A data frame or matrix, with m rows corresponding to variables (hypotheses) and n columns to observations. In the case of gene expression data, rows correspond to genes and columns to mRNA samples. The data can be read using read.table.

A vector of integers corresponding to observation (column) class labels. For k classes, the labels must be integers between 0 and k-1. For the blockf test option, observations may be divided into n/k blocks of k observations each. The observations are ordered by block, and within each block, they are labeled using the integers 0 to k-1.

A character string specifying the statistic to be used to test the null hypothesis of no association between the variables and the class labels.
If test="t", the tests are based on two-sample Welch t-statistics (unequal variances).
If test="t.equalvar", the tests are based on two-sample t-statistics with equal variance for the two samples. The square of the t-statistic is equal to an F-statistic for k=2.
If test="wilcoxon", the tests are based on standardized rank sum Wilcoxon statistics.
If test="f", the tests are based on F-statistics.
If test="pairt", the tests are based on paired t-statistics. The square of the paired t-statistic is equal to a block F-statistic for k=2.
If test="blockf", the tests are based on F-statistics which adjust for block differences (cf. two-way analysis of variance).

A character string specifying the type of rejection region.
If side="abs", two-tailed tests, the null hypothesis is rejected for large absolute values of the test statistic.
If side="upper", one-tailed tests, the null hypothesis is rejected for large values of the test statistic.
If side="lower", one-tailed tests, the null hypothesis is rejected for small values of the test statistic.

If fixed.seed.sampling="y", a fixed seed sampling procedure is used, which may double the computing time, but will not use extra memory to store the permutations. If fixed.seed.sampling="n", permutations will be stored in memory. For the blockf test, the option n was not implemented as it requires too much memory.

The number of permutations. For a complete enumeration, B should be 0 (zero) or any number not less than the total number of permutations.

Code for missing values (the default is .mt.naNUM=--93074815.62). Entries with missing values will be ignored in the computation, i.e., test statistics will be based on a smaller sample size. This feature has not yet fully implemented.

If nonpara="y", nonparametric test statistics are computed based on ranked data.
If nonpara="n", the original data are used.

Vector of row indices, between 1 and nrow(X), where rows are sorted first according to their adjusted p-values, next their unadjusted p-values, and finally their test statistics.

Vector of test statistics, ordered according to index. To get the test statistics in the original data order, use teststat[order(index)].

Vector of raw (unadjusted) p-values, ordered according to index.

Vector of adjusted p-values, ordered according to index.

For mt.minP function only, vector of "adjusted p-values", where ties in the permutation distribution of the successive minima of raw p-values with the observed p-values are counted only once. Note that procedures based on plower do not control the FWER. Comparison of plower and adjp gives an idea of the discreteness of the permutation distribution. Values in plower are ordered according to index.