Wijmenga: 3 components: disregulation of immune sys; environmental factors; underlying genetic factors (helped by GWAS) #ESHG14
12:47pm May 31st 2014 via Hootsuite
Cisca Wijmenga (Univ Groningen, Netherlands): The long non-coding RNA landscape of autoimmune diseases #ESHG14
12:46pm May 31st 2014 via Hootsuite
Deelen:Q:How to normalize data? A:Just used PCA, and removed the first one for eQTL. For ASE 'more about ref. bias' as test/individ #ESHG14
12:44pm May 31st 2014 via Hootsuite
Deelen: Their next work is to build a public portal. Publishing soon. Slides (Figshare) http://t.co/1Z8YDUN3TT #ESHG14
12:43pm May 31st 2014 via Hootsuite
Deelen: Pointed out directional allelic bias. Drilling down, significant ASE results (~45K at MAF >5%) #ESHG14
12:41pm May 31st 2014 via Hootsuite
Deelen: But another ~1K add'l eQTL genes from the 'other' set. Pointed out this data is free of charge, 'just lying around' #ESHG14
12:39pm May 31st 2014 via Hootsuite
Deelen: Validated eQTLs using Geuvadis samples, 96% validated eQTLs with genotype. 'Other' samples overlap 2.5k with Geuvadis #ESHG14
12:38pm May 31st 2014 via Hootsuite
Deelen:PCA analysis, looked at accuracy of genotyped & imputed SNVs, eQTL mapping MAF<0.05, meta-analysis per population #ESHG14
12:37pm May 31st 2014 via Hootsuite
Deelen: Aligned 13TB FASQ files of RNA-Seq data from 459 individuals, all LCL lines, genotypes avail; other ~800 samples mixed #ESHG14
12:36pm May 31st 2014 via Hootsuite
Patrick Deelen Univ Med Ctr Groningen: Resolving variants of unknown significance through reanalysis of 4,978 public RNA-seq samples #ESHG14
12:34pm May 31st 2014 via Hootsuite
Gilissen: Only one inherited causal ID (complex het); no de-novo noncoding mutations discovered ('which was a surprise for us') #ESHG14
12:08pm May 31st 2014 via Hootsuite
Gilissen: For ID (intellectual disability), 21/50 got a result that WES failed, reported in de Ligt 2012 http://t.co/2XdH2QbuP1 #ESHG14
12:07pm May 31st 2014 via Hootsuite
Gilissen: Another was 60kb duplication on Chr4; but inserted from ChrX, inversion as well. Did breakpoint-span PCR #ESHG14
12:05pm May 31st 2014 via Hootsuite
Gilissen: Onto de novo structural variation: found a 600bp deletion - but was able to use Sanger to sequence across breakpoint #ESHG14
12:04pm May 31st 2014 via Hootsuite
Gilissen: Compared their list of de novo mutations to Univ Wash 6k exome database, and calculated rare non-syn mutation rates #ESHG14
12:02pm May 31st 2014 via Hootsuite
Gilissen: 79 de novo cp to 84 (WES n=100 cp to WGS n=50). Plotting different de novo per individual: theirs is much higher rate #ESHG14
11:59am May 31st 2014 via Hootsuite
Gilissen: The same were found - 16/18 from WES cp to WGS; one was mosaic (30% present), another failed #ESHG14
11:58am May 31st 2014 via Hootsuite
Gilissen: From de novo muts: systematic validation (overall 38% validation), 84 de novo SNV's identified. Cp to WES 12% validated #ESHG14
11:57am May 31st 2014 via Hootsuite
Gilissen" n=50 for WGS via Complete Genomics. % of exome is 'much higher'; >20X goes from 80% to above 97% #ESHG14
11:55am May 31st 2014 via Hootsuite
Gilissen: Of 1500 ID patients: 1.5% via single-gene for ID; 12% via microarray; another 27% by WES (n=100) #ESHG14
11:54am May 31st 2014 via Hootsuite
Next: Christian Gilissen (Radboud U Nijmegen): “Genome sequencing identifies major causes of severe intellectual disability” #ESHG14
11:52am May 31st 2014 via Hootsuite
Tukiainen: Reported 3 new height X loci; recent pub: http://t.co/wMrV0Vm6i3 'new loci and interesting biology' 'more to discover' #ESHG14
11:47am May 31st 2014 via Hootsuite
Tukiainen: 20K from GWAS, ~400K ChrX SNPs; 12 phenotypes (but of them only height ass'd with ChrX) #ESHG14
11:36am May 31st 2014 via Hootsuite
Tukiainen: Nice to see the author's Twitter handle on her intro slide: @ttukiainen . Oops, missed the intro on ChrX... #ESHG14
11:35am May 31st 2014 via Hootsuite
Next: Taru Tukiainen (Mass Gen, Boston): "Chromosome X-wide association analysis discovers new loci for complex traits..." #ESHG14
11:34am May 31st 2014 via Hootsuite
RT @iontorrent: Attending #eshg14? @DaleYuzuki 'Improve your experience at conferences with Twitter' http://t.co/9gKsc5hnNU
11:32am May 31st 2014 via Hootsuite
Borel: Q: Which indiv. cell is more impt.? A: Tissues may not be homogeneous; you are observing at a different level #ESHG14
11:31am May 31st 2014 via Hootsuite
Borel: Q: Concern about variability between individual cells. A: Step taken to phase cell growth and stop at particular points in dev....
