Exact(3)
The dataset was normalized using the RMA algorithm [ 25].
The number of reads per protein coding mRNA was determined using Partek Genomics Suite (Partek Inc., St . Louis MO, USA) and the dataset was normalized using the trimmed mean of the M-values method [ 19].
The expression family was set to negative binomial, and the dataset was normalized using estimateSizeFactors followed by estimateDispersions.
Similar(57)
Before the actual learning, the training dataset was normalized using the min max method.
The entire dataset was normalized using gcRMA procedures and the linear model was fitted and contrasts were restricted to within treatment conditions.
To ensure all SNPs across all datasets were typed according to the same DNA strand, each dataset was normalized using HapMap phase 2 data as the reference set.
Each dataset was normalized using the trimmed mean of M-values normalization method proposed by Robinson & Oshlack [ 23], to remove systematic technical effects and minimize the sequencing technical bias on the data.
For the 36 cancer datasets generated from Affymetrix microarray platforms, the log2 intensities in each gene expression dataset were normalized using the GC-RMA normalization method (15).
In each test, the raw datasets were normalized using the Affymetrix detection algorithms in the MAS5 library and the background levels and PM/MM ratios were corrected according to the Affymetrix Statistical Algorithms.
The human and mouse datasets were normalized using the Robust Multichip Average (RMA) algorithm.
Both control and leukemia expression datasets are normalized using quantile normalization (Amaratunga and Cabrera, 2001).
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