Rehm: After discussion and evidence sharing (overall) able to get to 85% consensus. 1 outlier: SPG7 w/major disagreement #ESHG2016
12:46pm May 23rd 2016 via Hootsuite
Rehm: Sharing evidence on DNAH5, a 20bp indel, where discussion and consensus around evidence helped every group #ESHG2016
12:43pm May 23rd 2016 via Hootsuite
RT @gsaldanha: Thank you to all the #ESHG2016 attendees @promega https://t.co/uzMdIHrsJt
12:40pm May 23rd 2016 via Hootsuite
Rehm: Looking at Fabry disease (GLA gene); one weakness was timing of guidelines, not enough time to digest the details #ESHG2016
12:39pm May 23rd 2016 via Hootsuite
Rehm: Between labs - only 34% concordance on the 5 tier scale. 22% of diff's may affect medical management #ESHG2016
12:37pm May 23rd 2016 via Hootsuite
Rehm: Also working with CSER https://t.co/39Yah8rBuT 9 labs to compare; 9 var's for all labs. 79% intra-lab concordance #ESHG2016
12:36pm May 23rd 2016 via Hootsuite
Rehm: Types of evidence - population, computation, functional, segregation, de novo, allelic, giving codes and weights #ESHG2016
12:35pm May 23rd 2016 via Hootsuite
Rehm: 2 levels use 'likely' - not quantitative! 50%? 99%? But ended up defining 'likely' at 90% pathogenic, 90% benign #ESHG2016
12:34pm May 23rd 2016 via Hootsuite
Rehm: Tiers defined: 65% of labs surveyed use 5 terms; Pathogenic to Benign. "Never use mutation or polymorphism" #ESHG2016
12:33pm May 23rd 2016 via Hootsuite
Rehm: Not tackling issues of penetrance and expressivity in individual patients #ESHG2016
12:32pm May 23rd 2016 via Hootsuite
Rehm: Took 2 y for interpretation for seq variation, to get agreement. Terms, rules, classifying. Surveys, open forums etc #ESHG2016
12:31pm May 23rd 2016 via Hootsuite
Rehm: Figure from '15 NEJM https://t.co/DLKr6qGIBC #ESHG2016
12:30pm May 23rd 2016 via Hootsuite
Rehm: 17% of variants submitted differed. Lawsuit against Quest for misinterpretation. Distribution of rare var's #ESHG2016
12:29pm May 23rd 2016 via Hootsuite
Heidi Rehm @heidirehm (Harvard Partners MA) Recommendations for the Interpretation of Genetic Variants from ACMG and AMP #ESHG2016
12:28pm May 23rd 2016 via Hootsuite
.@labmonkey_in_KL You can usually find me in the first or second row on the left side (facing the speaker). Say hi anytime! (Here thru Wed)
12:28pm May 23rd 2016 via Hootsuite in reply to labmonkey_in_KL
Cook: So they use a conservative cut-off; 250 'disease genes' are then cut out - AF is far too high to be disease-causing #ESHG2016
12:19pm May 23rd 2016 via Hootsuite
Cook: HCM 1/500 (1/1000 alleles) Most common is MYBPC3, 1.7% cases. In ExAC - 2.5x 10^-5, same as calculated #ESHG2016
Cook: Lastly 'get with the guidelines' - ACMG Cardio Classifier tool. They've taken guidelines and customized for their diseases #ESHG2016
12:17pm May 23rd 2016 via Hootsuite
Cook: With 1%, why aren't these individuals affected? 'Someone in this room has a Titin truncating mutation' #ESHG2016
12:16pm May 23rd 2016 via Hootsuite
Cook: Reviews function of https://t.co/Ku3y2L8Yrj Lots of details, truncating variants. Shows ExAC cohort, about 1% #ESHG2016
Cook: Details on TTN in this '15 Science Trans Med ref https://t.co/9DuFxfHPpA #ESHG2016
12:14pm May 23rd 2016 via Hootsuite
Cook: https://t.co/lGx1pyEXkT Huge gene. With n=1,1932, shows OR variation by band (exon location) #ESHG2016
12:13pm May 23rd 2016 via Hootsuite
Cook: Interpreting titan variants in DCM - nonsense, truncating titin cases DCM in ~20% of cases. Rare missense are v. common #ESHG2016
12:09pm May 23rd 2016 via Hootsuite
Cook: MYBPC3 in 1161 DCM - ORs are not significant at all. #ESHG2016
12:07pm May 23rd 2016 via Hootsuite
Cook: MYBPC3 - found in 6179 HCM samples; looks at odds ratios - huge difference in truncating vs not #ESHG2016
12:06pm May 23rd 2016 via Hootsuite
Cook: Data on https://t.co/XYlbUcdeWU Imp Coll London, allows interpretation of variants. GIM in-press. https://t.co/15LahLlVQz #ESHG2016