11:30am May 31st 2014 via Hootsuite
Borel: Finding - 76% of hetSNVs displayed 'random monoallelic expression' #ESHG14
11:27am May 31st 2014 via Hootsuite
Borel: Now onto T2D: normal vs T2D islet cells: looking at 5 key islet cell genes - found new cell type with high glucagon exp #ESHG14
11:26am May 31st 2014 via Hootsuite
Borel: Showed many genes, # cells, allelic ratio, all in one (busy) figure. #ESHG14
11:25am May 31st 2014 via Hootsuite
Borel: Showed allelic pattern (majority 0 - 0.2 and 0.8-1). But from bulk - looks much different than individual cells interrogated #ESHG14
11:23am May 31st 2014 via Hootsuite
Borel: Used ERCC spike-in controls (avail from Ambion), defined threshold; reported 4 molecule sens at 95%. 98% accuracy of meas #ESHG14
11:22am May 31st 2014 via Hootsuite
Borel: 28M reads/sample; defined reference to ref+alt ratio. From germline pulled 83.5k het SNVs, used 16 reads as RNA threshold #ESHG14
11:21am May 31st 2014 via Hootsuite
Borel: Q1 was allelic expression in individ. cells. Primary Fibroblasts, 163 cells, used C1, ~2d sample prep, 2-14d sequencing #ESHG14
11:19am May 31st 2014 via Hootsuite
Next: Christelle Borel Univ Geneva, Switzerland: "Transcriptomes of individual cells" #ESHG14
11:18am May 31st 2014 via Hootsuite
Sawyer: Selection criteria: FORGE's evidence of Mendelian disorder, no diagnosis. #ESHG14
11:17am May 31st 2014 via Hootsuite
Sawyer: Presented results of 105 Canadian children as part of the FORGE consortium. Genome BC website http://t.co/0ghK1sGEqv #ESHG14
11:15am May 31st 2014 via Hootsuite
Sawyer: Value of using WES for non-typical phenotypes / ultra-rare disorders; some 8/36 were of these types #ESHG14
11:11am May 31st 2014 via Hootsuite
RT @illumina: AH: Speed of DNA-to-data important, particularly for the clinical applications of Exome-Seq. But quality always key. #ESHG14
7:46am May 31st 2014 via Hootsuite in reply to
RT @Ensemily: Alexander Hoischen: exome sequencing -> massive increase in disease gene discovery but still some flaws #ESHG14
7:45am May 31st 2014 via Hootsuite in reply to
MT @edyong209: Stunning visualisation of a single synapse. http://t.co/rXtPI6eXwV (I love @virginiahughes’s drawing too)
10:25pm May 29th 2014 via Hootsuite in reply to
RT @SwedishCanary: I ordered a chicken & an egg from Amazon. I'll let you know.
8:20pm May 29th 2014 via Hootsuite
RT @el_skootro: The first kick in this World Cup will be from a someone wearing a mind-controlled exoskeleton. http://t.co/u7qdnMTnff
7:50pm May 29th 2014 via Hootsuite
RT @brainpicker: Illustrated six-word memoirs by students from grade school to grad school around the world http://t.co/cgE7YoW17q
6:50pm May 29th 2014 via Hootsuite
RT @thinkgenome: Retention of UC Riverside students in STEM fields receives major financial boost http://t.co/SsTIzCI6th
5:40pm May 29th 2014 via Hootsuite
Georgetown offering 16-h MOOC Genomic Medicine Gets Personal | The Daily Scan http://t.co/j55wXhHZlV
4:40pm May 29th 2014 via Hootsuite
Why China Can't Innovate | Harvard Bus Rev (PDF) http://t.co/ZDSub0uy6d
3:40pm May 29th 2014 via Hootsuite
Human Proteome Project Finds 193 Previously Unknown Proteins | Bioscience Tech http://t.co/7KBopSyMuC
2:55pm May 29th 2014 via Hootsuite
Identifying the next big technologies via text mining | Nature News http://t.co/GBdDHYMhCO
1:25pm May 29th 2014 via Hootsuite
