Available plugins¶
QIIME 2 microbiome analysis functionality is made available to users via plugins. The following official plugins are currently included in QIIME 2 train releases:
- alignment: Plugin for generating and manipulating alignments.
- composition: Plugin for compositional data analysis.
- cutadapt: Plugin for removing adapter sequences, primers, and other unwanted sequence from sequence data.
- Methods
- demux-paired: Demultiplex paired-end sequence data with barcodes in-sequence.
- demux-single: Demultiplex single-end sequence data with barcodes in-sequence.
- trim-paired: Find and remove adapters in demultiplexed paired-end sequences.
- trim-single: Find and remove adapters in demultiplexed single-end sequences.
- Methods
- dada2: Plugin for sequence quality control with DADA2.
- deblur: Plugin for sequence quality control with Deblur.
- demux: Plugin for demultiplexing & viewing sequence quality.
- Methods
- emp-paired: Demultiplex paired-end sequence data generated with the EMP protocol.
- emp-single: Demultiplex sequence data generated with the EMP protocol.
- filter-samples: Filter samples out of demultiplexed data.
- partition-samples-paired: Split demultiplexed sequence data into partitions.
- partition-samples-single: Split demultiplexed sequence data into partitions.
- subsample-paired: Subsample paired-end sequences without replacement.
- subsample-single: Subsample single-end sequences without replacement.
- tabulate-read-counts: Tabulate counts per sample
- Visualizers
- Methods
- diversity: Plugin for exploring community diversity.
- Pipelines
- alpha: Alpha diversity
- alpha-phylogenetic: Alpha diversity (phylogenetic)
- beta: Beta diversity
- beta-correlation: Beta diversity correlation
- beta-phylogenetic: Beta diversity (phylogenetic)
- core-metrics: Core diversity metrics (non-phylogenetic)
- core-metrics-phylogenetic: Core diversity metrics (phylogenetic and non-phylogenetic)
- Methods
- filter-alpha-diversity: Filter samples from an alpha diversity metric.
- filter-distance-matrix: Filter samples from a distance matrix.
- partial-procrustes: Partial Procrustes
- pcoa: Principal Coordinate Analysis
- pcoa-biplot: Principal Coordinate Analysis Biplot
- procrustes-analysis: Procrustes Analysis
- tsne: t-distributed stochastic neighbor embedding
- umap: Uniform Manifold Approximation and Projection
- Visualizers
- adonis: adonis PERMANOVA test for beta group significance
- alpha-correlation: Alpha diversity correlation
- alpha-group-significance: Alpha diversity comparisons
- alpha-rarefaction: Alpha rarefaction curves
- beta-group-significance: Beta diversity group significance
- beta-rarefaction: Beta diversity rarefaction
- bioenv: bioenv
- mantel: Apply the Mantel test to two distance matrices
- Pipelines
- diversity-lib: Plugin for computing community diversity.
- Methods
- alpha-passthrough: Alpha Passthrough (non-phylogenetic)
- beta-passthrough: Beta Passthrough (non-phylogenetic)
- beta-phylogenetic-meta-passthrough: Beta Phylogenetic Meta Passthrough
- beta-phylogenetic-passthrough: Beta Phylogenetic Passthrough
- bray-curtis: Bray-Curtis Dissimilarity
- faith-pd: Faith’s Phylogenetic Diversity
- jaccard: Jaccard Distance
- observed-features: Observed Features
- pielou-evenness: Pielou’s Evenness
- shannon-entropy: Shannon’s Entropy
- unweighted-unifrac: Unweighted Unifrac
- weighted-unifrac: Weighted Unifrac
- Methods
- emperor: Plugin for ordination plotting with Emperor.
- feature-classifier: Plugin for taxonomic classification.
- Pipelines
- Methods
- blast: BLAST+ local alignment search.
- classify-sklearn: Pre-fitted sklearn-based taxonomy classifier
- extract-reads: Extract reads from reference sequences.
- find-consensus-annotation: Find consensus among multiple annotations.
- fit-classifier-naive-bayes: Train the naive_bayes classifier
- fit-classifier-sklearn: Train an almost arbitrary scikit-learn classifier
- makeblastdb: Make BLAST database.
- vsearch-global: VSEARCH global alignment search
- feature-table: Plugin for working with sample by feature tables.
- Pipelines
- Methods
- filter-features: Filter features from table
- filter-features-conditionally: Filter features from a table based on abundance and prevalence
- filter-samples: Filter samples from table
- filter-seqs: Filter features from sequences
- group: Group samples or features by a metadata column
- merge: Combine multiple tables
- merge-seqs: Combine collections of feature sequences
- merge-taxa: Combine collections of feature taxonomies
- presence-absence: Convert to presence/absence
- rarefy: Rarefy table
- relative-frequency: Convert to relative frequencies
- rename-ids: Renames sample or feature ids in a table
- split: Split one feature table into many
- subsample-ids: Subsample table
- tabulate-feature-frequencies: Tabulate feature frequencies
- tabulate-sample-frequencies: Tabulate sample frequencies
- transpose: Transpose a feature table.
