GJ: Incidental findings 'is what all labs will need to be good at'. #AGBT15
9:16am February 27th 2015 via Hootsuite
GJ: Biased toward overcalling var's. In the end final calls had very good match with SCRP, LMM projects #AGBT15
9:15am February 27th 2015 via Hootsuite
RT @bioinformer: GJ: criteria for pathogenic variants at CSER #AGBT15 @HAIL_CSER http://t.co/oaBjeKzJTm
9:13am February 27th 2015 via Hootsuite
GJ: Caveats - no CNV included. 'Very interesting about this: QC'. 53 reviewers, online training; 'errors at all expertise levels' #AGBT15
GJ: Cites Amendola Genome Res '15 http://t.co/hc0fow9Az9 Expected rate of actionable var's by ancestry N=4300 / 2203 (EU/AF) #AGBT15
9:12am February 27th 2015 via Hootsuite
GJ: Came up with 112 actionable genes; showed overlap with ACMG list (they selected only the more prevalent ones) #AGBT15
9:10am February 27th 2015 via Hootsuite
.@bioinfomagician Yes but for one year it'll be a nice change-up. Expect lots of mouse-ears, reminiscent of ABRF a few years ago #AGBT15
9:07am February 27th 2015 via Hootsuite in reply to
CJ: >200 clinicians; @hail_cser is their handle. (IMHO as a marketer that's an interesting choice.) #AGBT15
9:06am February 27th 2015 via Hootsuite
CJ: CSER explores in a clinical setting the application of genomic data http://t.co/4tnHx3dxgP #AGBT15
9:05am February 27th 2015 via Hootsuite
Gail Jarvik, Univ Washington: Clinical Genomics: Lessons From the Clinical Sequencing Exploratory Research (CSER) Consortium #AGBT15
9:04am February 27th 2015 via Hootsuite
Listen up, kids! RT @MySOdotCom: Why Productive People Take Better Notes http://t.co/sg4DNSgvmh via @FastCompany http://t.co/kWvvFIvXYW
7:25am February 27th 2015 via Hootsuite
Lessons from a High School Student: Motivation + Perseverance = Success | NIH Director's Blog http://t.co/AHXHlooJ1o
7:20am February 27th 2015 via Hootsuite
.@obahcall Awesome time with @nelsondl @h2so4hurts @illumina @splon and @GenomeLiberty! Alas, no photos of feet
5:58am February 27th 2015 via Hootsuite in reply to
RT @pathogenomenick: Just finished my second genome with the new @nanopore assembly strategy ... this time GC ~35%
5:15am February 27th 2015 via Hootsuite
RT @matthewherper: How to Develop New Antibiotics http://t.co/J9yUu9vx9T Zeke Emanuel says we need a $2 BILLION per company prize.
4:30am February 27th 2015 via Hootsuite
RT @msgbi: In Mysterious Pattern, Math and Nature Converge | Quanta Magazine #math394 http://t.co/D8Etq6Havj
11:40pm February 26th 2015 via Hootsuite
Order in which mutations in cancer crop up affect disease progression | GenomeWeb Scan http://t.co/OblexCuC4l
10:10pm February 26th 2015 via Hootsuite
MS: Future goals: det differences in asthmatics vs healthy; det biomarkers & pathways specific to resp virus #AGBT15 http://t.co/BI0XHl9
9:28pm February 26th 2015 via Hootsuite
MS: Low-depth polyA-WT seq can be used to 'detect nearly all common resp viruses'; simultaneous w/ host transcriptome #AGBT15
9:27pm February 26th 2015 via Hootsuite
MS: Building co-expression models, found seven modules w/ WGCNA #AGBT15
9:26pm February 26th 2015 via Hootsuite
MS: Showed nice heatmap between virus / no virus. Many GO hits for viral infection #AGBT15
9:25pm February 26th 2015 via Hootsuite
MS: Asymptomatic virus carriage is ass'd with dramatic shift in host transcriptome. Found 5k genes diff exp >2-fold #AGBT15
MS: 100 reads to 164K reads/smpl; none of the chemokine low samples had virus #AGBT15
9:24pm February 26th 2015 via Hootsuite
MS: Did low-depth RNA-seq on @iontorrent Proton; 10M reads/sample, poly-A Kapa protocol; found 11 chemokine high all had virus #AGBT15
9:23pm February 26th 2015 via Hootsuite
MS:Affect on host transcriptome: did qPCR on two most highly induced genes (both chemokines). Most very low exp; 11 were very high #AGBT15
