As one of the data processing steps recommended in [ 13], logarithmic transformation are applied on microarray datasets: base 10 log for data derived from oligonucleotide (Affymetrix) platform and base 2 log for data derived from cDNA (two-color) platform.
A detailed microarray dataset analysis, based on clustering of similarly expressed genes (GEDI software), can detect underlying global-scale responses, which cannot be detected by means of individual gene expression techniques using raw or corrected p values (FDR).
Various microarray gene expression datasets based studies have generated gene signatures to predict the prognosis outcomes, while ignoring the large amount of information contained in established clinical markers.
Celsius, the largest co-normalized microarray dataset of Affymetrix based gene expression, was used to calculate the correlation between all possible gene pairs on all platforms, and generate stored indexes in a web searchable format.
Only those TFs identified also for the whole microarray dataset are listed (based on chip-Chip analysis), without consideration of statistical significance.
Relative expression values of PDGF family members were combined with a cDNA microarray dataset and analyzed based on clinical findings and PDGF expression patterns.
Large-scale integrated microarray datasets typically combine strongly diverging datasets based on different experimental conditions, independent cohorts of samples, varying sample preparation methods and labelling methods or scanner settings, and even different microarrays or microarray platforms.
Similarly we analysed the microarray dataset using probe annotations based on v1.0 and v2.0 of the genome and assembly with similar gene-level results in both cases.
Briefly, microarray datasets were grouped based on the cell line.
Using three datasets based on physical interaction assays, genome-wide RNA interference (RNAi) screens and microarray assays, we identified 714 putative DENV-associated mosquito proteins.
