Rubin: John Snow (influenza, 1918) would consider today's world to be dangerous; 'lots of kindling'. #AGBT17
11:21am February 14th 2017 via Hootsuite
Rubin: Like a wildfire - quicker to detect and respond is critical, to prevent widespread impact. #AGBT17
11:18am February 14th 2017 via Hootsuite
Rubin: Idea is to make vaccines against core proteins against bad viruses, but need in-country capabilities, surveillance. #AGBT17
11:17am February 14th 2017 via Hootsuite
Ruby: Why do this $1B, ten-year project? To convert virology into a data-rich field. 'It is now a mom-and-pop industry' #AGBT17
11:16am February 14th 2017 via Hootsuite
Thanks @SwiftBioSci for the #agbt17 refreshments! (The shirts sure are popular.) https://t.co/PEg3gQ2A1w
Rubin: Describes Predict project, 14 viral families, discovered 1K viruses; 80% novel (Some info: https://t.co/UW42SLh2Fc ) #AGBT17
11:13am February 14th 2017 via Hootsuite
Eddy Rubin (Metabiota CA) The global virome project #AGBT17
11:11am February 14th 2017 via Hootsuite
Cool Lego figurines at #AGBT17 @PacBio suite 317. NB - Sequel is not to scale. https://t.co/SHZXW9a1Ej
10:35am February 14th 2017 via Hootsuite
Q:Panels or WGS or WES? Jones: Didn't show the data behind their choice, but they wanted to build a cohort to ask the Q's #AGBT17
10:28am February 14th 2017 via Hootsuite
Jones: Pt given first-line br ca Rx. Showed BRCA signature, positioned for cisplatin Rx. #AGBT17
10:27am February 14th 2017 via Hootsuite
Jones: Stg IV Lung ca, treated w/carbotaxol 4 cycles, re-diagnosis as extra-mammary breast cancer, Her+, APOBEC sig, ERBB2 amp #AGBT17
10:22am February 14th 2017 via Hootsuite
Jones: Leverages public sources, shares their findings via WashU's CIViC https://t.co/uehYtZQk6x #AGBT17
10:15am February 14th 2017 via Hootsuite
Jones: 17d sample prep, 6d TAT for NGS. Complex pipeline diagrammed. 'All of that in green was custom-developed for POG' LOG, sig's #AGBT17
10:14am February 14th 2017 via Hootsuite
Jones: Able to publish on rare cancer types due to this kind of analyses. Shows day 1 to 17 sample prep workflow thru path rev #AGBT17
10:12am February 14th 2017 via Hootsuite
Jones: Genes downstream of AP-1 are upregulated. Some evidence blood pressure med ibesartan '16 ref https://t.co/cNYErUbEGS #AGBT17
10:10am February 14th 2017 via Hootsuite
Jones: MLH1 del BRAF wt (IHC), enrolled 9/14 (before checkpt inh.) Transcriptome showed FOS-JUN AP1 complex overexpressed #AGBT17
10:08am February 14th 2017 via Hootsuite
Jones: 5x HiSeqX, 4x 2500's, 2x NextSeq. 524 sequenced to-date; 509 analyzed (41 pediatric). One case: CR Stg III, chemo AE #AGBT17
10:07am February 14th 2017 via Hootsuite
Jones: Accessible cohorts of fresh-frozen samples, detailed annotation, most from primary untreated, serial samples are rare #AGBT17
10:05am February 14th 2017 via Hootsuite
Jones: In Canada, est 25K new cases in '14, >10K metastatic. Integrating WGS/RNASeq to affect cancer care #AGBT17
Martin Jones (British Columbia Cancer Agency CAN) Taking whole genomics to the cancer clinic #AGBT17
10:02am February 14th 2017 via Hootsuite
RT @shgoodwin1: OP - path of zika to us. Brazil to Caribbean to Florida. Cruise ship tourism likely route of transmission. #agbt17
10:01am February 14th 2017 via Hootsuite
Carvalho: Claims it is cost-efficient, 'suitable for early detection'. #AGBT17
9:24am February 14th 2017 via Hootsuite
Carvalho: Also subtypes of Br ca - ER+, HER+, ER/PR+, TNBC by methylation pattern. Also Lung ca - FLT3-ITD status by methylation (!) #AGBT17
9:23am February 14th 2017 via Hootsuite
Carvalho: Now actively working on being able to classify tissue of origin by methylation pattern in cfDNA #AGBT17
9:22am February 14th 2017 via Hootsuite
Carvalho: Shows methylation profile from this '14 ref https://t.co/418txoazUz but methyl arrays are underpowered as done by TCGA #AGBT17
9:21am February 14th 2017 via Hootsuite
