Data in A and B are normalized to DMSO controls (set to 100%).
A stringent quality control and inter-array normalization procedure resulted in a normalized data matrix of methylation values (β-values, 0 < β < 1) over 24,039 CpGs and 152 samples (Methods).
Non-normalized data in a form of the Cell Intensity File (*.CEL) were re-annotated (EntrezGene htmg430pm_Mm_ENTREZG) and the data were RMA normalized [ 26].
Non-normalized data in a form of the Cell Intensity File (*.CEL) were re-annotated (EntrezGene htmg430pm_Mm_ENTREZG) and the data were RMA normalized [ 20, 21].
Subroutine GDATA The subroutine provides all Input and output data in the normalized form.
We then uploaded the log2-normalized intensity data in a tab-delimited text format into the Multi Experiment Viewer (http://mev.tm4.org/ /welcome) and illustrated these data using heat maps (Additional file 2: Figure S2).
The permutation p-value for testing the null hypothesis (that no polymorphism exists at position s) is determined by: the background-corrected and quantile-normalized hybridization data in a matrix with 4) p s = { R s b > R s and R s b < 1 / R s : s = 1, 2, … m ; b = 1,2, … B B * m if R s > 1 R s b < R s and R s b > 1 / R s : s = 1, 2, … m ; b = 1,2, … B B * m if R s < 1 < 0.01.
The most common of these practices is the use of visible to short-wave infrared data, in particular the Normalized Difference Vegetation Index (NDVI).
Suppose that the pre-processed (normalized) transcriptome data in an experiment with n replicates is given by, with i = 1, ⋯, N, b = 1, ⋯, n b and a = 1, ⋯, n a where b and a label, respectively, biological and technical replicates, n b and n a are the number of biological and technical replicates, summing up to n b × n a transcriptomes for each experimental condition labeled by subscript k.
The downloaded data were GC-RMA normalized in the R statistical environment (http://R-project.org).org
