focus. Focus was on research and on the journal publishing it. Appropriate to focus on this after WWII after the "perversion of genetics" that lead to eugenics laws - had to work to repair genetics #ASHG18
— 23andMe Research (@23andMeResearch) October 19, 2018
JF: HJ Mueller: "The two major purposes of [ASHG] were to be the furtherance of sound research in [human genetics] and the publication of [AJHG]." No mention of education. #ASHG18 https://t.co/TAp5LZzgdu
— Michael Hoffman (@michaelhoffman) October 19, 2018
Jan Friedman tells us that the medical board exams had no medical genetics questions in the 1990s. The only mentions of genetics were distractors (wrong answers). He got together a group to fix it. #ASHG18
— Avery Davis Bell (@averydavisbell) October 19, 2018
Presidential Symposium
John Hawks
Starting now the #ASHG18 Presidential address with @johnhawks speaking first about human origins
— Liz Crocker, Ph.D. (@liminalphase) October 19, 2018
#ASHG18 JH: 6 PhD students started excavating there over 28 days. Eventually one of the largest hominin finds in Africa.
— Eli Roberson (@thatdnaguy) October 19, 2018
John Hawks: Fossils are rare, and it is hard to say novel things about them if you don't find them. So I did what any of you would have done; went into genetics! #ASHG18
— Joanna L Cross (@photoandauthor) October 19, 2018
.@johnhawks Three main points 1) humans emerged over a long period between 200-350kya 2) there was deep long lasting diversity across that timespan 3) pops w/ very ancient roots survived until very recently & we don't fully know their relationship(s) to us #ASHG18
— Liz Crocker, Ph.D. (@liminalphase) October 19, 2018
Human evolution definitely absolutely most certainly doesn’t look like those t-shirt cartoons. @johnhawks just introduced us to MANY diverse hominins. So cool to meet you, guys. #ASHG18
— Julija Hmeljak (@JHmeljak) October 19, 2018
Himla Soodyall
Now: Himla Soodyall: Reconstructing the prehistory of Africa: the narrative of the genes. "Greetings, fellow Africans." #ASHG18
— Michael Hoffman (@michaelhoffman) October 19, 2018
Himla Soodyal: Theory of “Out Of Africa” origins for the human species dismisses that evolution in Africa is forever continuing. #ASHG18 “It’s time to celebrate Africa”
— Claudia Gonzaga-J (@cgonzagaj) October 19, 2018
HS: Genomic Variation in Seven Khoe-San Groups Reveals Adaptation and Complex African History. STRUCTURE plots. There are no "pure" populations. "We are all mongrels." cc @amy_harmon #ASHG18 https://t.co/Psu3b2lRe3 pic.twitter.com/ILvGcksS4I
— Michael Hoffman (@michaelhoffman) October 19, 2018
#ASHG18 HS: more information when they started adding in SNP genotyping. Things are different now. Can get on a flight, go somewhere far away quickly, and leave your genes there.
— Eli Roberson (@thatdnaguy) October 19, 2018
#ASHG18 HS: In South Africa you have to apply for a research permit from the San if you are going to work with them. Not just about the sample. Contextualizing the place and role of communities in our research.
— Eli Roberson (@thatdnaguy) October 19, 2018
Appreciate reminder to think about the societal value of science, and to conduct yourself (and the research) accordingly. #ASHG18
— Cathy Long (@yhtacgnol) October 19, 2018
Ambroise Wonkman
AW: Story of the curse of Chief K. Actually turned out to be Fragile X Syndrome. #ASHG18
— Michael Hoffman (@michaelhoffman) October 19, 2018
AW: researchers coming to Africa for genetics research are mostly interested in population genetics, not genetic medicine #ASHG18
— Genome Biology (@GenomeBiology) October 19, 2018
Diversity
The diversity of participants we see at #ASHG18, shows how different we are, yet similar and genetically the same as #Human #HumanGenetics #UnityinDiversity
— Dr. Swarkar Sharma (@sawerkar) October 18, 2018
.@simon_r_myers standing in for Sinan Shi in session 43 because speaker couldn’t get his visa. Hearing this far too much ? #ASHG18
— Brooke LaFlamme (@Brooke_LaFlamme) October 18, 2018
#MAGA deal with it, foreigner.
