Following background subtraction based on POS_A probe correction factors, normalization is performed in two steps: Positive Control normalization and codeset normalization. During both steps the geometric mean of each probeset is used to create a normalization factor. More information on normalization can be found on page 43 of the nSolver 4.0 Analysis Software User Manual.
ROSALIND calculates fold changes and p-values for comparisons defined during experiment setup using the t-test method. P-value adjustment is performed using the Benjamini-Hochberg method of estimating false discovery rates (FDR). More information on calculating fold change ratios for miRNA can be found on page 47 of the nSolver 4.0 Analysis Software User Manual.
ROSALIND analyzes the top targeted gene predictions, validated genes, and related drugs and diseases using the multiMiR R library. multiMir referenced multiple database like miRecords, MIRTarbase, miRDB, TargetScan, and miRanda to report enrichment scores.