Docstring:
Usage: qiime longitudinal first-distances [OPTIONS]
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.
Inputs:
--i-distance-matrix ARTIFACT
DistanceMatrix Matrix of distances between pairs of samples.
[required]
Parameters:
--m-metadata-file METADATA...
(multiple Sample metadata file containing
arguments will be individual-id-column.
merged) [required]
--p-state-column TEXT Metadata column containing state (time) variable
information. [required]
--p-individual-id-column TEXT
Metadata column containing IDs for individual
subjects. [required]
--p-baseline NUMBER 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.
[optional]
--p-replicate-handling TEXT Choices('error', 'random', 'drop')
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. [default: 'error']
Outputs:
--o-first-distances ARTIFACT SampleData[FirstDifferences]
Series of first distances. [required]
Miscellaneous:
--output-dir PATH Output unspecified results to a directory
--verbose / --quiet Display verbose output to stdout and/or stderr
during execution of this action. Or silence output if
execution is successful (silence is golden).
--example-data PATH Write example data and exit.
--citations Show citations and exit.
--use-cache DIRECTORY Specify the cache to be used for the intermediate
work of this action. If not provided, the default
cache under $TMP/qiime2/ will be used.
IMPORTANT FOR HPC USERS: If you are on an HPC system
and are using parallel execution it is important to
set this to a location that is globally accessible to
all nodes in the cluster.
--help Show this message and exit.
Import:
from qiime2.plugins.longitudinal.methods import first_distances
Docstring:
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.
