Bhalla: Complex and laborious. LCM of 5 nephrons, cut up into sections, and analysis. How it is done today. #AGBT17
7:38pm February 14th 2017 via Hootsuite
Bhalla: So many different cell types along the nephron - 1-2M nephrons within mouse kidney. Tubules, interdigitated cell types #AGBT17
7:37pm February 14th 2017 via Hootsuite
Bhalla: Power of technology - as a nephrologist, to use mouse kidney (not anatomically organized for discovery due to tissue) #AGBT17
7:36pm February 14th 2017 via Hootsuite
Bhalla: RNA in bulk RT'd to cDNA, read barcodes, reconstruct profile of single cells. #AGBT17
7:35pm February 14th 2017 via Hootsuite
Bhalla: Flowcell with 200K wells, with one cell, with one barcoded bead/cell. Lyse, mRNA hyb'd to the bead, then collected #AGBT17
7:33pm February 14th 2017 via Hootsuite
Vivek Bhalla (Stanford Univ CA) Single-Cell RNAseq applications using BD Resolve #AGBT17
7:31pm February 14th 2017 via Hootsuite
Marioni: Acknowledges @coregenomics at the CRUK core facility! #AGBT17
4:58pm February 14th 2017 via Hootsuite
Marioni: Expect work to be published in Science 'in a week's time'. Core activation highly conserved in divergent mice spp #AGBT17
Marioni: Also T-cell activation as a function of aging in mice, comparing gene expression data. #AGBT17
4:57pm February 14th 2017 via Hootsuite
Marioni: Describes work in mouse, CD4+ T-cell activation in vitro, looking at a cre activation pathway between BL6 and CAST lines #AGBT17
4:56pm February 14th 2017 via Hootsuite
Marioni: ...a population but also diff variable genes between populations #AGBT17
4:50pm February 14th 2017 via Hootsuite
Marioni: Shows equations of Poisson dispersion for biological as well a differential comparison. Finding highly-var genes within.. #AGBT17
Marioni: Makes reference to Human Cell Atlas project https://t.co/v650PjQKQz Shows data from https://t.co/4O7uMaldib #AGBT17
4:49pm February 14th 2017 via Hootsuite
John Marioni (CRUK, Univ Cambridge) Aging, evolution and immunity with sc RNA-sequencing #AGBT17
4:46pm February 14th 2017 via Hootsuite
Smet: Patient-derived initiatives like 'Count Me In': Link here: https://t.co/cS21eyVTXp #AGBT17
4:45pm February 14th 2017 via Hootsuite
Smet: 'Walk-up sequencing': pre-made libraries run, whether epigenomics, ChIP-Seq, Hi-C etc. 25% cost reduction for WES #AGBT17
4:44pm February 14th 2017 via Hootsuite
Smet: A 3T flowcell is >250 exomes; higher-plex needs to control for potential contamination #AGBT17
4:43pm February 14th 2017 via Hootsuite
Smet: Cautionary notes: RTA software, integration w/other large-scale projects. Chemistry changes; filling flowcells; batch effects #AGBT17
4:42pm February 14th 2017 via Hootsuite
Smet: Alignment rate high but not as high as the HiSeq 4000; higher # of SNPs and Indels on the NovaSeq 'need further investigation' #AGBT17
Smet: (Only at the Broad, what a place...) :o) #AGBT17
4:41pm February 14th 2017 via Hootsuite
Smet: Showed nice graph of price reduction, including on the X. NovaSeq. "We committed to buying... I can't remember the number" #AGBT17
4:37pm February 14th 2017 via Hootsuite
Smet: (i.e. duplication) - PCR-free started at 15% duplication, down to 3.5%. (What is a 'strip 2'?) #AGBT17
Smet: 38.8K WGS in '16 etc. The HiSeq X 'fully optimized', perfecting PCR-free workflow. Biggest challenge - the 'pad hopping' #AGBT17
4:34pm February 14th 2017 via Hootsuite
Smet: At the Broad: 254K exomes, 67K genomes. 1.6M samples. 26K transcriptomes #AGBT17
4:32pm February 14th 2017 via Hootsuite
Tim De Smet (Broad Inst MA) NovaSeq Broad Institute's comparison and intended uses #AGBT17
4:31pm February 14th 2017 via Hootsuite
Schroth: Cell purity 99.3%; 4922 genes detected; 5.4% ribosomal. Recommend 100K reads/cell. 10B reads = 100K cellsx100K reads #AGBT17
