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Sample GSM518349 Query DataSets for GSM518349
Status Public on Mar 10, 2010
Title SAE 13972543 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 -0.205 13.4 10246 11807 13657 1573 8858 1214
2 -0.438 13.6 10369 14045 15982 1452 9112 1149
3 2002 1536 1378 1142
4 2022 1581 1284 1168
5 1605 1342 1160 1175
6 1889 1787 1226 1189
7 -0.027 11.4 2625 2674 3193 1819 2198 1326
8 0.030 11.2 2443 2392 2878 1759 2030 1250
9 0.244 12.0 4321 3648 4336 1608 3636 1179
10 0.136 12.1 4565 4153 4902 1657 3868 1169
11 0.118 13.2 9861 9086 10763 1765 8325 1264
12 0.131 13.0 8569 7825 9291 1648 7217 1199
13 0.401 11.5 3233 2449 2921 1524 2710 1150
14 0.370 11.4 3178 2460 2936 1443 2663 1086
15 1399 1488 1142 1098
16 1384 1451 1115 1111
17 1456 1351 1118 1063
18 1450 1450 1096 1086
19 -0.016 11.4 2651 2681 3203 1627 2219 1219
20 0.017 11.5 2947 2912 3459 1612 2481 1190

Total number of rows: 15552

Table truncated, full table size 616 Kbytes.




Supplementary file Size Download File type/resource
GSM518349.csv.gz 812.6 Kb (ftp)(http) CSV
Processed data included within Sample table

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