Sentence examples for microarray platforms combined from inspiring English sources

Median expression data for 207 GBM samples from two different microarray platforms combined was downloaded from the TCGA data portal.

Despite using similar starting material (primary tumours) and the same microarray platform, when combined the two datasets formed two distinct, independent clusters representing the two datasets (Fig. 2A), suggesting a dataset-specific systematic bias as observed with the validation datasets described above.

Data from GSE24335 and GSE9588 were produced with the same microarray platform and were combined using ComBat (Johnson et al., 2007) to control for potential batch effects.

This approach poses three problems: errors and irrelevancies, multiple IDs for a single gene, and combining multiple microarray platforms.

The idea is to build a scale that can be combined across different microarray platforms, and therefore allows simultaneous examination of independent data sets.

Files were generated from this master file containing either the 189 phosphatase genes available on the microarray platforms or the 189 phosphatase genes combined with the 693 known kinase genes allowing a comparison to the whole genome.

Second, a challenge of this study was the implementation of many published predictors onto a common dataset, many of which used unique statistical methods; we strove to implement each predictor as published, however, almost all predictors "lost" genes due to combining data across microarray platforms, and thus, almost all predictors differed somewhat from their original specification.

The conversion can then be detected using a variety of methods combined with sequencing and/or microarray platforms.

Excluding the three most polymorphic gene families, var, rif and stevor (which are insufficiently represented in microarray platforms to allow for meta-analyses), these clusters combine the vast majority of the previously predicted 'exportome' in P. falciparum [ 37].

To combine these datasets obtained from different microarray platforms, we performed the following pre-processing methods.

While it is not the first application which combines multiple public breast cancer datasets and performs a cross-dataset survival analysis [ 37- 39], it is the first application which allows users to combine multiple prognostic markers across multiple microarray platforms without requiring complex adjustments for batch effects across different experiments/platforms.