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qiime longitudinal first-distances (version 2019.4)
--m-metadata-file [required]s
--m-metadata-file [required] 0

Compute first distances or distance from baseline between sequential states

Calculates first distances between sequential states for samples collected from individual subjects sampled repeatedly at two or more states. This method is similar to the "first differences" method, except that it requires a distance matrix as input and calculates first differences as distances between successive states. Outputs a data series of first distances for each individual subject at each sequential pair of states, labeled by the SampleID of the second state (e.g., paired distances between time 0 and time 1 would be labeled by the SampleIDs at time 1). This file can be used as input to linear mixed effects models or other longitudinal or diversity methods to compare changes in first distances across time or among groups of subjects. Also supports distance from baseline (or other static comparison state) by setting the "baseline" parameter.

Parameters

distance_matrix : DistanceMatrix
Matrix of distances between pairs of samples.
metadata : Metadata
Sample metadata file containing individual_id_column.
state_column : Str
Metadata column containing state (time) variable information.
individual_id_column : Str
Metadata column containing IDs for individual subjects.
baseline : Float, optional
A value listed in the state_column metadata column against which all other states should be compared. Toggles calculation of static distances instead of first distances (which are calculated if no value is given for baseline). If a "baseline" value is provided, sample distances at each state are compared against the baseline state, instead of the previous state. Must be a value listed in the state_column.
replicate_handling : Str % Choices('error', 'random', 'drop'), optional
Choose how replicate samples are handled. If replicates are detected, "error" causes method to fail; "drop" will discard all replicated samples; "random" chooses one representative at random from among replicates.

Returns

first_distances : SampleData[FirstDifferences]
Series of first distances.