[BioC] followup on reading RNA digestion plots

[Naomi Altman]

Looking at the plot, I would not take the slopes too seriously!

I only eliminate an array if it appears to be dramatically different from 
the others.  Your arrays vary (which is expected) but I do not see any 
outlying array.

I suppose you could do a formal test, but I wouldn't bother.  To do the 
test, you would probably want to use a semiparametric model of the form

curve(i) = m(i) + s(x)

where s(x) is the mean curve and m(i) is a random array effect.  Once you 
fit the model, you could test the goodness of fit of each curve to the 
model, adjust for multiple comparisons, and reject any significant 
curves.  Sorry, I do not have a reference for this.

--Naomi

At 08:35 AM 3/28/2005, Swati Ranade wrote:

>   Hello,
>
>  A while ago I had posted a question about amplified>
>RNA experiment and  guidelines one should follow
>during data analysis and Dr. Gentleman had suggested
>that RNA digestion plot will be a good indicator for
>deciding which samples should be used in data analysis
>as it is important to comapre likes. For my
>experiments,I think prima facie the plots look quite a
>bit similar but since I am new to this area
>I cannot estimate what should be range of difference
>in slopes that one should tolerate while choosing the
>comparable profiles. To give an idea of what I am
>seeing I am attaching a postscript image and giving
>the slopes at the bottom of this email. I will be
>extremely obliged if somebody could provide me
>further guidance so that I know I am on the right
>track. Please let me know if I need to provide more
>than the following information?
>
>  Thanks,
>
>  Swati
>
>Here is the data: (I think sample # 8 seems to have
>a slope that is different fro the rest!! Should it be
>eliminated or one should observe the trend of the
>graph?)
>$slope
>  [1] 1.6329065 1.5580935 1.5640235 0.9613637
>  1.2156617 1.2004132 1.4831510
>  [8] 0.3772531 1.6212330 1.2952673 1.2148458
>  1.6020575 1.8564214 1.0944649
>
>
>
>
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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