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Hello,
Good day and nice to meet you.
After considering and reconsidering the content of this posting, I
come to the conclusion that the solutions to the questons in this
posting could be helpful not only for those who are just dabble into
the GAGE application, but also for those who are entry users of R
packages.
I came across the GAGE package and found that it might be of great use
for my current data analysis.
After went through the manual, I understood the context and arguments
written for the demo file. However, I doubted how to implement new
arguments to suit my dataset. It is also noteworthy that through the
web-base forum, I found no single answer that is applicable to my
situation from the previous queries.
Here are the questions,
1. I realized that most, if not all or the R-users wrote their own
code for particular R function with slight differences. I also tried
to create some for my analysis. Is the following script correct for
importing the expression dataset (.csv) to be read by GAGE? Or is it
better to be formatted in text-delimited format (.txt)?
data <- read.table("C:/??????/Array.csv", sep=",", header=TRUE)
2. How to introduce customized gene set file from C:/ and adapt the
following scripts shown in the manual to execute corresponding
functions with this ???foreign??? get set file?
datakegg.gs)
datago.gs)
lapplykegg.gs[1:3],head)
3. To start analyzing the data, would you mind to show me an example
of script for the imported dataset, corresponding to the first example
in the manual? What is meant by .kegg.p and .go.p?
gse16873.kegg.p <- gage(gse16873, gsets = kegg.gs,
ref = hn, samp = dcis)
gse16873.go.p <- gage(gse16873, gsets = go.gs,
ref = hn, samp = dcis)
Let???s assume that the control is hn, positive sample is dcis, whilst
the ???gse16873??? file is not pre-loaded into the GAGE library, but
being introduced from elsewhere in C:/.
4. What is the least number of sample for control and treatment to be
included for GAGE analysis, respectively? Is there any limit of the
total number of expression datasets to be analyzed in each session of
GAGE? Many literatures shown that other methods have statistical
limitations for particular size of sample dataset, which influence the
outcome of the whole analysis.
Your reply is utmost appreciated.
Thanks in advance!
Sincerely,
Aurelle
-- output of sessionInfo():
The dataset contains control and treatment (2 groups). The replicate
ranged from 2 to 10 for each group.
--
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