Keating:Developing a miRNA guided minimization of rejection and immuno-supp therapy. #AGBT16
8:25pm February 11th 2016 via Hootsuite
@Becky_Kusko I met.@bioinfomagician at last year's #AGBT16 Jonathan will try to catch you perhaps tonight!
8:22pm February 11th 2016 via Hootsuite in reply to bioinfomagician
RT @Becky_Kusko: Wow just finally met @DaleYuzuki in person! Not sure how that took so long to happen. #AGBT16
8:20pm February 11th 2016 via Hootsuite
Keating: Kidney rejection via needle biopsy, but has complications and with cause. Assess 10 mRNAs in CTOT -04 study #AGBT16
8:16pm February 11th 2016 via Hootsuite
Keating: 5y survival - Kidney best, Lung worst. Hasn't really changed in 5y. Chronic renal failure in non-renal transplants too #AGBT16
8:15pm February 11th 2016 via Hootsuite
Keating: Immunosuppression drug tox is substantial. Kidney is $200K and Liver is $250K and heart is $860K. #AGBT16
8:14pm February 11th 2016 via Hootsuite
Keating: Post-transplant in 1y: 10% in kidney, 35% in heart. 6 biopsies in first year taken before irreversible damage occurs #AGBT16
8:12pm February 11th 2016 via Hootsuite
Brendan Keating (U Penn) Detection and validation of signatures of liver transplantation rejection diagnoses #AGBT16
8:11pm February 11th 2016 via Hootsuite
Lincoln: Second JAMA Onc. ref regarding this validation work https://t.co/yP0QbtVisj #AGBT16
8:10pm February 11th 2016 via Hootsuite
Lincoln: Strict, lower criteria that needs other methods to validate. Lower bound of conf. - and take a set at 0.11% FP SNV rate #AGBT16
8:08pm February 11th 2016 via Hootsuite
Lincoln: Second method to confirm for reporting: most var's are easy and accurate. Think about multiple thresholds are key #AGBT16
8:07pm February 11th 2016 via Hootsuite
Lincoln: It's hard to get these samples; Lisa Kalman from CDC is organizing a new GeT-RM website here: https://t.co/lMRDCQbkMZ #AGBT16
8:05pm February 11th 2016 via Hootsuite
Lincoln: Statistics: a 0.1% analytic FN reate but pt sample has a 10% FN rate. 'Huff's book: how to lie w/statistics #AGBT16
8:04pm February 11th 2016 via Hootsuite
Lincoln: Sizable fraction in that 23% - no exonic variants in 5 of 29 genes. Almost all were 'simple SNVs'; 77% is biased to easy #AGBT16
8:03pm February 11th 2016 via Hootsuite
Lincoln: WG reference samples, NA12878, similar @giab data methods. But: GIAB has 23% non-high-confidence calls #AGBT16
8:02pm February 11th 2016 via Hootsuite
Lincoln: Positive controls? Combed Coriell, found 42 samples for 9/29 cancer genes. 7 not available, or failed inbound QC #AGBT16
8:01pm February 11th 2016 via Hootsuite
RT @matthewherper: Miscarriages reported in 3 American women with Zika virus https://t.co/PUgRy4Zr6N via statnews
Lincoln: reproducibility of coverage, optimizing protocols. 'It's hard. Easier to throw informatics at it.' #AGBT16
8:00pm February 11th 2016 via Hootsuite
Lincoln: For CNV this '11 BMC paper -https://t.co/dEBRCyexSs But most important - biochemical and process steps clean. #AGBT16
Lincoln: 2 indel callers, 2 CNV callers, GATK, CoalGen for homopolymer vars. #AGBT16
7:58pm February 11th 2016 via Hootsuite
Lincoln: Lots of examples. PMS2 - a 99.9% identical pseudogene. Highly GC, or AT rich. Can't do it off-the-shelf. #AGBT16
Lincoln: Only 13.4% clinically actionable. Shows 28bp polyA right before MSH2. Other examples of a 'mess'. 24bp tandem repeat MET #AGBT16
7:56pm February 11th 2016 via Hootsuite
Lincoln: In Vitae's >1000 sample analytic validity '15 JMD ref https://t.co/hPltfIDZgS #AGBT16
7:55pm February 11th 2016 via Hootsuite
Stephen Lincoln (Invitae) Clinically important variants are often technically challenging for NGS #AGBT16
7:52pm February 11th 2016 via Hootsuite
Hoischen: Looking at a per-error rate by position along the FGFR2 S252W locus, shows sig signal about the clonal nature #AGBT16
