Hi Even,
Thanks for your response.
Best
Tiger


2013/1/21 Johnson, William Evan <wej@bu.edu>

>  See below:
>
>  On Jan 21, 2013, at 4:36 PM, hu duan wrote:
>
>  Hi Evan,
> Thanks for your quick response. I may list some interesting result.
>
>    1. The density plot on the left bottom in previous email shown red
>    line had a sharp peak while black not. Can you inform me what does that
>    difference mean?
>
>   Black = density estimate of the batch effects (used directly by
> non-parametric adjustments)
> Red= Normal/invgamma distributions used for the parametric adjustments
>
>  Ultimately, if the black curve in the first plot is roughly bell shaped,
> you won't see much difference in the batch effect adjustments.
>
>
>    1. I just finished analysis of the nonparametric and parametric for a
>    same data. The following two plots shown here, which the Y axis is the
>    parametric and X axis is the nonparametric. It seems nonparametric approach
>    will tend to increase signal. The mean for CV for that is 1.7% while median
>    is 0.37%. The data looks pretty close.
>
>
>  Yes, they are usually very similar unless the black and red lines are
> very different from each other.
>
>
>    1.
>    2. For the run time, I did a PCA analysis by using all features. The
>    left pic shown different run times in different color, which clearly shown
>    run time difference. Right one is after adjust by parametric approach.
>    Would you consider batch effects have been removed?
>
>   Yes, looks like the batch effects are gone.
>
>
>    1.
>    2. If I run Combat analysis in same data and use the adjust data to
>    run Combat again, do you think the result will be better or it will
>    overfitting your model? Does the model converge?
>
>   Yes, you might be overfitting a little, but the EB helps reduce the
> amount of over-fitting. Also, due to you experimental design, over-fitting
> shouldn't be a huge issue.
>
>
>    1.
>
>  Best
> Tiger
> <image.png>
>  <image.png>
>
>
>
> 2013/1/21 Johnson, William Evan <wej@bu.edu>
>
>> Tiger,
>>
>>  For question #1: The parametric plots look fine. What you are really
>> looking for here are major distributional deviations from these plots. They
>> actually look pretty good. You'll find only very small differences between
>> the parametric and non-parametric results. Also, no there should not have
>> been a plot for the non-parametric adjustment, as it uses the empirical
>> prior directly, so there are no distributional assumptions to check.
>>
>>  Question #2: Check to see if there is a clear "run time" batch effect.
>> If so, compare the two step with the single step. If you have only a few
>> nest run times in each experiment, then the two approaches will be very
>> similar. I would trust the two step approach more than the one-step method.
>>
>>  Hope this helps.
>>
>>  Evan
>>
>>  P.S. I hope you don't mind, I cc'd the bioconductor mailing list where
>> we are now using to answer questions on ComBat.
>>
>>
>> Begin forwarded message:
>>
>>  *From: *hu duan <hu.duan@asu.edu>
>>  *Subject: **about ComBat plot for non parametric*
>>  *Date: *January 21, 2013 3:52:46 PM EST
>>  *To: *wejlab@gmail.com
>>  *Reply-To: *hu.duan@asu.edu
>>
>> Hi Dr. Johnson
>> I am performing a microarray experiment on cancer research with multiple
>> run times in the two batch of arrays.
>>
>> 1. I have tried your Combat analysis with par.prior=T.
>>
>> The attachment is the plot. There is a difference between red and black
>> line, I am not sure whether it can be called a  major violation.
>> I have also tried the nonparametric one. The output was finished but
>> without any plot. Is that normal without a plot?. How should I judge the
>> nonparametric work?
>>
>> 2. Should I first do a Combat analysis in the same batch of slides with
>> multiple run time and then use the adjusted data to do with another batch
>> OR I could do them together?
>> Best
>> Tiger
>> [image: 内嵌图片 2]
>>  --
>> Hu Duan (Tiger)
>> Biological Design PhD student
>> Graduate Research Associate
>> Center for Innovation in Medicine
>>   The Biodesign Institute, Arizona State University
>>  --------------------------------------------------------------
>> -------------------------
>> "MY MIND REBELS AT STAGNATION." -- Sherlock Holmes
>>   ---------------------------------------------------------------
>> ------------------------
>>
>>
>>
>
>
>  --
> Hu Duan (Tiger)
> Biological Design PhD student
> Graduate Research Associate
> Center for Innovation in Medicine
>   The Biodesign Institute, Arizona State University
>  --------------------------------------------------------------
> -------------------------
> "MY MIND REBELS AT STAGNATION." -- Sherlock Holmes
>   ---------------------------------------------------------------
> ------------------------
>
>
>


-- 
Hu Duan (Tiger)
Biological Design PhD student
Graduate Research Associate
Center for Innovation in Medicine
The Biodesign Institute, Arizona State University
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"MY MIND REBELS AT STAGNATION." -- Sherlock Holmes
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