12:05pm May 23rd 2016 via Hootsuite
Cook: Beware - 'the danger of expanded panels'. MYH7 labeled as pathogenic - rare - and is not pathogenic at all. #ESHG2016
12:04pm May 23rd 2016 via Hootsuite
Cook: Shows chart of 66% no pathogenic gene detected in sarcomeric genes. Thus - recent 'HCM disease genes' aren't at all... #ESHG2016
12:02pm May 23rd 2016 via Hootsuite
Cook: Fundamental Q: is it a disease gene at all? Cumulative genes for HCM, DCM, ARVC, LQTS, Brugada: chart increasing to 80, 60 #ESHG2016
12:01pm May 23rd 2016 via Hootsuite
Cook: Disease-, gene- and variant-specific interpretation. 5 grades from pathogenic to benign. #ESHG2016
11:59am May 23rd 2016 via Hootsuite
Cook: Accuracy using #GIAB NA12878. 1 FN indel; 245 TP/0FP/0FN for SNVs. Take-home: "Off-the-shelf WES doesn't perform well" #ESHG2016
11:58am May 23rd 2016 via Hootsuite
Cook: (Powerful, powerful case for targeted sequencing's superiority over WES/WGS.) #ESHG2016
11:57am May 23rd 2016 via Hootsuite
Cook: Coverage is 99.9%; WES is 88.1%; WGS is 99.3%. 550x coverage cp to 74x or 69x respectively. $200 / $900 / $2800 costs #ESHG2016
11:56am May 23rd 2016 via Hootsuite
Cook: 174 gene capture assay; clinical plus research genes. '16 Feb ref: https://t.co/h5a7e5abUI Long list of conditions #ESHG2016
11:54am May 23rd 2016 via Hootsuite
Cook: Could be the thin person w/the defective gene needs intensive examination. #ESHG2016
11:53am May 23rd 2016 via Hootsuite
Cook: Ex: 2 individuals with high cholesteral - thin person? overweight? If the thin person w/gene defect - trouble. #ESHG2016
11:52am May 23rd 2016 via Hootsuite
Cook: Dx, (prevention - new therapies), prognosis (not all mut's are the same), stratified treatment - tailored therapy to gene #ESHG2016
11:51am May 23rd 2016 via Hootsuite
Cook: General population, 1:100 in total. Multi-genic, multi-allelic; most often autosomal dom. loss-of-function #ESHG2016
11:50am May 23rd 2016 via Hootsuite
Cook: Reggie Lewis, Boston Celtics (93), Fabrice Muamba footballer. Inherited conditions - 1:500 hypertrophic cardiomyopathy etc #ESHG2016
11:49am May 23rd 2016 via Hootsuite
Stuart Cook (Res Inst of Singapore) Methods for the assessment of variant pathogenicity in cardiac diseases #ESHG2016
11:47am May 23rd 2016 via Hootsuite
Koumbaris: In 2017, anticipate doing ctDNA, early data on @seracare reference material #ESHG2016 https://t.co/KwCK62oFMB
10:12am May 23rd 2016 via Hootsuite
Koumbaris: Future development - sex chromosome aneuploidies; microdel and microdupl syndromes; single-gene disorders #ESHG2016
10:09am May 23rd 2016 via Hootsuite
Koumbaris: They select 1600 regions, w/o CNVs, repetitive elements, optimal GC bias correction, very high coverage, dir enrichmt #ESHG2016
10:07am May 23rd 2016 via Hootsuite
George Koumbaris (NIPD Genetics): ; Presents Veracity; cfDNA by size analysis - lower variance, reducing noise #ESHG2016
10:06am May 23rd 2016 via Hootsuite
NIPD Genetics presenting aneuploidy results from @sercare ref materials at #eshg2016 https://t.co/7HljdBT7Rh
10:01am May 23rd 2016 via Hootsuite
Czwan: HCS - 6664bp deletion across exon 12, partial exon 11. Able to pick up Alu insertion for BRCA2. #ESHG2016
9:57am May 23rd 2016 via Hootsuite
Czwan: Same w/CNV - n=216, 105 TPs, 0 FN/FP. 6 additional positives discovered for their customers (!) #ESHG2016
9:56am May 23rd 2016 via Hootsuite
Czwan: Hereditary cancer - 27 genes. >80% on-target. 100% sens/spec. 0 FN / 0 FP, n=432, 698 TP's #ESHG2016
9:54am May 23rd 2016 via Hootsuite
Czwan: Accelerates time; ease transition for ISO. Benefit of analytical perf, shortened TAT for interpretation, reporting #ESHG2016
9:50am May 23rd 2016 via Hootsuite
Czwan: The offer Clinical NGS Validation Program; have consulting, then verification, and validation is performance on spec tests #ESHG2016
9:49am May 23rd 2016 via Hootsuite
