June 2014

Crosby: Mapped probes of microarrays to transcript patterns (7034 w/shared probes). Unpub. data #RNASeq2014

4:02pm June 18th 2014 via Hootsuite

Crosby: Took Agilent UHR RNA, human bone marrow RNA at dilutions; 4 microarray and 2 RNA-Seq lib prep; 33 genes via TaqMan #RNASeq2014

3:59pm June 18th 2014 via Hootsuite

Crosby: RNA-Seq can be 'what reviewers are looking for'. #RNASeq2014

3:57pm June 18th 2014 via Hootsuite

Crosby: GATC is a CRO-type facility, also has clinically validated cytogenetics, microarrays on down #RNASeq2014

3:54pm June 18th 2014 via Hootsuite

Seth Crosby (WashU): "RNA-Seq vs. Microarrays: a comparison as to which approach is most cost-effective for which situation" #RNASeq2014

3:52pm June 18th 2014 via Hootsuite

Yao: Q: any evidence of RNA editing? A: Haven't looked at it yet. #RNASeq2014

3:50pm June 18th 2014 via Hootsuite

Yao: "HR told me to put this slide" of 9 bioinformatics positions open at Merck. (So there's that.) #RNASeq2014

3:49pm June 18th 2014 via Hootsuite

Yao: Concludes 'RNA-Seq can be used for var discovery but not equivalent to DNA-Seq'. Will try GSNAP for RNA mapping #RNASeq2014

3:46pm June 18th 2014 via Hootsuite

Yao: 2nd strategy showed 92-94% concordance with same datasets; if dupl. weren't marked, went from 92 to 93% #RNASeq2014

3:45pm June 18th 2014 via Hootsuite

Yao: He used >20x cutoff for calling; 2nd approach used STAR instead of TopHat + duplicate marking for 2nd strategy #RNASeq2014

3:40pm June 18th 2014 via Hootsuite

Yao: After BWA-mem and TopHat alignment; DNA was 4x the reads: 100M vs 25M. Variant concordance was 74-77% betw. RNA/DNA #RNASeq2014

3:39pm June 18th 2014 via Hootsuite

Yao: Unpublished results so not a lot of detail; 22 samples, RNA-Seq at PE90bp and WES using Agilent 50MB at PE90bp #RNASeq2014

3:31pm June 18th 2014 via Hootsuite

Jianchao Yao (Merck): "Compare variant detection power between RNA-Seq and DNA-Seq" #RNASeq2014

3:29pm June 18th 2014 via Hootsuite

Wang: (Gary Schroth brings up the point that using SMARTer for miRNA isn't what that kit was designed for.) #RNASeq2014

3:28pm June 18th 2014 via Hootsuite

Wang: Concludes: method is 'the strongest confounding factor'; NEBNext appears best but missed large # lincRNA via random primer #RNASeq2014

3:22pm June 18th 2014 via Hootsuite

Wang: "Substantially different miRNA populations" between protocols, regardless of processing; informatics also makes difference #RNASeq2014

3:14pm June 18th 2014 via Hootsuite

Wang: Venn diagram: 4-13 common to all 3; dozens are specific to method for example samples shown #RNASeq2014

3:13pm June 18th 2014 via Hootsuite

Wang: In their analysis of 10M reads ea, NEBNext sRNA appears to be the best; but the methods cluster together; little overlap #RNASeq2014

3:12pm June 18th 2014 via Hootsuite

Wang: Analysis is by Genboree (Baylor: http://t.co/ylaEquyzUW) BOWTIE2 alignment and mirDeep2 #RNASeq2014

3:10pm June 18th 2014 via Hootsuite

Wang: Evaluated ProK, glycoblue add'n, DNAse as part of the process. Eval NEBNext sRNA, Epicentre Scripseq, Clontech SMARTer #RNASeq2014

3:06pm June 18th 2014 via Hootsuite

A few exosome resources from @LIFECorporation: http://t.co/T7r5cAcbpJ Online forum: http://t.co/0Vtc9aI2Mh #RNASeq2014

3:04pm June 18th 2014 via Hootsuite

Wang: Looking at extracellular RNAs (exosomes); but unknown distribution of types in these plasma samples #RNASeq2014

3:01pm June 18th 2014 via Hootsuite

Yaoyu Wang (Dana Farber Cancer Inst): "An unbiased comparison of RNA-Seq technologies" #RNASeq2014

2:52pm June 18th 2014 via Hootsuite

RT @atulbutte: An Annotated Online Bioinformatics / Computational Biology Curriculum http://t.co/Vicvfm5Utf

