Question: Analyzing Agilent custom array in R
gravatar for arisarkar88
2.5 years ago by
arisarkar880 wrote:

How to analyze datasets corresponding to 'Agilent-016332 Human Gene Expression 8X15k (AMADID: 16332)' in R?

agilent microarrays analyze • 1.1k views
ADD COMMENTlink modified 2.5 years ago by James W. MacDonald51k • written 2.5 years ago by arisarkar880
Answer: Analyzing Agilent custom array in R
gravatar for James W. MacDonald
2.5 years ago by
United States
James W. MacDonald51k wrote:

You would most likely want to use limma. Using the only GEO data set for this array as an example:

> library(GEOquery)

> getGEOSuppFiles("GSE72246")
trying URL ''
Content type 'application/x-tar' length 142499840 bytes (135.9 MB)
downloaded 135.9 MB

trying URL ''
Content type 'text/plain' length 3621 bytes
downloaded 3621 bytes
> setwd("GSE72246/")
> untar("GSE72246_RAW.tar")

> dat <- read.maimages(dir(".", "txt.gz"), "agilent.median", green.only = TRUE)
Read GSM1858547_S08-0285_Day1_201.txt.gz
Read GSM1858548_S08-0296_Day1_101.txt.gz
Read GSM1858549_S08-0300_Day1_203.txt.gz
Read GSM1858550_S08-0308_Day57_201.txt.gz
Read GSM1858551_S08-0322_Day57_101.txt.gz
Read GSM1858552_S08-0326_Day1_104.txt.gz
Read GSM1858553_S08-0328_Day1_301.txt.gz
Read GSM1858554_S08-0329_Day57_203.txt.gz
Read GSM1858555_S08-0334_Day1_702.txt.gz
Read GSM1858556_S08-0337_Day1_204.txt.gz
Read GSM1858557_S08-0339_Day1_206.txt.gz
Read GSM1858558_S08-0341_Day1_502.txt.gz
Read GSM1858559_S08-0350_Day1_207.txt.gz
Read GSM1858560_S08-0351_Day1_208.txt.gz
Read GSM1858561_S08-0352_Day1_106.txt.gz
Read GSM1858562_S08-0358_Day1_304.txt.gz
Read GSM1858563_S08-0359_Day1_801.txt.gz
Read GSM1858564_S08-0363_Day57_104.txt.gz
Read GSM1858565_S08-0365_Day57_301.txt.gz
Read GSM1858566_S08-0370_Day1_802.txt.gz
Read GSM1858567_S08-0372_Day57_702.txt.gz
Read GSM1858568_S08-0377_Day1_308.txt.gz
Read GSM1858569_S08-0378_Day1_307.txt.gz
Read GSM1858570_S08-0379_Day1_107.txt.gz
Read GSM1858571_S08-0382_Day57_204.txt.gz
Read GSM1858572_S08-0383_Day57_206.txt.gz
Read GSM1858573_S08-0384_Day57_502.txt.gz
Read GSM1858574_S08-0385_Day1_505.txt.gz
Read GSM1858575_S08-0392_Day57_207.txt.gz
Read GSM1858576_S08-0394_Day57_208.txt.gz
Read GSM1858577_S08-0396_Day57_106.txt.gz
Read GSM1858578_S08-0405_Day57_801.txt.gz
Read GSM1858579_S08-0407_Day1_705.txt.gz
Read GSM1858580_S08-0410_Day57_304.txt.gz
Read GSM1858581_S08-0417_Day1_312.txt.gz
Read GSM1858582_S08-0420_Day1_209.txt.gz
Read GSM1858583_S09-0427_Day57_802.txt.gz
Read GSM1858584_S09-0430_Day57_107.txt.gz
Read GSM1858585_S09-0431_Day57_308.txt.gz
Read GSM1858586_S09-0434_Day57_307.txt.gz
Read GSM1858587_S09-0439_Day57_505.txt.gz
Read GSM1858588_S09-0440_Day1_210.txt.gz
Read GSM1858589_S09-0441_Day1_506.txt.gz
Read GSM1858590_S09-0459_Day57_705.txt.gz
Read GSM1858591_S09-0461_Day57_312.txt.gz
Read GSM1858592_S09-0463_Day57_209.txt.gz
Read GSM1858593_S09-0467_Day57_210.txt.gz
Read GSM1858594_S09-0468_Day57_506.txt.gz

And now you can make whatever comparisons you might like. The limma User's Guide has examples of reading in this sort of data on p. 19, and a worked example starting on p. 110. But after the normalization step, a single color Agilent analysis isn't materially different from any of the Affy examples, and you could use one or more of those as an example since the Agilent example is a time course.

ADD COMMENTlink written 2.5 years ago by James W. MacDonald51k

Thank you for the reply. It was really helpful. I checked the user guide for limma. Therein Quantile normalization has been used. Is it possible to use '75th percentile/upper quartile' normalization using limma?

ADD REPLYlink written 2.5 years ago by arisarkar880

You can find all the available choices for normalization on the help page ?normalizeBetweenArrays

ADD REPLYlink written 2.5 years ago by James W. MacDonald51k
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