Sentence examples for between samples were assessed from inspiring English sources
Differences between samples were assessed using one-way ANOVA statistical test.
Differences between samples were assessed by the Student's two-tailed t test for independent samples.
Relationships between samples were assessed using Principal Coordinate Analysis (PCoA) based on a pairwise genetic distance matrix (number of base differences per sequence) between samples, and using the UPGMA method based on the number of substitutions per site from averaging over all sequence pairs between groups using the Tamura-Nei model [ 34].
A pairwise community similarity between samples was assessed based on the absence and presence of each OTU using a Jaccard index (Additional file 1: Table S1).
Reliability between samples was assessed with intraclass correlation: r = 0.83 in 1991 1993 and r = 0.57 in 2003 2004.
Data were quantile normalised and transformed to log base 2. Differential expression between samples was assessed using the 'limma' package (Smyth, 2005).
Reliability between samples was assessed with Pearson's correlation coefficients: r = 0.63; intra- and inter-assay coefficients of variation were 7.5% and 8.9%, respectively.
The significance of differences in AR, H and V between samples was assessed with the nonparametric Friedman and Wilcoxon sign rank tests (with locus as a repetition unit).
Bacterial diversity both within and between samples was assessed through alpha using Chao1 measure [ 56] and beta diversity using weighted and unweighted UniFrac distances [ 57].
The statistical significance of signal changes between samples was assessed by either pair-wise or multiclass tests from the Significance Analysis of Microarrays (SAM) software package [ 58], as appropriate, using all three biological replicates for each condition.
The log ratios between two samples were assessed from the respective spot signals, normalized by local weighted scatter plot smooth (LOWESS) based on print-tip.
