Otto: Performance metrics, and 'process-matched controls'. 3. Accurate at low MAF, and high spec (PPV, no FPs) #AGBT16
8:08pm February 12th 2016 via Hootsuite
Otto: Five critical features: 1. Comprehensive. "Only one shot" - maximize the Dx yield. 2. High quality - it has to work. #AGBT16
Geoff Otto (Foundation Med): Assessment of the relative clinical utility of ctDNA for detection of actionable genomic alterations #AGBT16
8:07pm February 12th 2016 via Hootsuite
Garvin: 3 homeobox genes implicated. Assoc w/DEG - two genes PTPRN2 and SLC12A8 as measured by PFS. #AGBT16
8:00pm February 12th 2016 via Hootsuite
Garvin: Found a long list in pancreatic ductal adenocarcinoma (PDA). Assoc w/genes impt in PDA - few. But affect pathways #AGBT16
7:58pm February 12th 2016 via Hootsuite
Garvin:1/3 had expression data; GECCO is their pipeline for analysis. Many Q's to answer - CRRs with recurrent non-coding mutations #AGBT16
7:57pm February 12th 2016 via Hootsuite
Garvin: And instead of 'binding site' is 'cis-regulatory regions' (CRR). Via ICGC, 308 pts with WGS, clincial #AGBT16
7:55pm February 12th 2016 via Hootsuite
Garvin: ENCODE has 121 'xcr factors'; but they often do not bind DNA themselves. Should be called 'regulatory proteins' (RPs) #AGBT16
Garvin: .. and chr remodelers. Looking for non-coding muts - promoters, enhancers, introns. #AGBT16
7:54pm February 12th 2016 via Hootsuite
Garvin: Low 5y OS rate; most common form of panc ca. Reg genome: signaling (kinases) xcription factors (repressor/activator) #AGBT16
7:53pm February 12th 2016 via Hootsuite
Tyler Garvin (CSHL): Recurrent noncoding regulatory mutations in pancreatic ductal adenocarcinoma #AGBT16
7:52pm February 12th 2016 via Hootsuite
Seshagiri: BAP1 - BRCA-Assoc Protein 1, epigenetic regulator. OS of TP53 burden - high mutation burden fare worse #AGBT16
7:38pm February 12th 2016 via Hootsuite
Seshagiri: List of significantly mutated mesothelioma - 3 known, 7 novel. NF2: tumor supp, LOF #AGBT16
7:37pm February 12th 2016 via Hootsuite
Seshagiri:675 cell lines of RNA-seq data made available recently '15 Nature Biotech https://t.co/haivnuTAUn #AGBT16
7:36pm February 12th 2016 via Hootsuite
Somasekar Seshagiri (Genentech) Comprehensive analysis of tumors at whole tissue to single cell level #AGBT16
7:34pm February 12th 2016 via Hootsuite
Just having dessert and @nanopore sequencing at #AGBT16 - @pathogenomenick and @mattloose. Good times! https://t.co/kW9y6w7kog
6:48pm February 12th 2016 via Hootsuite
If you want to see @nanopore ‘sequence tasting’ @mattloose has a crowd at #AGBT16 https://t.co/dV7333I9I5
5:41pm February 12th 2016 via Hootsuite
.@GraveleyLab Yes - science as something of a competitive sport.
4:34pm February 12th 2016 via Hootsuite in reply to GraveleyLab
.@h2so4hurts Next best thing to being here! :)
4:33pm February 12th 2016 via Hootsuite in reply to h2so4hurts
Furlan: But Monocle could collapse into 2D, all experiments and conditions. ID'ing DEG across cell-types: 48,988 cells, 6K DEGs #AGBT16
4:32pm February 12th 2016 via Hootsuite
Furlan: Via RNA-seq, identifying structure from single-cell RNA-seq data (pretty 3D globe-style, colored PCA graph) #AGBT16
4:31pm February 12th 2016 via Hootsuite
Furlan:Can separate by flow - use 10X get 2K cells/sample Cole Trapnell dev SW called Monocle for analysis. #AGBT16
4:30pm February 12th 2016 via Hootsuite
Furlan: Single-cell approach to GVHD, using a mixed lymphocyte reaction. Harvest from 2 people - one irradiated, another dyed #AGBT16
4:28pm February 12th 2016 via Hootsuite
Furlan: GVHD: Flow can only query limited number of markers. 'Complexity of tools need to meet complexity of disease' #AGBT16
4:27pm February 12th 2016 via Hootsuite
Scott Furlan (Univ Washington) #AGBT16 Studying the immune system at scale.