7:51pm February 11th 2016 via Hootsuite
Hoischen: Shows pieces (16) from a 71 y.o. testis looking at particular FGFR2 S252W mutation by section #AGBT16
7:50pm February 11th 2016 via Hootsuite
Hoischen: Recent PNAS paper https://t.co/cJtdMa6QF2 about these selfish mutations in testes over time #AGBT16
7:49pm February 11th 2016 via Hootsuite
Hoischen: Selfish mutations: mutated testis tissue will show clonal outgrowth - up to 1m long (!) #AGBT16
7:47pm February 11th 2016 via Hootsuite
Hoischen: Striking: five known paternal age effect disordered; 1000x increase birth prevalance cp to underlying mut rate. #AGBT16
Hoischen: 3rd application: de novo 'selfish mutations during spermatogenesis'. 80% of de novo's occur there. Increase w/paternal age #AGBT16
7:46pm February 11th 2016 via Hootsuite
Hoischen: Was able to validate via an invasive procedure. For paternal data - able to get 10/234 unique molecules (~4%) #AGBT16
7:44pm February 11th 2016 via Hootsuite
Hoischen: These markers spanned the repeat expansion. Father affected, son affected, ID'd the allele. 5ng w/pregnant mom #AGBT16
7:42pm February 11th 2016 via Hootsuite
Hoischen: Looked instead for tagging SNPs and look for that; since it was a dominant conditions. smMIP for 50 markers #AGBT16
7:41pm February 11th 2016 via Hootsuite
Hoischen: First gene - DMPK het (myotonic dystrophy). Problem: repeat expansions, never present in 170bp cfDNA. #AGBT16
Hoischen: If the fetal fraction is 10%, only 330 fetal genome copies, for het is only 165 molecules. smMIP can be strand-spec #AGBT16
7:40pm February 11th 2016 via Hootsuite
Hoischen: 2nd app - monogenic NIPT - not NIPT for anueploidy, but for inherited disease #. cfDNA about 10ng, 3300 haploid genomes AGBT16
7:39pm February 11th 2016 via Hootsuite
Hoischen: Timing of de novo mutations - some are inherited from a mosaic parent (!) May have recurrence risk #AGBT16
Hoischen RT @frapaport: AH : MIPs were upgraded to single molecule smMIPs https://t.co/XFtbAO4fIS #AGBT16
7:38pm February 11th 2016 via Hootsuite
Alex Hoischen (Radboud Univ Nijmegen NL) ultra-sensitive mosaic mut. detection for clinical applications #ASHG16 https://t.co/FcBci3FVOj
7:36pm February 11th 2016 via Hootsuite
Burgess:Std Oncology panels with 345 genes, 5.1K probes; smaller one with 53 genes, 635 probees. Custom to go to 1MB, 420 genes #AGBT16
1:50pm February 11th 2016 via Hootsuite
Burgess: Software for probe design, variable efficiency, need for balancing probes and buffers #AGBT16
1:43pm February 11th 2016 via Hootsuite
Burgess: Claims MIPS 'not more widely used' due to no 'off the shelf' commercial solution, and home-brew is hard #AGBT16
1:42pm February 11th 2016 via Hootsuite
Burgess: High Efficiency Amplification Targets - an advanced version of MIPS. Goes back to 1988, Lee Hood #AGBT16
Dan Burgess (Roche) HEAT-Seq massively parallel molecular inversion probes for targeted sequencing #AGBT16
1:36pm February 11th 2016 via Hootsuite
Wylie:Q:How modifiable is this panel? A: Can be done in a few hours, still sequence homology will pick up alternates #AGBT16
1:35pm February 11th 2016 via Hootsuite
Wylie: And then was able to quickly able to dev a real-time PCR assay for tracking. #AGBT16
1:32pm February 11th 2016 via Hootsuite
Wylie: Entervovirus D68 was dominant type in the US in 2014; found in all 50 states. Was able to rapidly enrich and sequence #AGBT16
RT @jgreid: Big question at #AGBT16 SV lunch -- "How do we know when two SVs are the same?" Seems simple, but it is not.
1:27pm February 11th 2016 via Hootsuite
RT @DukeSequencing: Sequel looks pretty cool. On my wish list for sure :)@erichjarvis @PacBio #AGBT16 https://t.co/TV1DU5s9hE
1:26pm February 11th 2016 via Hootsuite
Wylie: 34 viral families, 190 genera, 337 spp - both RNA and DNA. Charted sequence capture capacity - NimbleGen 200MB largest #AGBT16
1:25pm February 11th 2016 via Hootsuite
