[BioC] statistical test for time course data

[Gordon K Smyth]

Dear Rich,

> Date: Fri, 1 Feb 2013 10:30:16 -0500
> From: Richard Friedman <friedman at cancercenter.columbia.edu>
> To: chris Jhon <cjhon217 at gmail.com>
> Cc: Bioconductor mailing list <bioconductor at r-project.org>
> Subject: Re: [BioC] statistical test for time course data
>
> Dear Chris,
>
> The F-test in Limma will tell you if at least one point is different 
> from the others. It won't tell you which one.

The time course example in the limma User's Guide does use an F-test, but 
limma isn't limited to that approach.

> The program EDGE (not EdgeR which is a different program entirely) will 
> do the same based on an model which explicitly takes temporal variation 
> into account (this is why I mention it).

limma can easily do explicit temporal modelling by fitting time course 
trends, for example as polynomials or as spline curves.  It's just a 
matter of defining the design matrix.

> There is also a t-test that deals with whether a single measurement is a 
> member of the same normal distribution as other measurements. I am not 
> sure off hand, how to do this in R. If you implement this in R and do it 
> for all the rows, it may be the test that you want. If you do this, you 
> will be forgoing the empirical Bayesian increase in accuracy in Limma or 
> the explicit temporal modeling in EDGE, but that is up to you. If you do 
> this, you should current for false discoveries.

limma can test for a single observation as an outlier by creating a design 
matrix column specific for that observation.  This produces an empirical 
Bayes version of the classical t-test for an outlier.

Best wishes
Gordon

> With hopes that this help,
>
> Best wishes,
> Rich
> ------------------------------------------------------------
> Richard A. Friedman, PhD
> Associate Research Scientist,
> Biomedical Informatics Shared Resource
> Herbert Irving Comprehensive Cancer Center (HICCC)
> Lecturer,
> Department of Biomedical Informatics (DBMI)
> Educational Coordinator,
> Center for Computational Biology and Bioinformatics (C2B2)/
> National Center for Multiscale Analysis of Genomic Networks (MAGNet)
> Room 824
> Irving Cancer Research Center
> Columbia University
> 1130 St. Nicholas Ave
> New York, NY 10032
> (212)851-4765 (voice)
> friedman at cancercenter.columbia.edu
> http://cancercenter.columbia.edu/~friedman/
>
> In Memoriam, Hymie Simon
> On Jan 31, 2013, at 10:19 PM, chris Jhon wrote:
>
>> Hi Richard,
>>
>> Thank you for help.
>> In my data ,i have one point which i think it is different from other points and i would like to test statistical significance of the difference of this point.
>> Your suggestion means that there is no direct function in R that i can use,i have to use a package which implement an algorithm.
>> If so, i think edgeR can do the same analysis too,Am i right?
>>
>> Best Reagards,
>> Chris
>>
>> On Thu, Jan 31, 2013 at 11:53 PM, Richard Friedman <friedman at cancercenter.columbia.edu> wrote:
>> Dear Chris,
>>
>> 	Limma can be used to test between time points
>> treating each time point as a categorical variable.
>> The program "EDGE" from the Storey lab, can test whether
>> there is significant change over a whole time course.
>>
>> http://www.ncbi.nlm.nih.gov/pubmed/16357033
>>
>> with hopes that the above helps,
>> Rich
>> Richard A. Friedman, PhD
>> Associate Research Scientist,
>> Biomedical Informatics Shared Resource
>> Herbert Irving Comprehensive Cancer Center (HICCC)
>> Lecturer,
>> Department of Biomedical Informatics (DBMI)
>> Educational Coordinator,
>> Center for Computational Biology and Bioinformatics (C2B2)/
>> National Center for Multiscale Analysis of Genomic Networks (MAGNet)/
>> Columbia Initiative in Systems Biology
>> Room 824
>> Irving Cancer Research Center
>> Columbia University
>> 1130 St. Nicholas Ave
>> New York, NY 10032
>> (212)851-4765 (voice)
>> friedman at cancercenter.columbia.edu
>> http://cancercenter.columbia.edu/~friedman/
>>
>> "Complex numbers! Ha! Ha! There is nothing weirder
>> than imaginary numbers. Architects don't need to know
>> complex numbers. Whenever I get a  negative root for
>> an area, I throw it out. And don't talk to me about
>> quaternions. I am not going into computer animation."
>> -Rose Friedman, age 16
>>
>>
>> On Jan 30, 2013, at 11:43 PM, chris Jhon wrote:
>>
>>> Hi All,
>>>
>>> I have data at different time points for time course experiment.
>>> I have a response for each time point and i would like to test whether the
>>> difference between response of two time points is statistically significant
>>> or not.
>>> my data is linear plot where response on y axis and time on x axis.
>>>
>>> what statistical test shall i use?
>>>
>>>
>>> I appreciate any help.
>>>
>>> Best Regards,
>>> Chris

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