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Sample GSM518379 Query DataSets for GSM518379
Status Public on Mar 10, 2010
Title SAE 13972527 GEO D3 – cy5 vs S3 – cy3
Sample type RNA
 
Channel 1
Source name S3 – cy3
Organism Dictyostelium discoideum
Characteristics sample type: AX2 cells treated with S. typhimurium. Total RNA isolated at 3h time point.
strain: AX2
Extracted molecule total RNA
Extraction protocol RNA was isolated using TRIzol
Label Cy3
Label protocol Fairplay indirect labelling kit (Stratagene)
 
Channel 2
Source name D3 – cy5
Organism Dictyostelium discoideum
Characteristics sample type: AX2 cells in Soerensen phosphate buffer as control. Total RNA isolated at 3h time point.
strain: AX2
Extracted molecule total RNA
Extraction protocol RNA was isolated using TRIzol
Label Cy5
Label protocol Fairplay indirect labelling kit (Stratagene)
 
 
Hybridization protocol Cy3 and Cy5 labelled targets were mixed, ethanol precipitated and dissolved in 65 µl of hybridisation buffer (Noegel et al., 1985) with 500 µg/ml Fish sperm DNA (Roche, Mannheim, Germany) and 2 µM Oligo dA 18-mer. The hybridisation mix was heated to 80 °C for 10 min, applied to the microarray under a cover-slip and incubated in a hybridisation chamber (Corning, New York, USA) for 15 hours at 37°C. Post-hybridisation washes were performed twice with 2x SSC, 0.1% SDS and once with 0.1x SSC, 0.1% SDS for 5 min each, five times with 0.1x SSC and once with with 0.01x SSC for 5 sec each and dried by centrifugation at 235xg for 5 min.
See also Farbrother et al., Cell. Microbiol., 3:438-456, 2006.
Scan protocol Signal detection was performed with the ScanArray 4000XL confocal laser scanner (PerkinElmer Life Sciences, Wellesley, USA). Images for Cy3 and Cy5 were obtained, spots were detected and quantified with ScanArray Express v2.2 (PerkinElmer Life Sciences), then manually inspected and if necessary corrected.
See also Farbrother et al., Cell. Microbiol., 3:438-456, 2006.
Description DNA microarrays cotainining 5,423 non-redundant ESTs from the D. discoideum cDNA project (Urushihara et al., 2004), partial sequences of 450 selected genes, probes of the SpotReport-10 Array Validation System (Stratagene, La Jolla, USA) and appropriate positive and negative controls were produced in-house using standard protocols (see also: http://www.uni-koeln.de/medfak/biochemie/transcriptomics/ production.e.shtml). Briefly, probes were amplified by two 100µl PCR reactions in 96-well microtiter plates using standard primers (M13F2: 5’-GTAAAACGACGGCCAGTG-3’, M13R2: 5’-C6-Aminolink-ACCATGATTACGCCAAGC-3’) for the cloned ESTs and gene-specific primers for the selected genes and the positive controls. After analysis by agarose gel electrophoresis (10µl of each reaction) the two reactions were combined, precipitated, solubilised in 11µl 25% DMSO, 1µl separated again by agarose gel electrophoresis and evaluated (Farbrother et al., 2002). Probes were transferred with the proteineer dp pipetting robot (Bruker, Germany) into 384-well microarray plates with cylindrical wells (Abgene, Hamburg, Germany) and printed onto UltraGaps slides (Corning, New York, USA) at 18°C and 45% humidity with a BioRobotics MicroGrid 600 microarray robot (Genomic Solutions, Huntingdon, UK) using MicroSpot 2500 microarraying pins. Each probe was spotted in duplicate, positive and negative controls were spotted 6, 24, 192 or 286 times and the SpotReport controls 96 times. The microarray is composed of three grids with 16 subarrays each and 14,620 spots in total. The complete microarray dataset is available at GEO, http://www.ncbi.nlm.nih.gov/geo; accession number GPL1972.
Data processing For each individual comparison four microarrays were hybridised and analysed. Two imagepairs were produced per microarray slide, one with high laser intensity so that signals for most probes and also some saturated signals were obtained and a second one with lower laser intensity so that none of the signals was saturated. This way the dynamic range of the measurement was expanded. To handle the import and export of microarray data to different analysis programs an Excel Add-In, Array tools (http://www.uni-koeln.de/med-fak/biochemie/ transcriptomics/tools-array.e.shtml), was programmed in Visual Basic. Upon import of two data files of the same microarray scanned with different laser powers the saturated spots of the high laser power scan were replaced by non-saturated spots from the low laser power scan. In addition the import also performed data filtering by flagging SpotReport controls, negative controls, empty spots, spots where only spotting solution was printed and spots whose intensities were below or equal to zero as "Bad". Fluorescence ratios were normalised by LOWESS-norma-lisation using R1.6.2 (BioConductor, http://www.bioconductor.org/). The normalized M values (M = log2 (Intensityexperiment/Intensitycontrol) were transferred into a new worksheet for significance analysis of microarrays (SAM) analysis (Tusher et al., 2001). At the transfer all probes spotted in higher replicates were reduced to double spots by averaging. Furthermore all probes that were flagged "Found" in less than half of the spots, were excluded from SAM analysis. Differentially regulated genes were identified using the one-class SAM method calculating 1000 permutations. The SAM program not only identifies the differentially regulated genes, but also predicts the number of false positives. These are the genes that are falsely reported as differentially expressed. This feature was used in all microarray experiments to set the significance level such, that the 90th percentile of the false discovery rate (FDR) was minimal.
See also Farbrother et al., Cell. Microbiol., 3:438-456, 2006.
 
