Sentence examples for methods for data normalization from inspiring English sources

Our methods for data normalization and analysis are based on the use of "internal standards" [17] that characterize some aspects of the system's behavior, such as technical variability, as presented elsewhere [18], [19].

For example, we are exploring alternative methods for data normalization.

We applied two independent methods for data normalization and used PAM for feature selection.

These unique features contained in RNA-Seq data have motivated the development of a number of statistical methods for data normalization and differential expression (DE) detection.

The developing field of lipidomics still lacks standardized methods for data normalization, analysis, and visualization, as well as for lipid annotation (Snijder et al., 2014).

After estimating gene expression from the sequencing reads, two methods for data normalization were assessed: Exploratory Data Analysis and Normalization for RNA-Seq (EDASeq) [ 16] and Conditional Quantile Normalization (CQN) [ 17].

We used a statistically based quantile normalization method for data normalization [14].

The BioMark HD™ system is most cost effective and provides a straightforward and simple method for data normalization.

We used the GLM method in edgeR for data normalization and differential expression analysis.

Moreover, several methods have been proposed for data normalization [15] and summarization of protein ratios, including averaging [13] or intensity-weighted averaging [16] of ratios for peptides identifying the same protein.

For example, the R package edgeR [ 17] uses the TMM method [ 16] for data normalization and an exact test for negative binomial (NB) distribution [ 22] for gene ranking.