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Quantitative-Percentage

Description

The “quantitative-percentage” module takes phenotype/bioactivity data where samples have a measured percentage of bioactivity/phenotype at a specified concentration. Multiple measurements can be specified for each sample, and multiple assays (each with a determined concentration) can be provided. The algorithm works as follows:

  • All percentage values lower than zero are set to zero.
  • Duplicate measurements per sample are summarized with a user-specified algorithm (mean or median).
  • For each feature occurring in more than two active samples, the area per sample and the percentage measurement per sample are extracted and z-transformed.
  • The transformed areas and percentages are correlated using the Pearson correlation.
  • The resulting p-value is corrected for multiple hypothesis testing using the Bonferroni-method (p-value * number of tested features)
  • If both correlation coefficient and p-value meet a user-specified cutoff, the phenotype information is assigned and the tested feature is considered bioactivity-associated

Parameters

  • sample_avg: specifies the algorithm to summarize multiple measurements per sample for same assay. Possible algorithms are mean and median.
  • value: specifies value per feature to be correlated with percentage. Only area is currently allowed.
  • algorithm: specifies the statistical algorithm to use. Only pearson is currently allowed.
  • p_val_cutoff: Maximum Bonferroni-corrected p-value to consider, with zero disabling cutoff filtering for both p-value and coefficient.
  • coeff_cutoff: Minimum correlation coefficient to consider, with zero disabling cutoff filtering for both p-value and coefficient.

Limitations

  • This method assumes that the prerequisites with regard to sample reproducibility are met (see Input/Output).
  • This method assumes a positive linear correlation between phenotype (percentage) and concentration (area of feature).
  • This method does not take into account any synergistic or quenching effects