Submission date Mar 05, 2010
Last update date Mar 09, 2010
Contact name Ludwig Eichinger
E-mail(s) ludwig.eichinger@uni-koeln.de
Phone +49 221 478 6928
Organization name Institute for Biochemistry 1
Lab AG Eichinger
Street address Joseph-Stelzmann-Strasse 52
City Cologne
ZIP/Postal code 50931
Country Germany
 
Platform ID GPL1972
Series (2)
GSE20651 Investigation of differential expression: Differentiating cells vs Salmonella infected cells (t3)
GSE20688 Salmonella infected Dictyostelium discoideum

Data table header descriptions
ID_REF
VALUE Normalised M-value; M=log2(Intensity_Exp/Intensity_Con)
A Norm Normalised A-value; A=log2 times square root of (I_Exp x I_Con)
Exp Norm Normalised intensity value of experiment
Con Norm Normalised intensity value of control
Con Median Median intensity value of control
Con B Median Median background intensity value of control
Exp Median Median intensity value of experiment
Exp B Median Median background intensity value of experiment

Data table
ID_REF VALUE A Norm Exp Norm Con Norm Con Median Con B Median Exp Median Exp B Median
1 -0.382 14.3 17482 22781 26473 1138 15044 1108
2 -0.388 14.4 19125 25030 29462 1201 16248 1233
3 -0.110 11.9 3807 4108 4133 1645 3784 1577
4 -0.257 11.7 3132 3742 3797 1405 3087 1520
5 1263 1231 1325 1324
6 1043 1184 1446 1371
7 -0.323 13.0 7080 8856 9682 1191 6476 1409
8 -0.467 13.0 6900 9536 10416 1296 6317 1368
9 0.236 14.6 27370 23239 27827 1362 22857 1505
10 0.208 14.6 26132 22627 26977 1268 21918 1441
11 0.376 13.8 16291 12550 14454 1212 14145 1442
12 0.246 13.4 12051 10164 11059 1212 11076 1401
13 0.177 13.0 8604 7609 8313 1211 7876 1447
14 0.243 13.0 8921 7541 8226 1208 8178 1435
15 1358 1306 1433 1546
16 1224 1547 1285 1499
17 1249 1328 1553 1374
18 1223 1264 1377 1439
19 -0.017 13.4 10935 11065 12031 1427 10057 1609
20 -0.165 13.5 11268 12634 13946 1905 10208 1786

Total number of rows: 15552

Table truncated, full table size 627 Kbytes.




Supplementary file Size Download File type/resource
GSM518379.csv.gz 832.0 Kb (ftp)(http) CSV
Processed data included within Sample table

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