Carvalho: Looks at hyper- and hypo-methylated sites, infer active transcriptional factor networks #AGBT17
9:19am February 14th 2017 via Hootsuite
RT @melaniesinche: Check it out--@jacksonlab is hiring at #agbt17! https://t.co/2UzawiF1D5
9:17am February 14th 2017 via Hootsuite
Carvalho: Training set uses a few thousand DMRs, shows 100% ROC; Test set of 35 cases/controls #AGBT17
Carvalho: 38K DMRs (differentially methylated regions) - shows data Cp methlyation profile in normal/tumor tissue vs plasma #AGBT17
9:15am February 14th 2017 via Hootsuite
Carvalho: Used PDx (pt-derived xenograft) model to demonstrate enrichment of ctDNA (2x from 1% to 2% detected) #AGBT17
9:13am February 14th 2017 via Hootsuite
RT @mason_lab: Cell free methylation DNA Immunoprecipitation (cfMeDIP-seq) from D De Carvahlho, similar to https://t.co/FRCkhbuS3S #agbt17
9:12am February 14th 2017 via Hootsuite
Carvalho: Cp their method against RRBS of cfDNA; by interrogating more features can exceed limitations of barcoding #AGBT17
Carvalho: Challenges - low amt. Doing a version of MeDIP - pull-down of methylated DNA. Add 'filler' lambda DNA to up the input #AGBT17
9:10am February 14th 2017 via Hootsuite
Carvalho: Shows unpub data of sens (probability of det) against LoD - down to 0.01% as a function of depth (theoretical calc) #AGBT17
9:08am February 14th 2017 via Hootsuite
Carvalho: At ASCO2016, Pathway genomics indicates 6/42 stg I had one pos mutation above LoD #AGBT17
9:06am February 14th 2017 via Hootsuite
Carvalho: Detection needs to go down way below 1%. (Note: @SeraCare has reference materials: https://t.co/YjV6rUwPQW ) #AGBT17
Carvalho: Into using fig from '13 https://t.co/AGX5kOpvhM to describe liquid biopsy ctDNA detection #AGBT17
9:04am February 14th 2017 via Hootsuite
Daniel De Carvalho (Princess Margaret Cancer, CAN) Highly sensitive tumor detection, classification using plasma DNA methylome #AGBT17
9:02am February 14th 2017 via Hootsuite
Hey #agbt17 you need to check out @QIAGEN in 313 - not bad! (See photo.) https://t.co/dayyQLt9N0
7:36am February 14th 2017 via Hootsuite
Also great to meet new people from @bcmhouston @ChildrensMercy @AgilentGenomics at #AGBT17 (you know who you are)
6:34am February 14th 2017 via Hootsuite
Great to see @RocheSequencing as well as meet former and current @AppliedBio @iontorrent and @illumina developers last night at #AGBT17
6:31am February 14th 2017 via Hootsuite
Hi #AGBT17 @masonlab will do an interpretive dance before Thursday's 230pm talk if this gets to 100 RT's. @coregenomics @DeciBio
6:26am February 14th 2017 via Hootsuite
Q: How much missing data in s.c. data? Greenleaf: Aggregates across lots of sites in the same cell, getting around drop-out prob #AGBT17
7:14pm February 13th 2017 via Hootsuite
Q: GWAS connection? Greenleaf: TF data, is there larger GWAS hits for association? #AGBT17
7:13pm February 13th 2017 via Hootsuite
Greenleaf: Can ID transitional and re-activatable regulatory elements - some complex axes along w/colors for 3rd dimension for mark #AGBT17
7:12pm February 13th 2017 via Hootsuite
RT @ScienceJill: .@WJGreenleaf Hematopoiesis Rorschach Test -> Do you see the "manta ray"? #ATACseq #agbt17 https://t.co/c1sdgJilQS
7:08pm February 13th 2017 via Hootsuite
Greenleaf: Looks at cis-acting elements - accessibility, looking at regions that correlate to open-ness. Showing CCC vs ATAC-seq #AGBT17
7:01pm February 13th 2017 via Hootsuite
Greenleaf: Able to show Nanog in eSCs, single-cell variability defining celltypes, revealing trans-factor noise in single-cells #AGBT17
6:59pm February 13th 2017 via Hootsuite
Greenleaf: Shows dynamic range of 0 to 2: representing two copies of DNA in a single-cell. #AGBT17
6:57pm February 13th 2017 via Hootsuite
Greenleaf: Down to single-cell: due to TFs can vary dramatically. Collaborating with @fluidigm '15 ref https://t.co/gKIYlZbagf #AGBT17
6:56pm February 13th 2017 via Hootsuite
