A table of time-aligned detected features containing the retention times, m/ z ratio, and intensities of each sample was then obtained.
Accurate mass and retention time methods aligned samples to generate quantitative peptide data, with predictive modeling using Bayesian sparse latent factor regression.
Acquisition times of both isotropic and aligned samples in t1 and t2 were 63.6 and 341 ms, respectively; the total experimental times were 62.5 and 45.5 h, respectively.
Based on the time delays identified with cross-correlation, we aligned the samples and calculated correlations of genes using the aligned samples.
Second, we align the time samples for the target gene based on the time delays (see Algorithm 2), and compute correlations between this gene and the other genes based on the aligned samples.
Figure 3 shows the distribution of vector angles for the most aligned and the least aligned samples in the dataset.
The correlation matrix also includes correlations between all the other genes using the time samples aligned based on the inferred time delays between these genes and the target genes (see Algorithms 1 and 2).
First, in each species sampling times for growth curves of biological replicates were shifted in order to align the exponential growth phase.
We present a novel approach to sampling the NMR time domain, whereby the sampling points are aligned on concentric rings, which we term concentric ring sampling (CRS).
We then replace each sample of the corrupted channel Y i 1 [ x ] with the time-warped sample Ŷ i 1 [ x ̂ ], which is obtained from the median of the samples with which it is aligned.
To correct retention time variation between runs, we applied an iterative block-shift alignment method [ 67] to produce precisely aligned data with minimal peak distortion (thus preserving quantitative information), resulting in 77 three-way arrays (m/z × time × samples).
