When data from two platforms are compared, the two platform-specific systematic errors are combined with the random error, hence the superior platform which minimises its own systematic errors should have higher agreement with the other platforms.
Second, can predictive signature genes selected from one platform be used to directly train a model on another platform?
In addition, we introduce a novel approach to compare two platforms based on the calculation of differences between expression ratios observed in each platform for each individual transcript.
The results indicate that the proposed approach effectively integrates images from the two platforms and thereby improves 3D modeling in urban areas.
A first approach to integratively investigate data from any two platforms is the 'data-pairing' procedure.
Using Affymetrix and Illumina data from the microarray quality control project, from our own clinical samples, and from additional publicly available datasets we evaluated several approaches to directly integrate intensity level expression data from the two platforms.
Using a new approach to map probes across platforms, we found that the genes in the signatures from the two platforms were highly similar, and that the predictions they generated were also strongly correlated.
Data from the two platforms were treated separately.
Results from these two platforms were the most concordant, and, if the recommended intensity-based filtering is applied, that the Operon platform agrees most with the Affymetrix platform, suggesting that Affymetrix may be platform generating the most reproducible data.
Using a pooled DNA approach on 1,082 LOAD patients and 1,239 controls, the fourth GWAS tested more than 500,000 SNPs from two Illumina platforms [ 54].
Discrepant calls between the two platforms may derive from differences in the GeneChip and CodeLink platform technologies.
