KK: 'Everyone is a KO': hundreds. Illustrates several indiv's w/ WGS. Points to Macarthur et al Science 2012 http://t.co/S09PxtmoQT #ASHG14
11:06am October 20th 2014 via Hootsuite
KK: LoF:a broad category; for him, truncating (nonsense SNV, frameshift indels, or splice disrupting). Natural homozygous #ASHG14
11:05am October 20th 2014 via Hootsuite
KK: 2005 Nature Genet on PCSK9 for low LDL http://t.co/bMYUwYR7RK #ASHG14
11:03am October 20th 2014 via Hootsuite
KK: 100's of examples of LoF var's over decates; but protective LoF can guide pharma dev. PCSK9 example #ASHG14
11:02am October 20th 2014 via Hootsuite
#ASHG14 Plenary: Konrad Karczewski (MGH Boston): The Human Knockout Project: systematic discovery of loss-of-function variants in humans
11:01am October 20th 2014 via Hootsuite
MT @LifeTech: Interested in Genome: Unlocking Life’s Code: The Smithsonian exhibit? Register & join us Mon PM #ASHG14 http://t.co/5MsVpO
10:20am October 20th 2014 via Hootsuite
Avail @Lifetech exhibit MT @NatRevNeph: New #free web collection on clinical appl of NGS to coincide with #ASHG14 http://t.co/MniHVOY4pQ
10:05am October 20th 2014 via Hootsuite
Obama signs “BuySecure” initiative to speed EMV adoption in the US | Ars Technica http://t.co/t5KLQHJiRg
9:10am October 20th 2014 via Hootsuite
Nov 17 at the Smithsonian: Bill Nye: Why Evolution Is Undeniable - Smithsonian Associates http://t.co/Sq2rUuZBlN
8:10am October 20th 2014 via Hootsuite
.@christian_buhay Hi Christian - for sure! If you are free tonight (Mon) we have a social event at a science museum http://t.co/lHoJ9QFB8r
8:01am October 20th 2014 via Hootsuite in reply to
RT @LifeTech: BTW: Most used word today on Twitter today at #ASHG14 - DATA #notsurprised
6:25am October 20th 2014 via Hootsuite
RT @HistoryInPics: The "shadow" of a Hiroshima victim, permanently etched into stone steps after the 1945 atomic bomb http://t.co/QY8wpewal5
5:05am October 20th 2014 via Hootsuite
RT @Forbes: Now is a great time to consider your relationship with your current boss: http://t.co/AWkaxWWL53
4:10am October 20th 2014 via Hootsuite
“Gene Drives” and CRISPR Could Revolutionize Ecosystem Management | G Church, Scientific American http://t.co/h2DRv1c2Ef
11:05pm October 19th 2014 via Hootsuite
If you are free tonight at #ashg14 we have dinner, a brief RNA-Seq presentation (by me) and the movie ‘Fury’ http://t.co/EjhoZnjA5h
9:49pm October 19th 2014 via Hootsuite
#ashg14 come to the @lifetech exhibit and take a cool photo, like this one. :) http://t.co/WfuqJJnTfX
6:08pm October 19th 2014 via Hootsuite
MS: Credits his mom: "When you get your WGS you talk with your parents a lot" #ASHG14
4:08pm October 19th 2014 via Hootsuite
MS: Want to understand how people react; much sequencing-based. Future: 'Omes and other info (sensors), iPS, goal to predict risk #ASHG14
4:07pm October 19th 2014 via Hootsuite
MS: Break down disease into biochemical components. Now: larger cohort (will talk about it on Tues.) Follow 3y, ~60 pre-diabetics #ASHG14
4:06pm October 19th 2014 via Hootsuite
MS: Gut microbiome shifts: shows shift during fever. 'Your whole system changes' - we need to think about illness system-wide #ASHG14
4:05pm October 19th 2014 via Hootsuite
MS: Lastly microbiome: with last HRV (rhinovirus) infection; looking at change in nasal microbiome. Strep. pneumoniae went up #ASHG14
MS: Damaging SNVs to paternal allele, and allele-specific methylation with important implications on gene expression #ASHG14
4:03pm October 19th 2014 via Hootsuite
MS: DNA methylation: 539 allele diff. methylated regions (DMRs); combining w/ genomic SNV info. May make better predictions #ASHG14
MS: Some other 'omes: an "IMAX movie picture of change" when sick vs. healthy. Cytokines spike 2-5d post-infection (unexplained) #ASHG14
4:00pm October 19th 2014 via Hootsuite
MS: PGx profile indicates lower metformin dose is needed. All family members are pre-diabetic (around 5.5 where 6.5 is diabetic) #ASHG14
3:59pm October 19th 2014 via Hootsuite
