Sentence examples for normalised batch from inspiring English sources

Array data were processed using Illumina BeadStudio software, then it was normalised, batch corrected, 16 filtered and quality controlled as described (online supplementary text and figure S2).

Normalised and batch-corrected intensity-level data from Affymetrix and Illumina microarrays can be directly combined to generate biologically meaningful results with improved statistical power for robust, integrated reanalysis.

The sequence in which the data were quantile-normalised and batch-corrected appeared to produce only marginal differences in the resulting variance components; as a result, all remaining corrections using mean-centring and ComBat were performed after quantile normalisation for consistency and to comply with the statistical assumptions of the latter [ 16].

Each experiment was normalised independently to preclude batch effects which would obscure gene expression patterns [ 62].

The methylation scores from samples on all three chips were processed using standard quality control measures, and normalised (colour correction) and batch adjusted using COMBAT, resulting in beta methylation values according to the fluorescent intensity ratio that ranged from 0 (unmethylated) to 1 (completely methylated).

Illumina probe profile expression data were normalised using quantile normalisation and corrected for batch processing effects using mean-centring [ 12] and ComBat [ 21].

These datasets were independently filtered by detection calls, quantile-normalised, and, where stated, batch corrected by mean-centering or ComBat before generating lists of differentially expressed genes.

Correlation between replicate UHRR samples improved by two orders of magnitude following batch-correction using ComBat (ranging from 0.9833-0.9991 0.9833-0.9991999) and increased toe consistency of the gene-lists from the duplicate clinical samples, from 11.6% in quantile normalised data to 66.4% in batch-corrected data.

The batches were analysed and normalised separately to maintain the independence of the two datasets.

Batch effects across the three RPPA slides per marker were mitigated using ComBat [11] and data were normalised using variable slope normalisation [12].

In addition, a batch script features macroarray normalisation and generation of a series of log-transformed and normalised images of each spot over all the arrays analysed automatically.