Category Archives: General STORM

buffer tests 04/23/14

1% BME 10 mM MEA 0.5% BME + COT 2% BME + COT 10 mM MEA + COT 50 mM MEA +COT 50 mM MEA + SSC + COT

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STORM Users planning meeting

STORM2 Max Laser Powers 488 laser head (100%): 580 mW 488 before expander: 275 mW 488 microscope backport: 180 mW 561 at head (2100mW in GUI): HIGH 561 laser at beam expander: 1500 mW 561 laser at backport 900 mW … Continue reading

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STORM2 dye and buffer testing

optimizing buffer conditions for deep 3D imaging of A647 and A750 labeled chromatin First buffer 750 and 647_storm_0001 – 0004 1/2x BME (new) 2 mM COT (new, reg strength) 350-380 mW 647 laser (2960 mA) 2100 mA of A750 1% … Continue reading

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improved cluster analysis

search radius cluster algorithm fastest implimentation is hist3 with binsize = search radius can easily require multiple molecules in the search radius by filtering: M=hist3([x,y],[Xmin:radius:Xmax,Ymin:radius:Ymax]); so if we want 15 nm search radius, just make 15nm steps M>3 require at … Continue reading

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3D chromatic warp: Insight vs DaoSTORM

Results using 2013-13-02 Bead Data: Z-calibrations for this data set look pretty similar Comparing Chromatic warping DaoSTORM is actually getting a better fit and tighter warp, but not managing to get the same dynamic range in Z — only +/- … Continue reading

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z-calibration: Insight vs DaoSTORM

with single iteration, Hazen 3D-DaoSTORM avoids splitting molecules more distant from frame A few notes on 3D-DaoSTORM First 4 iterations are computed with 4x the input threshold. So if using less than 4 iterations you want to quarter the threshold … Continue reading

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chromatic warping: general formulation

Description of problem There are N different color channels which are imaged through different filters, and need to be mapped together to an accuracy greater than the resolution limit of the instrumentation / detection system (e.g. 10-20 nm for STORM, … Continue reading

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z-calibration part 4

There are two problems with the maximal alignment approach: it is still a bit slow (though much faster than the iterative method). it decouples wx and wy, and the simulated annealing allows for some generally small but arbitrary jiggle in … Continue reading

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z calibration part 3

Maximal alignment achieved through simulated annealing. Basically we have a whole bunch of short fragments of the longer, true z-curve, and we don’t know their z-offset displacement. So we jiggle them around and find the parts of them that match. … Continue reading

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Z-calibration part 2

Curves fit the following polynomial: $latex w_x=\sqrt{w_{x0} \sqrt{B_xX^4+A_xX^3+X^2+1}}$ where $latex X= (z-g_x)/(z_{rx})$ In general we will require $latex gx$ to be negative $latex gy$ to be positive. $latex Ax$ and $latex Bx$ are correction factors and should be small. See … Continue reading

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