Hi James,

 

I use read.table() to read .txt file, which have 7 columns (probeID, 3
columns for control, next 3 for ko).  These data have already rma
pre-processed.  Here is the first ten lines after I used read.table:

 

> data <- read.table("Apopt_rma.txt", header=TRUE, row.names="ID")

> data[1:10,]

                Eurasnet.Apoptosis.CEL Eurasnet.Apoptosis2.CEL

AFFX-BioB-3_at                10.16030                 9.75900

AFFX-BioB-5_at                 9.56744                 9.07906

AFFX-BioB-M_at                10.38530                 9.94925

AFFX-BioC-3_at                10.30660                 9.81339

AFFX-BioC-5_at                10.97160                10.54450

AFFX-BioDn-3_at               12.43740                12.17020

AFFX-BioDn-5_at               11.80980                11.45310

AFFX-CreX-3_at                13.76850                13.67820

AFFX-CreX-5_at                13.59800                13.48740

AFFX-DapX-3_at                 7.58850                 8.05139

                Eurasnet.Apoptosis3.CEL Eurasnet.Apoptosis4.CEL

AFFX-BioB-3_at                  9.61602                 9.43489

AFFX-BioB-5_at                  9.02821                 8.83341

AFFX-BioB-M_at                  9.85227                 9.69166

AFFX-BioC-3_at                  9.75543                 9.62851

AFFX-BioC-5_at                 10.42980                10.27400

AFFX-BioDn-3_at                12.00490                12.00640

AFFX-BioDn-5_at                11.29640                11.35080

AFFX-CreX-3_at                 13.48130                13.68150

AFFX-CreX-5_at                 13.26550                13.44120

AFFX-DapX-3_at                  7.06897                 6.90034

                Eurasnet.Apoptosis5.CEL Eurasnet.Apoptosis6.CEL

AFFX-BioB-3_at                 10.29660                 9.69907

AFFX-BioB-5_at                  9.72952                 9.08717

AFFX-BioB-M_at                 10.59420                 9.92486

AFFX-BioC-3_at                 10.47480                 9.89643

AFFX-BioC-5_at                 11.15980                10.54430

AFFX-BioDn-3_at                12.58160                12.18040

AFFX-BioDn-5_at                12.12000                11.58860

AFFX-CreX-3_at                 13.86080                13.81650

AFFX-CreX-5_at                 13.78710                13.67390

AFFX-DapX-3_at                  7.07626                 7.12627

 

My phenoData is;

> pd <- read.phenoData("pData.txt", header=TRUE, row.names=1)

> show(pData(pd))

                        Target

Eurasnet-Apoptosis1.CEL     CO

Eurasnet-Apoptosis2.CEL     CO

Eurasnet-Apoptosis3.CEL     CO

Eurasnet-Apoptosis4.CEL     KO

Eurasnet-Apoptosis5.CEL     KO

Eurasnet-Apoptosis6.CEL     KO

 

Can I doing some sort of conversion for the data from output of
read.table, to make data object look like the eset object you create
from affystart(), combine with phenoData info, so I can use it to call
lmFit () and other function in limma package.

 

Thanks in advance,

Regards, 

Weiyin Zhou

Statistics and Data Analyst

ExonHit Therapeutics, Inc.

217 Perry Parkway, Building # 5

Gaithersburg, MD 20877

 

email: Weiyin.zhou@exonhit-usa.com <mailto:Weiyin.zhou@exonhit-usa.com> 

phone: 240.404.0184

fax: 240.683.7060

 

 

 


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