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For the organ specific analysis, expression data from LD were background corrected with the "rma" method and normalized with the "quantiles" method using the R affy library [25].
The 450.idat files were preprocessed and background corrected with the preprocessIllumina function in minfi to obtain β values.
The raw intensity data was normalized with quantiles, background corrected with the gcrma algorithm and summarized using median polish.
The raw intensity data was background corrected with the robust multi-array average (RMA) algorithm [ 59], normalized with quantiles, and summarized using median polish.
Gene expression levels are measured as probe-target hybridisation intensities, and all values are background corrected, with the inter-array quantile normalised to remove systematic biases, providing relative rather than absolute gene expression levels [ 9].
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Median intensities were background corrected with Normexp method fixing the offset parameter κ = 50 [ 28]. Background corrected data was normalized using a within print-tip loess-location normalization [ 29].
Arrays were processed and background corrected with default settings for all parameters with the Agilent Feature Extraction software (v.9.5.3.1).
The data obtained from CEL files was background corrected with RMA, quantile normalized before an ANOVA was used to determine the Fold Change difference in log-transformed intensities between Tumor and Normal samples.
Affymetrix Human JAY arrays were normalized using the probe scaling method and background corrected with ProbeEffect from GeneBase (Kapur et al., 2008).
Both reporter gene assays were background corrected with values obtained from lysis buffer alone.
Control probes were filtered, and then expression values were normexp background corrected with offset 16 [ 20], and then log-ratios were global loess normalized [ 22].
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