Thursday 02/27/14

Posted on February 27, 2014 by admin

10:00a – 11:15p

Meetings

  • (ski trip planning meeting) (10a-11a)
  • team project planning meeting (11a-12p)

Project 2 data analysis

  • locate new data files
  • run splitdax
  • run STORM analysis on data and beads
  • beads look low contrast but we’ll see.

Literature: selected for journal club

Notes on Lee … Church Science 2014: Highly Multiplexed Subcellular RNA sequencing in Situ

Concerning detection efficiency

  • intentionally exponentially deplete density using sequencing primers with random mismatches
  • on thresholds: use all signal (I suppose the brightest of the 4 channels is called the base?) relative rather than absolute thresholding? This could have been more explicitly explained than ‘putative sequences are determined for all pixels.’

Controls

  • induction of mCherry.
    • 7472 (98%) map to ‘+’ strand (as opposed to the minus strand? or as opposed to nothing? Given the method that every pixel is assigned a sequence, I suspect the claim of all reads mapped to on target can’t be true.)
    • shows nice induction from 0 to 15 transcripts per cell
    • For 853 genes from human primary fibroblasts with more than one observation (per cell?) compare to RNA-seq: Pearson’s correlation .57 fibroblasts to fibroblasts, .47 to lymphocyte seq, .23 to iPS cell seq. (excluding 1 outlier)

Experiment

  1. transcriptome in human primary fibroblasts
    • per-base error rate 0.64%, read 27 bases
    • ID 14,960 amplicons > 5 pixels -> 4,171 genes. (Do you get to choose which genes you look for? Does not seem so.
    • Fig S5 has ~250 amplicons implies of order 60 cells. 125-200 of these are rRNA. leaving 50-125 transcripts.
    • how stringent is the alignment ?!! Either you are missing most of the genes / sequences you could be detecting (by insisting on perfect alignment), or you are hiding an essential variable.
  2. trasncriptome primary fibroblasts after wounding. 171,730 reads, 6,880 genes.

Drawbacks

  • 81% of reads in EGF medium are rRNA

Goodbye Pubget

  • Pubget’s what’s hot in Science, top 10 papers this month: http://s2086772265.t.en25.com/e/es?s=2086772265&e=18778&elq=4ccdc583ab5d43e396c32c8bbb422845
  • includes a 1968 paper reporting the discovering of a restriction enzyme from E coli and a paper written in french on pallative care for the elderly.
  • I’m afraid pubget your filters don’t work for me.

STORM: imaging F04-647, F05-750

  • lower concentration (1uL primaries) seems a bit too low. Staining is clear but dots aren’t bright.
  • imaging buffer is 2uL fresh 1M MEA, 5 uL COT, 10 uL fresh GLox, 100 uL 50% glucose, 420 uL 200 mM Tris pH 8.0
  • we’ll see how things look in STORM
  • dye switching looks alright, density is pretty low (25,000 frames of switching instead of 50-80K).
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