I have obtained some raw data from GEO (GSE40115) for the SurePrint G3 Human GE 8x60K Microarrays. I am looking to normalise this by quantile normalisation, however I can't decipher what are the relevant columns to use, I have a look around for agilent header information but can only find details about probes.

Also if anyone has an idea on how to combine samples into a single matrix easily that would be useful.

 FEATURES FeatureNum Row Col SubTypeMask ControlType       ProbeName  SystematicName PositionX PositionY   LogRatio LogRatioError
1     DATA          1   1   1         260           1 GE_BrightCorner GE_BrightCorner   24708.0   636.321  0.2140902    0.06446019
2     DATA          2   1   2          66           1      DarkCorner      DarkCorner   24740.4   636.500  0.0000000    0.62317094
3     DATA          3   1   3          66           1      DarkCorner      DarkCorner   24772.2   636.500  0.0000000    0.62336874
4     DATA          4   1   4           0           1  ERCC-00040_174  ERCC-00040_174   24803.8   636.564 -0.3058726    0.25747479
5     DATA          5   1   5           0           0    A_23_P121637       NM_003619   24835.6   636.523 -0.9495249    0.10866640
6     DATA          6   1   6           0           0     A_23_P85903       NM_003268   24867.3   636.532  1.0358744    0.11478085
  PValueLogRatio gProcessedSignal rProcessedSignal gProcessedSigError rProcessedSigError gMedianSignal rMedianSignal
1   8.960652e-04     28894.180000     47304.290000        2889.421000        4730.433000       17751.0       47819.0
2   1.000000e+00         4.674576         5.929726           4.688329           5.946516          60.0          87.0
3   1.000000e+00         4.723133         6.010852           4.737029           6.027871          64.0          94.0
4   2.348448e-01        19.068100         9.428331           4.994801           6.395058          77.0         108.0
5   2.373133e-18       577.647600        64.884070          57.935810           9.329354         386.5         157.5
6   1.800212e-19       123.970200      1346.455000          13.190320         134.814600         135.5        1441.5
  gBGMedianSignal rBGMedianSignal gBGPixSDev rBGPixSDev gIsSaturated rIsSaturated gIsFeatNonUnifOL rIsFeatNonUnifOL gIsBGNonUnifOL
1              44              77   6.119108   16.61561            0            0                0                0              0
2              44              77   6.100530   16.88031            0            0                0                0              0
3              44              77   6.060663   17.00620            0            0                0                0              0
4              43              76   6.052998   16.84867            0            0                0                0              0
5              44              76   6.107882   16.99665            0            0                0                0              0
6              44              77   6.186906   17.31859            0            0                0                0              0
  rIsBGNonUnifOL gIsFeatPopnOL rIsFeatPopnOL gIsBGPopnOL rIsBGPopnOL IsManualFlag gBGSubSignal rBGSubSignal gIsPosAndSignif
1              0             0             0           1           1            0 17922.100000 48401.700000               1
2              0             0             0           1           0            0    -6.257540   -11.001600               0
3              0             0             0           1           0            0    -0.910912    -0.267662               0
4              0             1             0           1           1            0    10.475700    10.132900               1
5              0             0             0           1           1            0   329.323000    65.797000               1
6              0             0             0           1           0            0    69.787200  1355.890000               1
  rIsPosAndSignif gIsWellAboveBG rIsWellAboveBG SpotExtentX gBGMeanSignal rBGMeanSignal
1               1              1              1     25.7310       43.9275       78.8626
2               0              0              0     26.8924       44.0073       78.9792
3               0              0              0     27.2685       44.0236       78.9094
4               1              0              0     27.2685       43.9348       78.1473
5               1              1              1     26.8924       44.0412       78.5506
6               1              1              1     27.1750       44.1255       79.2054

Code is already available to parse the headers for you. Just use:

library(limma)
x <- read.maimages(files, source="agilent")

where 'files' is a vector of file names for the files you downloaded from GEO. This will read the relevant columns from all the files into a matrix-like data object that you can then normalize and use. See the help page ?read.maimages or search for "Agilent" in the limma User's Guide:

   http://www.bioconductor.org/packages/3.7/bioc/vignettes/limma/inst/doc/usersguide.pdf

GSE40115 appears to be two-color microarrays, with a common reference on the Cy3 channel, so Chapter 10 of the limma User's Guide is relevant.

You should use gBGSubSignal i.e. the background subtracted signal intensity.  Also if a probe is detected (above background) then gIsWellAboveBG should be greater than zero.