Sentence examples for bias of the microarray from inspiring English sources

Linear and LOWESS normalization were conducted to eliminate possible dye-related bias of the microarray data.

We cannot completely rule out the presence of a length bias in the microarray data, for example due to decreased accessibility of long transcripts for the microarray surface, and we note that care must be taken to control for length bias in any method that measures expression.

Given that the whole human transcriptome was represented by the microarray analysis, this analysis was not biased toward the coverage of the microarray.

Given that the whole human transcriptome was represented in microarray performed, this analysis was not biased toward the coverage of the microarray.

To assess the removal of the microarray bias effect across the datasets, another merged dataset without batch effect removal was also compiled.

This approach, while surely providing an information easily understandable to biologists who are used to think on a gene-by-gene based, can be severely biased by the high dimensionality of the microarray experiments provoking a lot of chance correlations [12].

In addition, QPCR of amplified RNA is biased towards recapitulating the results of the microarray experiment due to truncation of the RNA products.

Tissue sample bias for running the microarray may be one of the possible reasons.

Another potential bias lies in the probe composition of the microarray.

It was investigated whether there was any systematic technical bias of the real-time PCR-to-microarray correlation.

As can be seen in Figure 5, spatial biases that cover more than 15% of the microarray surface and that correspond to ratio measurements that deviate from the mean of the rest of the microarray by at least two-fold are responsible for generating autocorrelation patterns similar to those observed in ~60% of real experiments.