AlanFung:LabNotes/Rolony/2013-9-26: Difference between revisions

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*Call a base based on the signal area
*Call a base based on the signal area
*Generate the 3 base sequence based on the location of the signal
*Generate the 3 base sequence based on the location of the signal
==Tools==
==Tools==
*Images (taken with Hosuk)
*Images (taken with Hosuk)
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*whos ;Check that the variable indeed was converted into double
*whos ;Check that the variable indeed was converted into double
*Hist(DI); Display histogram of intensities of the image
*Hist(DI); Display histogram of intensities of the image
*Looks like the cutoff is at 5000
*Looks like the cutoff is at 5000
*BI = DI > 5000; threshold; choose threshold based on whatever
*iptsetpref('ImshowBorder','tight'); display image without boarder
*iptsetpref('ImshowBorder','tight'); display image without boarder
<!--Start of table definition-->
<!--Start of table definition-->
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|width="100"|'''Original Image'''
|width="100"|'''Original Image'''
|width="25"|
|width="25"|
|width="100"|'''Histogram'''
|width="100"|'''Intensity Histogram'''
|width="25"|
|width="25"|
|width="100"|'''>5000'''
|width="100"|'''>5000 Binary'''
|width="25"|
|width="25"|
|}
|}

Latest revision as of 00:55, 27 September 2013

Strip off dye coupling with formamide[edit]

  • Aspirate PBS from mattek dish with primary/secondary rolonies
  • Add 200ul preheated (65C-80C) 80% formamide in 2X SSC
  • Incubate 10min RT
  • Rinse w H2O
  • Add in 1:200-1uM 200ul (preheat 65C) ACTB-primary rolony target probe (Alexa 488) (200uM ACTB_1stRolonyFISH)
  • Incubate 10min RT
  • Rinse w 2x SSC twice
  • Add in 2X ssc
  • image

Matlab Image Analysis[edit]

Goal[edit]

  • The goal is to analyze the image taken from SBS sequencing of the primary rolony
  • I would create a threshold to screen out the noise
  • Call a base based on the signal area
  • Generate the 3 base sequence based on the location of the signal

Tools[edit]

  • Images (taken with Hosuk)

[1]

  • Matlab

Protocol[edit]

  • We will use cycle#3 Cy3 image as an example and optimize the image analysis setting
  • I=imread('sbs_cycle03_Cy3.tif') ;load the image
  • DI=double (I); Convert the image to a double class (when storing use single variable as it takes less memory, for processing convert variable to double)
  • whos ;Check that the variable indeed was converted into double
  • Hist(DI); Display histogram of intensities of the image
  • Looks like the cutoff is at 5000
  • BI = DI > 5000; threshold; choose threshold based on whatever
  • iptsetpref('ImshowBorder','tight'); display image without boarder
Images
Original Image Intensity Histogram >5000 Binary