9:22pm February 26th 2015 via Hootsuite
MS: Read depth seemed uniform across diff transcripts. Can determine virus strain, 'from all we're finding' #AGBT15
9:20pm February 26th 2015 via Hootsuite
MS:100M reads/sample; 10 asthmatic samples, 10 ctls. Found viral reads in 2 ctrl samples. 3.1K viral reads / 140M; 1.2K / 112M #AGBT15
9:19pm February 26th 2015 via Hootsuite
MS:Listed many common resp viruses: rhinovirus, coronavirus, RSV, influenza etc. All RNA viruses #AGBT15
9:17pm February 26th 2015 via Hootsuite
MS: Looking for viral RNA (asymptomatic). Community-based recruitment; ask whether host transcriptome affected. #AGBT15
9:16pm February 26th 2015 via Hootsuite
MS: GALA - large nasal airway study in Latino asthmatics (Puerto Rico). Nasal specimens from 700. RNA + DNA; doing polyA RNA-Seq #AGBT15
9:15pm February 26th 2015 via Hootsuite
MS: Respiratory viruses - play a role in disease onset. RSV inf has OR 2.6; HRV OR 9.8. URTI affects lower airway #AGBT15
9:14pm February 26th 2015 via Hootsuite
MS Cells that line airway important - cilia + goblet mucus-prod cells; asthma is GxE interactions. #AGBT15
9:12pm February 26th 2015 via Hootsuite
MS Airway epithelium - using RNA-seq to also look at respiratory viruses. Asthma is an airway disease w/ complex etiology #AGBT15
9:11pm February 26th 2015 via Hootsuite
Max Seibold, National Jewish Health “Integrated RNA-Seq of Host and Microbe in the Nasal Airway of Childhood Asthmatics” #AGBT15
9:10pm February 26th 2015 via Hootsuite
RL: Not solved yet but steps made toward original aim. Microfluidics not yet, want to speed up library prep and make mobile. #AGBT15
9:07pm February 26th 2015 via Hootsuite
RL: Showed embedded Raspberry Pi movie, w/ same analysis for field deployment. #AGBT15
9:06pm February 26th 2015 via Hootsuite
RL: Best fragment size on the order of 500-2kb length #AGBT15
RL: Opt yield: don't need very long reads for this application; took lambda HindIII digest, seq on MinION shows reads/length #AGBT15
9:05pm February 26th 2015 via Hootsuite
RL: Greenhouse, outside tree air sampled; findings were consistent. #AGBT15
9:04pm February 26th 2015 via Hootsuite
RL: Venn diagram of spp counts: 1391 illumina, 41 oxford, 99 common. #AGBT15
9:03pm February 26th 2015 via Hootsuite
RL: Air-seq: 100-300L air/min; 10^9 enrichment; 1000L air -> 1ul DNA. illumina lib -> @nanopore library #AGBT15
RT @GenomeNathan: Viral minions haunting the #AGBT15 ballroom tonight? Leggett asks how fast & well @nanopore might pull microbial insig
9:00pm February 26th 2015 via Twitter Web Client
RL: At low, med & high G-C - graph of k-mers, build a tool based around kmers and compared to library; called 'Kontaminant' #AGBT15
9:00pm February 26th 2015 via Hootsuite
RL: Longest stretch of perfect bases - 302bp. Finds k-mer similarity. #AGBT15
8:59pm February 26th 2015 via Hootsuite
RL:Metagenomics on MinION: HMP mock community, 20 diverse bacteria; 20K reads, 98% aligning to one of the references #AGBT15
8:57pm February 26th 2015 via Hootsuite
RL: Build NanoOK to generate FASTA, quality stats, PDF report. Finds most reads aligning, 80-85% accurate. Stretches of perfect seq #AGBT15
8:56pm February 26th 2015 via Hootsuite
RL:512 pores, simple sample prep, inexpensive; long reads. Trend is upwards - better quality and yield. 'It actually works.' #AGBT15
8:54pm February 26th 2015 via Hootsuite
RL: Early access since April 14; experience 'effectively alpha or beta'; 'frequent updates'. #AGBT15
8:53pm February 26th 2015 via Hootsuite
RL:Perhaps combination of MinION + microfluidics + cloud computing? Is it practical? #AGBT15
8:52pm February 26th 2015 via Hootsuite
RL: One of the first @nanopore talks here. Aim: in-field surveillance. Env monitoring of air. #AGBT15
