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Sample GSM518372 Query DataSets for GSM518372
Status Public on Mar 10, 2010
Title SAE 13727645 GEO D3 – cy3 vs S3 – cy5
Sample type RNA
 
Channel 1
Source name D3 – cy3
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 Cy3
Label protocol Fairplay indirect labelling kit (Stratagene)
 
Channel 2
Source name S3 – cy5
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 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 0.668 13.0 10160 6394 6310 1583 10295 1190
2 0.496 12.8 8463 5999 5943 1524 8543 1159
3 0.006 11.2 2440 2429 2487 1577 2383 1156
4 2980 1815 2225 1254
5 1770 1637 1456 1218
6 -0.013 10.8 1750 1765 1897 1573 1628 1253
7 -0.028 12.5 5892 6006 6069 1624 5831 1178
8 -0.116 12.5 5427 5881 6031 1506 5292 1160
9 0.333 11.5 3143 2496 2576 1595 3045 1128
10 -0.221 11.5 2726 3176 3290 1599 2632 1170
11 0.013 12.4 5431 5383 5562 1533 5256 1172
12 -0.003 12.5 5869 5879 5967 1525 5783 1189
13 0.049 11.7 3274 3164 3311 1600 3129 1133
14 -0.134 11.7 3103 3405 3570 1512 2960 1152
15 1504 1641 1179 1154
16 1531 1550 1213 1164
17 1636 1505 1191 1169
18 1549 1580 1187 1147
19 0.510 12.8 8679 6094 6031 1562 8770 1205
20 0.369 12.8 8172 6326 6264 1547 8253 1154

Total number of rows: 15552

Table truncated, full table size 605 Kbytes.




Supplementary file Size Download File type/resource
GSM518372.csv.gz 794.1 Kb (ftp)(http) CSV
Processed data included within Sample table

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