|
Status |
Public on Dec 22, 2010 |
Title |
S288c_Glucose_rep2 |
Sample type |
RNA |
|
|
Source name |
Saccharomyces cerevisiae grown on glucose medium
|
Organism |
Saccharomyces cerevisiae |
Characteristics |
strain: S288c culture condition: grown on glucose medium
|
Extracted molecule |
total RNA |
Extraction protocol |
Total RNA was extracted using the FastRNA Pro RED kit (QBiogene, Carlsbad, USA) according to manufacturer’s instructions.
|
Label |
Biotin
|
Label protocol |
Labeling was performed according to the manufacturer’s recommendations (Affymetrix GeneChip® Expression Analysis Technical Manual, 2005-2006 Rev. 2.0).
|
|
|
Hybridization protocol |
Array hybridization to Affymetrix Yeast Genome Y2.0 arrays were performed according to the manufacturer’s recommendations (Affymetrix GeneChip® Expression Analysis Technical Manual, 2005-2006 Rev. 2.0).
|
Scan protocol |
Washing and staining of arrays were performed using the GeneChip Fluidics Station 450 and scanning with the Affymetrix GeneArray Scanner (Affymetrix, Santa Clara, CA).
|
Data processing |
Affymetrix Microarray Suite v5.0 was used to generate CEL files of the scanned DNA microarrays. These CEL files were then processed using the statistical language and environment R v5.3 (R Development Core Team, 2007, www.r-project.org), supplemented with Bioconductor v2.3 (Biconductor Development Core Team, 2008, www.bioconductor.org) packages Biobase, affy, gcrma, and limma (Smyth, 2005). The probe intensities were normalized for background using the robust multiarray average (RMA) method only using perfect match (PM) probes after the raw image file of the DNA microarray was visually inspected for acceptable quality. Normalization was performed using the qspline method and gene expression values were calculated from PM probes with the median polish summary. Statistical analysis was applied to determine differentially expressed genes using the limma statistical package. Moderated t-tests between the sets of experiments were used for pair-wise comparisons. Empirical Bayesian statistics were used to moderate the standard errors within each gene and Benjamini-Hochberg’s method was used to adjust for multi-testing. A cut-off value of adjusted p<0.01 was used for statistical significance (Smyth, 2000).
|
|
|
Submission date |
Apr 22, 2010 |
Last update date |
Dec 22, 2010 |
Contact name |
wanwipa vongsangnak |
E-mail(s) |
[email protected]
|
Phone |
+46 7723847
|
Organization name |
Chalmers University of Technology
|
Department |
Department of Chemical and Biological Engineering
|
Lab |
Systems Biology
|
Street address |
Kemivägen 10
|
City |
Gothenburg |
ZIP/Postal code |
SE-412 96 |
Country |
Sweden |
|
|
Platform ID |
GPL2529 |
Series (1) |
GSE21479 |
Whole genome sequencing of Saccharomyces cerevisiae: from genotype to phenotype for improved metabolic engineering applications |
|