Input:

Two counts (integers, ≥0) of the same item/event occurring in two independent sampling experiments.

Computation:

The ACD cumulative probability of observing these two counts as different as they are, if their relative frequencies are the same in the two samples (null hypothesis).

Output:

The probability value (and its logarithm) of such fluctuation. Usable as a conservative estimate of statistical significance (provided an eventually needed correction for multiple testing is applied).

Input:

1) One table of N x M counts (integers, ≥0) where N (lines) contain the numbers of occurrence of N independent rare events as drawn from M sampling experiments.

2) Two identifiers indicating which pairwise sample comparison to make.

Computation:

The ACD cumulative probability of observing each pair of cognate counts as different as they are, if their relative frequencies are the same in the two samples (null hypothesis).

Output:

Ranked by increasing values (decreasing significance), the pairwise probabilities values of the fluctuations observed for each event, the corresponding distance (-ln(p)), and the count-wise normalized distance.

Input:

One table of N x M counts (integers, ≥0) where N (lines) contain the numbers of occurrence of N independent rare events as drawn from M sampling experiments.

Computation:

A MxM table of normalized pairwise distances between all samples.

Output:

1) An interactive heatmap of the pairwise distances between samples.

2) A file containing the MxM distance table (for clustering, phylogeny, other graphics).

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