1:40pm June 18th 2014 via Hootsuite

ESHG14 Interview with Pfizer researcher: KRAS & cell free DNA detection using QuantStudio 3D digital PCR | YouTube http://t.co/Tep8T00dx

1:20pm June 18th 2014 via Hootsuite

Schroth:Q: Use of 2x75? A: 2x100 has lower mapping rate. Other applications though for longer reads. 2x50? Also fine #RNASeq2014

1:12pm June 18th 2014 via Hootsuite

Schroth: Q:BaseSpace for targeted? A: Cufflinks/TopHat view (implying - no, as it isn't for targeted RNA-Seq) #RNASeq2014

1:11pm June 18th 2014 via Hootsuite

Schroth: Showed browser view of captured RNA using exome capture - able to discover novel fusions in melanoma FFPE #RNASeq2014

1:07pm June 18th 2014 via Hootsuite

Schroth: Shows fold-change r2 values on the order of 0.96 from both FF and FFPE #RNASeq2014

1:03pm June 18th 2014 via Hootsuite

Schroth: Yield and DV200 quality highly correlated from FFPE RNA #RNASeq2014

1:03pm June 18th 2014 via Hootsuite

Schroth: New metric DV200: amount of input 200nt long. Good is >70%, 20ng. Moderate 50-70%, 20-40ng. Poor 30-50%, 40ng #RNASeq2014

1:01pm June 18th 2014 via Hootsuite

Schroth: Showed loss of exons from FFPE RNA; but use exome capture from 10ng RNA #RNASeq2014

12:58pm June 18th 2014 via Hootsuite

Schroth: Reviewed TopHat / Cufflinks on BaseSpace (a commercial for @illumina - so it goes). #RNASeq2014

12:55pm June 18th 2014 via Hootsuite

Schroth: There is no 'one kit to use'; showed chart of 5 $ILMN kits; he has been working on BaseSpace analysis #RNASeq2014

12:48pm June 18th 2014 via Hootsuite

Schroth: Points to 2008 paper, done with only 20M reads http://t.co/FtUuJjMnXh pointing out there isn't any 'std' # reads to use #RNASeq2014

12:45pm June 18th 2014 via Hootsuite

MT @BioMickWatson: Phi X nanopore paper uses ref. quadromer map, and "aligns" raw data to the reference. Cp @nanopore's de novo base calling

12:45pm June 18th 2014 via Hootsuite

Schroth: Biggest challenge of RNA-Seq: 'Enormous dynamic range', the genes at the low end #RNASeq2014

12:43pm June 18th 2014 via Hootsuite

Schroth: "I don't RNA-Seq should be as complicated as we make it out to be" #RNASeq2014

12:41pm June 18th 2014 via Hootsuite

RT @CompBiolPapers: Nanopore Sequencing of the phi X 174 genome. (arXiv:1406.4214v1 [q-bio.GN]) http://t.co/NG1vkje32c

12:40pm June 18th 2014 via Hootsuite

Gary Schroth (Illumina): "Total solutions for RNA-Seq within the Illumina ecosystem" #RNASeq2014

12:39pm June 18th 2014 via Hootsuite

Tan: Q: Pre-capture pooling? A: Have seen people using 4-plex; higher possible but not tested (yet) #RNASeq2014

12:37pm June 18th 2014 via Hootsuite

RT @Forbes: .@MeredithLEaton East Coast cities like Boston are tough because the cost of living tends to outpace wage growth. #AskForbes

12:30pm June 18th 2014 via Hootsuite

Tan: Showed MAQC HBR data for rRNA depletion and 256 neuro RNAs. On-target ~90%; linearity with ERCC from 3M-140M reads #RNASeq2014

12:26pm June 18th 2014 via Hootsuite

Tan: Showed figure from this 2014 Nat Protocols Mercer et al http://t.co/nD8d3wVwmo called SeqCap RNA #RNASeq2014

12:17pm June 18th 2014 via Hootsuite

John Tan (Roche NimbleGen): "Increased visibility to low-abundance variants through a novel RNA-Seq target enrichment method" #RNASeq2014

12:16pm June 18th 2014 via Hootsuite

Park: Q: end bias? A: They claim similar performance, no data #RNASeq2014

11:15am June 18th 2014 via Hootsuite

Park: Sense 'very economical'; one PolyA+, soon-to-be-launched one will do total RNA. Has @illumina, @iontorrent and SOLiD #RNASeq2014

11:11am June 18th 2014 via Hootsuite