To this end, we intend to transform the p-Laplace equation into a functional minimum problem (see Section 2 in [12]) solved by Newton iterations.
To determine significance levels, the RP method uses a permutation-based estimation procedure to transform the p-value into an e-value that addresses the multiple testing problem derived from testing many genes simultaneously.
Firstly, we corrected the p-values for multiple testing (see Methods) then our first attempt was to transform the p-values into a measure whose magnitude would express the degree of significance, and to that purpose, we transformed p-values into Pathway Enrichment Factors (PEFs).
The correction above is then used to transform the p-value of 0.01 to approximately a p_full of 0.1.
Thus, the correction above would transform the p-value of 0.01 to approximately a p_ full of 0.1.
We transformed the P values obtained for every donor lineage to generate heatmap charts.
We transformed the P values obtained for every pathway to generate heatmap charts.
We transformed the P values obtained for every pathway to generate heatmap charts based on these transformed values.
This is attained by transforming the p initial variables X = [ x 1, x 2,…, x p ] to a latest set of q predictor variables.
This is achieved by transforming the p original variables X = [ x 1, x 2,..., x p ] to a new set of q predictor variables, T = [ t 1, t 2,..., t q ], which are linear combinations of the original variables.
LOC_Os10g12080, which is also named CYP98A15p (Liu et al. 2010), was down-regulated exclusively in Loto and encodes coumarate 3-hydroxylase (C3H), which transforms the P-coumaric acid into caffeic acid at the beginning of the lignin branch.
