Longitudinal Analysis¶

The q2-longitudinal plugin provides tools to track how microbial communities change over time within individuals or groups. Here we use accumulated degree days (ADD) as the temporal axis.

PCoA-Based Volatility¶

Track the position of samples along a PCoA axis over time:

qiime longitudinal volatility \
  --m-metadata-file metadata_q2_workshop.txt \
  --m-metadata-file core_metrics/weighted_unifrac_pcoa_results.qza \
  --p-state-column add_0c \
  --p-individual-id-column host_subject_id \
  --p-default-group-column 'sample_type' \
  --p-default-metric 'Axis 2' \
  --o-visualization pc_vol_sample_type.qzv

Interpreting Volatility Plots

The volatility plot shows how each individual's community composition (summarized by a single PCoA axis) changes over time. Trajectories that converge or diverge between groups suggest temporal differences in community dynamics.

First Distances¶

Calculate Change from Baseline

Calculate the distance of each sample from its own baseline (ADD = 0) using weighted UniFrac:

qiime longitudinal first-distances \
  --i-distance-matrix core_metrics/weighted_unifrac_distance_matrix.qza \
  --m-metadata-file metadata_q2_workshop.txt \
  --p-state-column add_0c \
  --p-individual-id-column host_subject_id_sample_type \
  --p-baseline 0 \
  --o-first-distances from_first_wunifrac.qza

Visualize Distance from Baseline¶

qiime longitudinal volatility \
  --m-metadata-file metadata_q2_workshop.txt \
  --m-metadata-file from_first_wunifrac.qza \
  --p-state-column add_0c \
  --p-individual-id-column host_subject_id \
  --p-default-metric Distance \
  --p-default-group-column 'sample_type' \
  --o-visualization from_first_wunifrac_vol.qzv

Linear Mixed Effects Model¶

Beta Diversity

Test whether the distance from baseline changes significantly over time, accounting for facility and sample type:

qiime longitudinal linear-mixed-effects \
  --m-metadata-file metadata_q2_workshop.txt \
  --m-metadata-file from_first_wunifrac.qza \
  --p-state-column add_0c \
  --p-individual-id-column host_subject_id \
  --p-formula "Distance ~ add_0c + facility + sample_type" \
  --o-visualization from_first_wunifrac_lme_formula.qzv

Alpha Diversity Volatility¶

Track Shannon entropy over time:

qiime longitudinal volatility \
  --m-metadata-file metadata_q2_workshop.txt \
  --m-metadata-file core_metrics/shannon_vector.qza \
  --p-default-metric shannon_entropy \
  --p-default-group-column sample_type \
  --p-state-column add_0c \
  --p-individual-id-column host_subject_id \
  --o-visualization sample_type_shannon_volatility.qzv

Linear Mixed Effects Model¶

Alpha Diversity

Test whether Shannon entropy changes significantly over time:

qiime longitudinal linear-mixed-effects \
  --m-metadata-file metadata_q2_workshop.txt \
  --m-metadata-file core_metrics/shannon_vector.qza \
  --p-state-column add_0c \
  --p-individual-id-column host_subject_id \
  --p-formula "shannon_entropy ~ add_0c + facility + sample_type" \
  --o-visualization shannon_lme_formula.qzv

Outputs¶

File	Type	Description
`pc_vol_sample_type.qzv`	Visualization	PCoA-based volatility by sample type
`from_first_wunifrac.qza`	Artifact	Distance from baseline per sample
`from_first_wunifrac_vol.qzv`	Visualization	Volatility of distance from baseline
`from_first_wunifrac_lme_formula.qzv`	Visualization	LME model for beta diversity change
`sample_type_shannon_volatility.qzv`	Visualization	Shannon entropy volatility
`shannon_lme_formula.qzv`	Visualization	LME model for Shannon entropy change

Next: Getting Data Into R