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Sample GSM518347 Query DataSets for GSM518347
Status Public on Mar 10, 2010
Title SAE 13972509 GEO D6’ – cy3 vs S6’ – cy5
Sample type RNA
 
Channel 1
Source name D6’ – cy3
Organism Dictyostelium discoideum
Characteristics sample type: AX2 cells in Soerensen phosphate buffer as control. Total RNA isolated at 6h 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 S6’ – cy5
Organism Dictyostelium discoideum
Characteristics sample type: AX2 cells treated with S. typhimurium. Total RNA isolated at 6h 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)
GSE20648 Investigation of differential expression: Differentiating cells vs Salmonella infected cells (t6)
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 0.585 14.4 27111 18073 15898 1333 30821 1171
2 0.666 14.4 27379 17254 15204 1281 31071 1131
3 0.124 12.4 5799 5322 5543 1205 5567 1028
4 0.173 12.4 5751 5102 5320 1390 5516 1003
5 1298 1263 1008 993
6 1252 1340 1015 1026
7 -0.513 14.6 20153 28759 25179 1330 23019 1095
8 -0.458 14.4 18370 25226 22251 1302 20826 1064
9 0.228 13.8 15797 13492 13399 1445 15907 1103
10 0.160 13.9 15810 14154 13966 1288 16022 1053
11 -0.404 13.1 7384 9770 9974 1291 7233 1034
12 -0.417 13.0 7329 9783 9980 1340 7184 1088
13 -0.399 12.6 5355 7060 7275 1326 5197 1031
14 -0.374 12.6 5305 6872 7093 1229 5140 982
15 1204 1339 932 1043
16 1271 1201 1007 953
17 1404 1210 962 950
18 1219 1114 1049 1009
19 0.693 12.8 8759 5419 5549 1243 8554 1055
20 0.838 12.8 9854 5512 5609 1266 9684 1096

Total number of rows: 15552

Table truncated, full table size 586 Kbytes.




Supplementary file Size Download File type/resource
GSM518347.csv.gz 813.5 Kb (ftp)(http) CSV
Processed data included within Sample table

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