— Tom Segal (@tomsegal) October 18, 2018
Trolls :/
This is sort of a silly thing to say, but after attending so many conferences that are predominantly male (cough, JP Morgan, cough) it’s actually nice to wait in line, behind so many scientists, in the ladies room. #ashg18
— Meghana Keshavan (@megkesh) October 18, 2018
Echoing yesterday's NSGC GC roundtable, a reminder that genomics is failing diversity. How do we do better? #ASHG18 #gcchat
— Cathy Long (@yhtacgnol) October 19, 2018
Misc
May recommend speakers not perform an awards ceremony for “everyone that made this research possible”? Not a great use of time.
— Mark T. W. Ebbert (@bioinfo_mark) October 18, 2018
Put their names up, bold them, or even include pictures.
I liked how @dgmacarthur lab included pictures of individuals on specific slides.#ASHG18
Good morning #ASHG18 tweeps! Help us spread the word about our travel grants for #ECRs. Award will be paid soon after winner announcement. No need to wait for reimbursement. Applications due Nov 5 https://t.co/JoJxIGwY9b
— Brooke LaFlamme (@Brooke_LaFlamme) October 18, 2018
Presenters: please include a short (even if it's 1 sentence) lay description of the esoteric statistical and computational models that form the basis of your methods #ASHG18
— Basel Al-Barghouthi (@basel_bargho) October 18, 2018
This is hard. Some don’t mention the methods to avoid this issue, but then it becomes a “black box”. I guess that it can also be a “black box” if they don’t explain a bit what the model is/does. /shrug
*takes a big ol' bite of beef jerky* REMEMBER FOLKS, TAKIN' PHOTOGRAPHS O' SOMEONE ELSE'S SLIDES WITHOUT PERMISSION IS A BREACH OF PROFESSIONAL ETHICS #ASHG18 https://t.co/CG0Y1pCvQ1
— The Sheriff of ASHG (@genome_sheriff) October 18, 2018
#ashg18 #ASHGtrainee For presenters, this might be helpful especially for the big rooms:https://t.co/KVuIXRytYW
— Alon Goren (@alon_goren) October 18, 2018
Maybe too soon to say this, but @genome_sheriff is the best emoji-based wild west hyperbole novelty account I've ever seen at a genetics conference #ashg18
— Erick Loomis (@ErickLoomis) October 18, 2018
"our code is on github and our preprint is up on bioRxiv" - things I love hearing during #ASHG18 talks. Instant credibility boost.
— Daniel MacArthur (@dgmacarthur) October 18, 2018
On our way to the presidential address. #scooters #ASHG18 pic.twitter.com/UrtAuoD2jd
— Audrey Hendricks (@hendricks_ae) October 19, 2018
Still can't get over that almost 9,000 people are here! Absolutely amazing. #ASHG18
— John Morris (@johnm09) October 19, 2018
As always please feel free to correct anything I got wrong! Thanks @splon #ASHG18 https://t.co/hmRGx5CuM1
— Michael Hoffman (@michaelhoffman) October 19, 2018
Acknowledgements
This blog post was made possible thanks to:
- BiocStyle (Oleś, Morgan, and Huber, 2018)
- blogdown (Xie, Hill, and Thomas, 2017)
- knitcitations (Boettiger, 2017)
- sessioninfo (Csárdi, core, Wickham, Chang, et al., 2018)
and everyone that I met at the tweetup
#ASHG18 pic.twitter.com/8RJh35VzeO
— Michael Hoffman (@michaelhoffman) October 19, 2018
tweeting up at a dueling piano bar at #ASHG18 pic.twitter.com/QccDcZ8si6
— Lisa (@meandertail) October 19, 2018
References
[1] C. Boettiger. knitcitations: Citations for ‘Knitr’ Markdown Files. R package version 1.0.8. 2017. 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 1.1.0.9000. 2018. URL: https://github.com/r-lib/sessioninfo#readme.
[3] A. Oleś, M. Morgan and W. Huber. BiocStyle: Standard styles for vignettes and other Bioconductor documents. R package version 2.8.2. 2018. 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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## [1] /Library/Frameworks/R.framework/Versions/3.5/Resources/libraryThanks for visiting r-craft.org
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