[BioC] Memory issues with limma and ImaGen file import

[Gordon Smyth]

Dear Christian,

limma 2.4.15 reads successfully all the ImaGene files which the 
package authors have access to, so we can't reproduce the error you report.

I'm not ruling out a limma error, but the memory error you report 
doesn't sound necessarily as if the problem is with limma.

Can you read your file with an earlier version of limma? What version 
of R? What other packages do you have loaded? What do you see if you type

   x <- readImaGeneHeader(targets$FileNameCy3[1])
   names(x)
   x$NHeaderRecords


Best wishes
Gordon


>Date: Fri, 28 Apr 2006 16:21:43 +0200
>From: "Christian Spieth" <Christian.Spieth at uni-tuebingen.de>
>Subject: [BioC] Memory issues with limma and ImaGen file import
>To: <bioconductor at stat.math.ethz.ch>
>
>Hi,
>
>I am having a problem with limma 2.4.13 and ImaGene files:
>Whenever I try to read the files as described in the manual
>
>targets <- readTargets()
>files <- targets[,c("FileNameCy3","FileNameCy5")]
>RG <- read.maimages(files, source ="imagene")
>
>R aborts the operation with the following error message:
>
> > RG <- read.maimages(files,source="imagene")
>Read header information
>Fehler: kann Vektor der Gr??e 3200000 Kb nicht allozieren
>(Error: unable to allocate a vector of size 3200000 Kb)
>
>I am trying to read 10 chip files ( 5 replication with red and green).
>Each file is approx. 6MB. Is there a special format of the ImaGene files?
>My files start with
>
>
>Begin Header
>         version 5.6.1
>         Date    Mon Apr 24 20:13:17 CEST 2006
>         Image File
>X:\Lab_Hochholdinger\Individual_folders\Diana\microarray\lrt\replicate1\01Mu
>rot\0G701Murot.tif
>         Page    0
>         Page Name
>         Inverted        false
>         Begin Field Dimensions
>                 Field   Metarows        Metacols        Rows    Cols
>                 A       8       4       20      20
>                 B       4       4       20      20
>         End Field Dimensions
>         Begin Measurement parameters
>                 Segmentation Method     auto
>                 Signal Low      0.0
>                 Signal High     0.0
>                 Background Low  0.0
>                 Background High 0.0
>                 Background Buffer       3.0
>                 Background Width        5.0
>         End Measurement parameters
>         Begin Alerts
>                 Control Type    Minimum threshold       If tested
>Percentage allowed      If failed       Maximum threshold       If tested
>Percentage allowed      If failed       CV threshold    If tested       If
>failed
>         End Alerts
>         Begin Quality settings
>                 Empty Spots     true    Threshold:      2.0
>                 Poor Spots      true
>                 Begin Poor Spots Parameters
>                         Background contamination flag   true    Threshold:
>0.9995
>                         Background tested against subgrid data only     true
>                         Signal contamination flag       false   Threshold:
>0.9995
>                         Signal contamination test connected to background
>contamination threshold false
>                         Ignored percentage flag true    Threshold:      25.0
>                         Open perimeter flag     true    Threshold:      30.0
>                         Shape regularity flag   true    Threshold:      0.6
>                         Area To Perimeter Ratio flag    false   Threshold:
>0.7
>                         Offset flag     true    Threshold:      60.0
>                 End Poor Spots Parameters
>                 Negative Spots  true
>
>         End Quality settings
>End Header
>Begin Raw Data
>         Field   Meta Row        Meta Column     Row     Column  Gene ID Flag
>Signal Mean     Background Mean Signal Median   Background Median
>Signal Mode     Background Mode Signal Area     Background Area Signal Total
>Background Total        Signal Stdev    Background Stdev        Shape
>Regularity      Ignored Area    Spot Area       Ignored Median  Area To
>Perimeter       Open Perimeter  XCoord  YCoord  Diameter        Position
>offset  Offset X        Offset Y        Expected X      Expected Y      CM-X
>CM-Y    CM Offset       CM Offset-X     CM Offset-Y     Min Diam        Max
>Diam    Control Failed Control  Background contamination present
>Signal contamination present    Ignored % failed        Open perimeter
>failed  Shape regularity failed Perim-to-area failed    Offset failed
>Empty spot      Negative spot   Selected spot
>         A       1       1       1       1       HakeT2_V2-I-13-CB250166 0
>6628.6592       637.9275        6496.0  542.0   6694.4912       441.2314
>179.0   262.0   1186530.0       167137.0        2784.5909       466.856
>0.895   0.0     179.0   null    0.9763  0.0     1898.0  5548.0  16.0
>1.824   -0.7266 -1.673  1898.7266       5549.673        1898.3799
>5547.8547       1.851   -0.3467 -1.8183 14.7603 15.6522         0       0
>0       0       0       0       0       0       0       0       0
>
>......
>
>
>
>
>The error happens both under Windows (1GB RAM) and Linux (4GB RAM).
>Anyone an idea?
>
>Thanks in advance!
>
>christian
>
>
>--
>  Christian Spieth
>  Dipl.-Ing., MSc (Oxon)
>  Center for Bioinformatics (ZBIT), Univ. Tuebingen
>  NGFN - Nationales GenomForschungsNetz
>  Sand 1, D-72076 Tuebingen, Germany
>  Phone (+49/0) 7071 29 78987, Fax (+49/0) 7071 29 5091
>mailto:christian.spieth at uni-tuebingen.de
>  http://www-ra.informatik.uni-tuebingen.de
>
>  PGP fingerprint =  8A AC FD DA 57 A3 15 67  23 16 15 0A BD 04 AC A7  MD5
>  Fingerprint =  22a9627dcc5302371de7764b40c2be6d