This issue highlights the importance of data normalisation: currently data are normalised to the maximum cytokine value among all treatments.
There are three different types of data normalisation according to the requirement of LB, HB, or NB criteria.
However, proper and highly reliable reference genes are needed for normalisation of data, as normalisation by total pathogen RNA in mixed host-pathogen samples is usually not possible.
Included within the TRF is a reference baseline analysis (RBA) that encompasses raw data selection; data normalisation; recognition of outliers; and statistical analysis.
With regard to papers presenting biomedical-relevant applications, 41(29.1 %) of these papers did not report on data normalisation and 83 (58.9%) did not describe the normalisation technique applied.
The accuracy of quantitative RT-PCR experiments is dependent on proper data normalisation.
The averaged expression of B2M and GAPDH was used as an endogenous control for data normalisation.
The data normalisation will be analysed through a visual inspection of the histograms.
Data normalisation was performed across all arrays using quantile normalisation.
DH is responsible for data normalisation.
