fold change question

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# fold change question

Hi,

I am trying to develop an estimate for the fold change in the expression level of a gene, under 2 conditions A and B. I take three signal intensity measurements in each condition, say, IntA(1), IntA(2), IntA(2) etc. The signal intensity provides a direct measure of expression level.

What is the best way to develop an estimate for the fold-change between A and B?

Two possible ways:

1)

IntA(mean)= Mean of the 3 intensity measurements under condition A.

IntB(mean)= Mean of the 3 intensity measurements under condition B.

Mean fold change = IntA(mean)/ IntB(mean)

2)

I calculate all 9 possible foldchanges: IntA(1)/IntB(2); IntA(1)/IntB(3); IntA(2)/IntB(1); IntA(2)/IntB(2) etc..

Then Mean fold change = Mean of the 9 fold changes.

Any feedback on which method is more suitable would be very much appreciated.

Thanks in advance!

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## Re: fold change question

thank you both for your replies.

## Re: fold change question

OK, dh2718. Let Fa and Fb be the numerator and the denominator of the estimated fold change, F

I tried to minimize the following function:

D= [(IntA(1)-Fa)^2+(IntB(1)-Fa)^2+(IntA(1)-Fa)^2+(IntB(2)-Fa)^2+...]

Result: Fa= [IntA(1)+IntA(2)+IntA(3)]/3

Fb= [IntB(1)+IntB(2)+IntB(3)]/3

However, if I try to minimize:

D= [(IntA(1)-F*IntB(1))^2+(IntA(1)-F*IntB(2))^2+(IntA(1)-F*IntB(2))^2+...]

F= [IntA(1)/IntB(1)+IntA(1)/IntB(2)+........]/9

I will stick to the first minimization to estimate Fa and Fb.

Thanks for your input

## Re: fold change question

Off hand I would recommend method 1.

## Re: fold change question

Method 3 - The least mean square estimate. F being the meand fold change, minimize the F-function:

[IntA(1) - F*IntB(1)]^2 + [IntA(2) - F*IntB(2)]^2 + ...