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Normalized datasets were applied for further analysis of replication timing and efficiency.
Expression patterns of the genes were extracted from the normalized datasets and were expressed as mean levels of the log2 intensity (Table S2).
Differentially expressed genes are identified from the normalized datasets at the cut-off p-value < = 0.05 and fold change value > = 1.5 and < = −1.5.
Throughout this study, these normalized datasets were used for the computation of relative abundances of either taxonomic groups or the functional characterization.
Final normalized datasets were used to create 3 datasets used in the analyses: (i) centred enrichment data, (ii) log2 centred enrichment data, and (iii) log2 centred Z-scored enrichment data (log2 centred data were divided by the standard deviation of the entire dataset).
Normalized datasets were retrieved from the Cancer Genome Atlas (TCGA) data portal (http://tcga-data.nci.nih.gov/).
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The error e i n c o m p l,5(s ), as estimated by incomplete 5-fold CV, is computed by conducting the RMA normalization beforehand on the whole dataset and performing 5-fold CV on the normalized dataset.
Hierarchical agglomerative CA was performed on the normalized dataset using squared Euclidean distances as a measure of similarity.
In this study, hierarchical agglomerative CA was performed on the normalized dataset by means of the Ward's method, using squared Euclidean distances as a measure of similarity.
The entire normalized dataset extends over three orders of magnitude (0.1 to 0.001).
The normalized dataset was further filtered by removing transcripts with low intensity values and low across-sample variances; thus, 29892 transcripts were reduced to 26903.
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