Sentence examples for multiple microarray batches from inspiring English sources

CD4 and CD14 RNA samples were run on multiple microarray batches, leaving microarray datasets potentially confounded by technical artefacts.

Integrative analysis uses an integrated data of multiple microarray datasets via adjusting batch effects, or systematic difference between datasets, which is promising approach to identify robust molecular basis associated to multiple brain diseases.

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.

Of course, the issue of batch effects when combining data from multiple microarray experiments conducted in different laboratories must be considered carefully.

Because there are multiple microarray elements matched for some genes, the heatmap and line plot are displayed according to microarray element IDs.

Y8_1 is a YD sample, 8hpf, batch 1. Microarray batches have been denoted with A-C instead of 1 3, in order to distinguish RNAseq samples from microarray samples.

Between-batch normalization was performed using Distance Weighted Discrimination (DWD) approach [ 19] using 4 samples replicated in the 2 microarray batches.

Using individual generalised linear models adjusting for microarray batch, age and stage and adjusting for multiple comparisons using FDR, two probes; MTDH (probe ID '212250_at') and IGF1R (probe ID '208441_at') were found to be significantly differentially expressed (P<0.05, FDR <5%) associated with optimal (⩽1 cm residual disease) or suboptimal (>1 cm residual disease) surgery.

For PREDICT microarrays all matched pairs were labeled and hybridized together to minimize microarray batch effects.

Microarray batch effects visible from MDS plots were addressed by adjusting for the microarray lot number as a covariate.

The microarrays batch was validated if all controlled micromembranes of this batch were validated.