2 Statistical tests
| Type of analysis | Test abbreviation | Full Name | Null hypothesis | Principle | Usage recommendation |
|---|---|---|---|---|---|
| Pairwise or Time-course | ranksum | Rank sum test (Wilcoxon’s) | Two populations have the same distribution | Based on the sum of the positions in which the values of the two conditions fall. | Unpaired samples. Equal or unequal sized samples. Any number of variables. |
| Wcox | Wilcoxon’s signed rank | Differences across two matched populations are close to 0 | Based on the signs of the matched differences | Paired or related -non independent- samples (check your experimental design). Any number of variables. | |
| MW | Mann Whitney | Two populations have the same distribution | Based on the order in which the values from the two conditions fall | Independent samples; a.k.a “the non-parametric version of the t-test”. Assumes equal variances. Any number of variables. | |
| KW | Kruskal-Wallis | Two populations share the same medians | Based on the difference in the group-wise order totals | Unpaired, independent samples. Works better with n 5 Any number of variables. | |
| BrMu | Brunner-Munzel | Two populations share the same range of values | Difference in the averaged orders of the values, normalized by the variances. | Unpaired, independent samples, being n 10. Highly similar to the Mann-Whitney test, but does not require equal variances. Any number of variables. | |
| disfit | Fitting of a distribution to the z-scores | Data follows the specified distribution | Identify outliers using the best fit for the ratios of geometric means of values in 2 conditions | Unpaired and paired samples. Number of variables: use it if there are thousands or hundreds of isotopologues. Do not use it for fractional contributions or total metabolite abundances if you have few (<100) metabolites. | |
| prm-scipy | Permutations method via scipy | Two populations are drawn from the same underlying distribution | Differences between means of subsampled values from 2 conditions | Unpaired and paired samples. Any number of variables. | |
| Multi-group | KW | Kruskal-Wallis | Three or more populations share the same medians | Based on the difference in the group-wise order totals | Independent samples; a.k.a “the non-parametric alternative to the ANOVA test”. Works better with n 5 . Any number of variables. |
| Type of analysis | Full Name | Null hypothesis | Principle |
|---|---|---|---|
| MDV profile comparison between 2 conditions | Pearson or Spearman test | The MDV values of the two conditions are not correlated | Correlation of the MDV geometric means of the two conditions |
| MDV profile comparison between 2 consecutive time-points | Pearson or Spearman test | The MDV values of the two consecutive time-points are not correlated | Correlation of the MDV geometric means of two consecutive time-points |
| Metabolite total abundances and fractional contribution time-course profile comparison between 2 conditions | Pearson or Spearman test | The time-course values of metabolite total abundance or fractional contribution of the two conditions are not correlated | Correlation of the geometric means (computed across the time-course set of values) of the two conditions |
Note: the Spearman test (spearman) is the option set by default in the DIMet's bi-variate analysis.
