Sentence examples for samples using linear from inspiring English sources

The expression levels of these three transcripts were compared between the microarray and qPCR data for the 22 (pre and post-surgery) samples using linear regression analysis; and, each transcript had a very strong positive correlation (R values ranged from 0.75 to 0.88).

These comparisons of the subscale scores between psychiatrists and community members were then repeated after adjusting for differences in gender, age and years of education between the two samples using linear regression methods.

Package limma [ 50] was used for importing microarray data from GenePix files, for data pre-processing (background correction and normalization) and to search for differentially expressed genes between infected and healthy grapevine samples using linear models (common reference design).

Drug response phenotypes (IC50 values) for both drugs were adjusted for ethnicity, gender and storage time of the 197 samples using linear regression (natural log transformation applied to IC50 values).

Figure 7 shows the computation time relative to rotating the texture sample using linear interpolation.

Each SNP was tested for association with the average DNA methylation level across all CpGs measured in the CEPH sample, using linear mixed effects models in R [ 47].

18 Briefly, 25(OH D was modelled against the date of blood sampling using linear regression with trigonometric sine and cosine functions, and residuals of regression models were used as season-adjusted 25(OH D in main analyses.

Prior to angiography processing, the raw data was processed with the customary OCT processing chain [ 29], which includes background subtraction, λ- to k-space re-sampling (using linear or spline interpolation), fast Fourier transformation, and logarithmic scaling.

The impact of increasing proportions of adjacent normal tissue was assessed for each sample using linear combinations of tumor gene expression and paired normal gene expression according to the following: (1) where a is the percentage of tumor signal and 1- a is the percentage of normal signal.

It is due to its capability on classifying the samples by using linear and nonlinear separators.

We present a comprehensive theoretical analysis of the discrete polar Fourier transform, and derive the consequences of its application to radially sampled data using linear response theory.