4:28pm February 14th 2017 via Hootsuite
Schroth: Single-cell profiling: solution with Bio-Rad started shipping 'this week'. More detail in the ILMN lounge Wed AM #AGBT17
4:27pm February 14th 2017 via Hootsuite
Schroth: Shows TruSeq DNA methylation 2x75bp PE reads, 6% %Q30 read 1 on NovoSeq. RNASeq data comparable to HiSeq 2500/4000 #AGBT17
4:25pm February 14th 2017 via Hootsuite
Gary Schroth (Illumina CA) The next era of sequencing starts now #AGBT17
4:23pm February 14th 2017 via Hootsuite
Hoischen: "Few answers... more questions..." Clone dynamics, and also role in disease or perhaps normal aging phenomena #AGBT17
4:05pm February 14th 2017 via Hootsuite
Hoischen: Clonal hematopoeis can be detected as sensitivity is driven down. Observed as early as 21y of age. #AGBT17
4:04pm February 14th 2017 via Hootsuite
Hoischen: 196/225 were missense, 21 indels. Shows # by age, steady exponential w/age #AGBT17
4:03pm February 14th 2017 via Hootsuite
Hoischen: Shows IGV plot of DNMT3A R326C mut in 25yo woman; seq coverage was 4,000x, 1% AF. Of 225: only 8 synonymous, 217 known CH #AGBT17
4:00pm February 14th 2017 via Hootsuite
Hoischen: Plot of mut by age, 225 somatic SNVs and indels. From 0.08% to 30% Allele Fraction. #AGBT17
3:58pm February 14th 2017 via Hootsuite
Hoischen: Able to sequence both directions. Able to use Poisson for error distribution on a per-base basis, multiple test correction#AGBT17
Hoischen:Had 400 samples for every decade 20-29, etc through 60-69 from healthy blood donors. Screened for 131 hotspots common to CH #AGBT17
3:56pm February 14th 2017 via Hootsuite
Hoischen: #AGBT17 Quickly reviews the method described here '13 Genome res https://t.co/oh8yrYCQYK
3:55pm February 14th 2017 via Hootsuite
Hoischen: Another '15 ref https://t.co/cJIKa7fwtb Working with Ashley (Stanford) and Shendure (U Wash) and smMIPs #AGBT17
3:54pm February 14th 2017 via Hootsuite
Hoischen: 'New insights into age-related clonal hematopoiesis': Landmark papers, of which is '14 Nat Med https://t.co/coUo3JudD9 #AGBT17
3:53pm February 14th 2017 via Hootsuite
Alex Hoischen (Radboud Univ Med Ctr Netherlands) Ultra-sensitive mosaic mutation detection in blood DNA of healthy individuals #AGBT17
3:51pm February 14th 2017 via Hootsuite
Cuppen: In intestine, 3/14 small deletions at fragile sites. Colon: large chromosomal events 5/15 #AGBT17
3:42pm February 14th 2017 via Hootsuite
Cuppen: Showing chromosomal segregation errors may play a role in driving colon ca. 1/9 livers dupl. w/microhomology... #AGBT17
Cuppen: Regional biases in mutation patterns may be explained by MMR; by doing CRSPR MMR-deficient, demonstrated this #AGBT17
3:40pm February 14th 2017 via Hootsuite
Cuppen: First is cell-cycle tissue-indep, next is cell cycle-, and tissued dependent, third may be culture assoc'd #AGBT17
3:38pm February 14th 2017 via Hootsuite
Cuppen: Looking at signatures, determined three: Unknown proc, deamination-induced, oxidative stress-induced. #AGBT17
3:37pm February 14th 2017 via Hootsuite
Cuppen: Across abt 30 donors, seeing about 40 mutations/year in these cells. Shows chart of type of mut across colon, gut, liver #AGBT17
3:36pm February 14th 2017 via Hootsuite
Cuppen:. Culture is 7-14d, to single ASCs, do clonal organoid culture 6w. Only 200 - 2K mutations/cell #AGBT17
3:34pm February 14th 2017 via Hootsuite
Cuppen: They use 3D organoid cultures to grow '13 Science ref https://t.co/NSu5wxZc2R #AGBT17
3:33pm February 14th 2017 via Hootsuite
Cuppen: ASCs (adult stem cells) rare, no markers/Abs available, mutation rate is low, may not be non-random, need scWGS w/low error #AGBT17
3:32pm February 14th 2017 via Hootsuite
Cuppen: Adult stem cells have impt role in tissue homeostasis, aging and cancer. Present, multipotent, long-lived. #AGBT17
3:31pm February 14th 2017 via Hootsuite
