[BioC] image processing -fixed xircle vs. adaptive

[Sheetal Bhan]

Yeah I still don't understand how dye swaps can show such strong positive correlation. I have now started using the genisphere dendrimer kit amd theoretically it should get rid of dye bias caused by direct incorporation methods.
I have some questions about image quantification. I think that most people prefer to use the adaptive threshold method for for quantitiating the images. If we were to use the fixed circle method,and select a diameter of the spot smaller than the actual spot then only the middle or the best part of the spot would be quantitated (not true in case of donuts). I am saying this because I have observed unequal hybridization of the red and green dyes near the boundaries  of the spot. Also, when  the software finds the spots that is deleniates the spots from the background the circle is not always placed correctly on the spot. Sometimes, the circle is a liitle off form the spot. THis happens because the arryas are not printed perfectly. And even after my best efforts to align the grid this happens. I don't think it is not  feasible to sit down and move all the circles to thir best place. In this case i think if I have chosen a fixed area slightly smaller than the actual area of the spot, it would be better than adaptive method. I may be completely off track here..I would appreciate any suggestions.

Sheetal Bhan
Graduate Student
Donald B. Sittman Lab
Dept.of Biochemistry
Univ.of Mississippi Medical Center
2500 North State Street
Jackson, MS-39216
E-mail: sbhan at biochem.umsmed.edu

>>> Naomi Altman <naomi at stat.psu.edu> 08/02/05 4:02 PM >>>
I have looked at the spots causing this, and I do not see evidence of dye 
bias on the scale necessary to cause this.

--Naomi


>To: bioconductor at stat.math.ethz.ch
>From: Naomi Altman <naomi at stat.psu.edu>
>Subject: limma: positive correlation for dyeswap pairs
>Cc:
>Bcc:
>X-Eudora-Signature: <work>
>Date: Tue, 02 Aug 2005 16:48:16 -0400
>
>I have 4 arrays in technical replicate dyeswap pairs.  Using 
>duplicateCorrelation (LIMMA) I got a positive correlation for the 
>consensus correlation and I cannot understand how this is possible.  There 
>is really no evidence of dye-bias.   But 13% of the noncontrol spots have 
>correlation higher than 0.9.  I have done extensive QC on these arrays, 
>and I am happy with the quality of the data.
>
>I have attached a plot of one of the dyeswap pairs.  The left panel is M 
>array 1 vs. M array 2.  The highly correlated spots are indicated in 
>red.  The right panel is A array 1 vs A array 2.  The histogram is the 
>value of A for the highly correlated spots on array 1.
>
>The correlation is even higher if I pair the wrong set of arrays together 
>i.e. the correct blocking is 1,1,2,2 but if I put in 1,2,2,1 for the 
>blocks, 20% of the spots have correlation higher than 0.9.
>
>If anyone has any ideas, I would be happy to hear them.  The only thing I 
>can think of is dye bias.
>
>Naomi S. Altman                                814-865-3791 (voice)
>Associate Professor
>Bioinformatics Consulting Center
>Dept. of Statistics                              814-863-7114 (fax)
>Penn State University                         814-865-1348 (Statistics)
>University Park, PA 16802-2111

Naomi S. Altman                                814-865-3791 (voice)
Associate Professor
Bioinformatics Consulting Center
Dept. of Statistics                              814-863-7114 (fax)
Penn State University                         814-865-1348 (Statistics)
University Park, PA 16802-2111

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