Transcriptional output can be estimated by comparing GFP amplification signal from cDNA between different samples after normalizing for construct incorporation and for the amount of RNA utilized (using the signal from the amplification of Spz12 as described in [7], [14]).
In both cases, we used the distance one minus the squared correlation (1-r) between the samples, after normalizing the raw data with the RMA procedure [ 18], as detailed in Material and Methods.
However, they reported similar levels of compliance with the collection protocol (i.e., in terms of the intervals between respective samples) after waking.
The Mann–Whitney test was used to compare differences in plasma miRNA levels between the cancer and healthy groups, and the Wilcoxon's test was used to compare plasma levels between the paired samples before and 1 month after oesophagectomy or between the samples after oesophagectomy and at recurrences.
Traditionally, biomarkers are screened between samples after cancer manifestation, often at relatively late stages in the cancer development after symptoms have occurred.
Additionally, multi-dimensional scaling (MDS) was performed on the Euclidean distance matrix between samples after differential gene expression statistical analysis [ 42].
The majority of pairwise comparisons (393 of 406) showed significant differences in allele frequencies between samples after correction for multiple testing.
We investigated the CV between samples after data transformation: the lowest CVs decreased to 16.5% in the colon dataset while it increased to 25.8% for the prostate dataset (Table 3 and Table 4).
They observed that the use of TS strategies does not improve the fidelity of RNA amplification versus the Eberwine method, that there is good correlation between samples after amplification, that the overall bias introduced by T7-based amplification strategies is uniformly low, and that the results are reproducible.
