[BioC] How to analysis the this kind of data set?

Fangxin Hong fhong at salk.edu
Fri Apr 8 02:38:44 CEST 2005

Hi Xiao;
I think maybe you want to identify differentially expressed genes under
treatment (a,b,ab) compared to untreated group, across all time points.
Say X=log(R/G) (a vector of 6 as the log ratio of red and green
intensities across 6 common time.)
H0: X=0 vs Ha: X!=0

If you don't have replications, ANOVA is not possible if you treat time as
a factor. There are some publications on this topic, just search pubmed
with key words "time course"


> Hi Xiao,
> It seems in a design such as this with Treatment and Time, there are a lot
> of
> ways to define 'differential expression'.  You say you're looking for
> differentially expressed genes with respect to treatment(a,b,ab).  So,
> does
> this mean you're not interested in any time effects(or any
> Treatment-by-Time
> interactions)?  Maybe you're looking for genes where the three expression
> profiles over time are parallel for the different treatments, but one of
> these
> profiles is 'far away' from the other two?
> Rhonda
>> hi,everybody
>> I have a *time course* data set about a CML cell line treated by two
>> drugs
>> and their combination.The experiment was performed on cDNA microarray
>> platform.The green channel of all the arrays are common,the untreated
>> cell.Here follows the experiment design:
>> a_0hr,a_3hr,a_8hr,a_12hr,a_24hr,a_48hr,a_72hr,
>> b_3hr,b_8hr,b_12hr,b_24hr,b_48hr,b_72hr,
>> ab_3hr,ab_8hr,ab_12hr,ab_24hr,ab_48hr,ab_72hr.
>> A total of 19 *cDNA microarrays*.a_0hr means* *drug *a *treament *0
>> hours
>> vs. control. *And a_3hrs means drug a treatment 3 hours vs. control.So
>> for
>> drug *b *and their combination *ab*(drug a and drug b added together).My
>> goal is to identify the three sets of genes,the genes differentially
>> expressed by drug a,the genes by drug b ,and their combination.
>>  i am thinking about *ANOVA* ,but i am not sure whether it is correct.
>> Any comments,suggestions?Any R/bioconductor packages can be used?Thanks
>> in
>> advance
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Fangxin Hong, Ph.D.
Plant Biology Laboratory
The Salk Institute
10010 N. Torrey Pines Rd.
La Jolla, CA 92037
E-mail: fhong at salk.edu

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