MS: During one RSV infection, glucose level went to 6.7 (6.5 is diabetic). Then changed diet, lifestyle, got to normal level #ASHG14
3:56pm October 19th 2014 via Hootsuite
MS: 'Your family is not a reliable method of information transfer' since you don't talk about basal cell ca. around dinner (!) #ASHG14
3:55pm October 19th 2014 via Hootsuite
MS: Showed WGS 'risk-o-gram' with @atulbutte's help; predict T2D. Basal cell ca. risk Most made sense in light of family history. #ASHG14
3:54pm October 19th 2014 via Hootsuite
MS: During healthy periods 2-3mo intervals. 3 rhinovirus, one RSV (rare in adults), 2 adenovirus. #ASHG14
3:53pm October 19th 2014 via Hootsuite
MS: Went from 40K molecules/measurements to billions. 54mo, 82 timepoints, 6 viral infections. Dense sampling during sickness #ASHG14
3:52pm October 19th 2014 via Hootsuite
MS: Metabolome (both hydrophobic/philic). >2K metabolite peaks. 62 cytokines. Antibody: the 'virome' put down, 5 microbiome sites #ASHG14
3:51pm October 19th 2014 via Hootsuite
MS: Genome, epigenome, transcriptome, proteome, cytokines, metabolome, autoantibody-ome, microbiome #ASHG14
3:49pm October 19th 2014 via Hootsuite
MS: Predicting chances for disease based upon genome & exposure to environment. 5y ago, when he moved to Stanford, it began #ASHG14
MS: Personal Omics to manage health of a 'normal' individual? Chen et al Cell 2012 paper: http://t.co/QhiQvTij7X Genome + exposome #ASHG14
3:48pm October 19th 2014 via Hootsuite
MS: Looking at enhancer var & its correlation with expression #ASHG14
3:46pm October 19th 2014 via Hootsuite
MS: Now looking at chromatin marks - Kasowski et al 2013 http://t.co/l1PI5eEaIj enhancers vary the most between individuals #ASHG14
3:44pm October 19th 2014 via Hootsuite
MS: And now can look at allele-specific exons, a "personal transcriptome" with proper exon information #ASHG14
3:41pm October 19th 2014 via Hootsuite
MS:20 tissues Sharon et al 2013 http://t.co/Ioz1teMhs2 10-14% isoforms are novel #ASHG14
3:40pm October 19th 2014 via Hootsuite
MS: 'We're doing sequencing wrong' - b/c of lack of long-read technology to do RNA seqencing. PacBio: 8kb median RL, 75K reads/lane #ASHG14
3:38pm October 19th 2014 via Hootsuite
MS: Seeing allelic expression variation changing over time, in 100's of genes #ASHG14
3:37pm October 19th 2014 via Hootsuite
MS: Traditionally researchers focus on coding variation; yet indiv / species-level differences are via regulation. #ASHG14
MS: Cites Dewey et al 2014 http://t.co/v540xzt2Hp regarding coverage issues, mosaicism in cancer #ASHG14
3:35pm October 19th 2014 via Hootsuite
MS: Accuracy: Same DNA, same inst., 60x: 3.7% & 2.4% missed between runs; 146.1K / 94.2K SNVs respectively #ASHG14
3:32pm October 19th 2014 via Hootsuite
MS: Still unaddressed: phasing genomes, accuracy and mosaicism. They've used Moleculo for 10kb virtual reads. 'Works well' #ASHG14
3:29pm October 19th 2014 via Hootsuite
MS: Needed: large database for sharing; 'recurrence is key'; functional info to determine causative variant (i.e. via stem cells) #ASHG14
3:28pm October 19th 2014 via Hootsuite
MS: About 25% success with WES; illustrates trio analysis, 3.1M SNVs apiece, 7 candidates ID. 2nd child ID via Facebook (!), NGLY1 #ASHG14
3:27pm October 19th 2014 via Hootsuite
MS:Undiagnosed diseases: 25M in US; $5M/individual/lifetime; 8% adults have genetic disorder recognized by adulthood, 0.4% births #ASHG14
3:25pm October 19th 2014 via Hootsuite
MS: Illustrates role for the proteome: Liebler et al Nature 2014 http://t.co/OpaVYhbTIC using TCGA samples #ASHG14
3:24pm October 19th 2014 via Hootsuite
MS:Work of ICGC, 49 projects, 11.3K samples (mostly WES). Illustrates how RNA-Seq can help inform esophageal ca. 21 -> 7 genes #ASHG14
3:23pm October 19th 2014 via Hootsuite
MS:NGS: cancer, mystery diseases, pre-natal work. Cancer: 10-20 driver mutations; and every cancer is unique http://t.co/JoB7Gp7y0e #ASHG14
3:20pm October 19th 2014 via Hootsuite