4:26pm February 12th 2016 via Hootsuite
NB I need to read @cigenomics and @omicsomicsblog posts on @10xgenomics https://t.co/fHSNcz4gRa and https://t.co/JOtJ8MOYT4. Or just sleep.
4:24pm February 12th 2016 via Hootsuite
Gabriel: Used NA12878, both forms of C4 are present in b37 reference; 'allows us to directly obs phased C4 haplotypes w/o trios' #AGBT16
4:22pm February 12th 2016 via Hootsuite
Gabriel: Major schizophrenia discovery Nature '16 https://t.co/Ai8JV1tiJv on C4 association in MHC; could linked reads have helped? #AGBT16
4:20pm February 12th 2016 via Hootsuite
Gabriel: [Loose-end rescue' to resolve complex tumor re-arrangements. #AGBT16
4:18pm February 12th 2016 via Hootsuite
Gabriel: 8-11Mb phase-blocks. 125kb lengths. #AGBT16
4:15pm February 12th 2016 via Hootsuite
Gabriel: Dan MacArthur picked 4 lines with Titan muts (largest gene in the genome, most difficult to deal with). 1 ng WES #AGBT16
Gabriel T @shgoodwin1: SG: GemCode chromium seems easy to use and scalable. Do need to be gentle with long fragment input DNA #AGBT16
4:14pm February 12th 2016 via Hootsuite
Gabriel RT @TorontoGenomics: SG: working routinely with 1.2 ng DNA #AGBT16
4:13pm February 12th 2016 via Hootsuite
ICYMI: The Genome Technology of #AGBT16 https://t.co/0M98ZpOsG8
4:10pm February 12th 2016 via Hootsuite
Gabriel: Populations, Mendelian, Cancer. Rare disease / cancer can use 10X. ~30 samples processed. Goal assess bias, SNP calling #AGBT16
4:08pm February 12th 2016 via Hootsuite
Gabriel: Context of scale, comparing '06 vs '15: 60Mb vs 5Pb. From 1 human genome to 32,693 #AGBT16
4:05pm February 12th 2016 via Hootsuite
Stacey Gabriel (Broad) The power of linked long reads in human sequencing applications #AGBT16
4:03pm February 12th 2016 via Hootsuite
RT @CIgenomics: Covering the @10xgenomics launch at #AGBT16 https://t.co/mHZQXwEckA
4:02pm February 12th 2016 via Hootsuite
Schnall-Levin: Single-cell RNA-seq using bacodes for human transcriptome. PCA clusters 3 cell lines #AGBT16
4:01pm February 12th 2016 via Hootsuite
Schnall-Levin: Eml4-Alk fusion for Neimann Pick disease compound het. Stacey G, Hakon H will speak later about Titan, others #AGBT16
4:00pm February 12th 2016 via Hootsuite
Michael Schnall-Levin (10X Genomics): Chromium exome does Agilent pull-down with optimized baits, w/rescued regions #AGBT16
3:58pm February 12th 2016 via Hootsuite
RT @KMS_Meltzy: Comic Sans #BINGO #AGBT16
3:38pm February 12th 2016 via Hootsuite
Nickerson:Q:Carrier testing? A:In ClinVar is shared. #AGBT16
Nickerson: Rare Disease Day is coming Feb 29 - can you support it? https://t.co/wrN9UXzaZN #AGBT16
3:37pm February 12th 2016 via Hootsuite
Nickerson: Developng 'MyGene2' where parents of children can get involved. 'We need to think about this for cancer too' #AGBT16
3:35pm February 12th 2016 via Hootsuite
Nickerson: Social media is being used by parents of children with rare disease New Yorker https://t.co/d8EYb6DgPX the Might family #AGBT16
Nickerson: Also mentions Genotype to Mendelian Phenotype https://t.co/2Wbu7a2XUW to promote gene discovery #AGBT16
3:32pm February 12th 2016 via Hootsuite
Nickerson: Mentions GeneMatcher for those with interest in the same gene '15 ref https://t.co/LBesqkGeIJ #AGBT16
3:31pm February 12th 2016 via Hootsuite
Nickerson: What do we mis with exomes? SVs, indels, and impactful var's in non-coding regions #AGBT16
3:30pm February 12th 2016 via Hootsuite
Nickerson: Solve rates is average 55%; solve rate for recessives is 95%. Missing some variation (SVs, indels that are larger) #AGBT16
3:25pm February 12th 2016 via Hootsuite