- Visualizers
- fragment-insertion: Plugin for extending phylogenies.
- longitudinal: Plugin for paired sample and time series analyses.
- Pipelines
- Methods
- Visualizers
- anova: ANOVA test
- linear-mixed-effects: Linear mixed effects modeling
- pairwise-differences: Paired difference testing and boxplots
- pairwise-distances: Paired pairwise distance testing and boxplots
- plot-feature-volatility: Plot longitudinal feature volatility and importances
- volatility: Generate interactive volatility plot
- metadata: Plugin for working with Metadata.
- phylogeny: Plugin for generating and manipulating phylogenies.
- Pipelines
- Methods
- fasttree: Construct a phylogenetic tree with FastTree.
- filter-table: Remove features from table if they’re not present in tree.
- filter-tree: Remove features from tree based on metadata
- iqtree: Construct a phylogenetic tree with IQ-TREE.
- iqtree-ultrafast-bootstrap: Construct a phylogenetic tree with IQ-TREE with bootstrap supports.
- midpoint-root: Midpoint root an unrooted phylogenetic tree.
- raxml: Construct a phylogenetic tree with RAxML.
- raxml-rapid-bootstrap: Construct a phylogenetic tree with bootstrap supports using RAxML.
- robinson-foulds: Calculate Robinson-Foulds distance between phylogenetic trees.
- quality-control: Plugin for quality control of feature and sequence data.
- Pipelines
- Methods
- Visualizers
- decontam-score-viz: Generate a histogram representation of the scores
- evaluate-composition: Evaluate expected vs. observed taxonomic composition of samples
- evaluate-seqs: Compare query (observed) vs. reference (expected) sequences.
- evaluate-taxonomy: Evaluate expected vs. observed taxonomic assignments
- quality-filter: Plugin for PHRED-based filtering and trimming.
- rescript: Pipeline for reference sequence annotation and curation.
- Pipelines
- evaluate-classifications: Interactively evaluate taxonomic classification accuracy.
- evaluate-cross-validate: Evaluate DNA sequence reference database via cross-validated taxonomic classification.
- evaluate-fit-classifier: Evaluate and train naive Bayes classifier on reference sequences.
- evaluate-taxonomy: Compute summary statistics on taxonomy artifact(s).
- get-silva-data: Download, parse, and import SILVA database.
- trim-alignment: Trim alignment based on provided primers or specific positions.
- Methods
- cull-seqs: Removes sequences that contain at least the specified number of degenerate bases and/or homopolymers of a given length.
- degap-seqs: Remove gaps from DNA sequence alignments.
- dereplicate: Dereplicate features with matching sequences and taxonomies.
- edit-taxonomy: Edit taxonomy strings with find and replace terms.
- extract-seq-segments: Use reference sequences to extract shorter matching sequence segments from longer sequences based on a user-defined ‘perc-identity’ value.
- filter-seqs-length: Filter sequences by length.
- filter-seqs-length-by-taxon: Filter sequences by length and taxonomic group.
- filter-taxa: Filter taxonomy by list of IDs or search criteria.
- get-bv-brc-genome-features: Fetch genome features from BV-BRC.
- get-bv-brc-genomes: Get genome sequences from the BV-BRC database.
- get-bv-brc-metadata: Fetch BV-BCR metadata.
- get-gtdb-data: Download, parse, and import SSU GTDB reference data.
- get-ncbi-data: Download, parse, and import NCBI sequences and taxonomies
- get-ncbi-data-protein: Download, parse, and import NCBI protein sequences and taxonomies
- get-ncbi-genomes: Fetch entire genomes and associated taxonomies and metadata using NCBI Datasets.
- get-unite-data: Download and import UNITE reference data.
- merge-taxa: Compare taxonomies and select the longest, highest scoring, or find the least common ancestor.
- orient-seqs: Orient input sequences by comparison against reference.
- parse-silva-taxonomy: Generates a SILVA fixed-rank taxonomy.
- reverse-transcribe: Reverse transcribe RNA to DNA sequences.
- subsample-fasta: Subsample an indicated number of sequences from a FASTA file.
- Visualizers
- Pipelines
- sample-classifier: Plugin for machine learning prediction of sample metadata.
- Pipelines
- classify-samples: Train and test a cross-validated supervised learning classifier.
- classify-samples-from-dist: Run k-nearest-neighbors on a labeled distance matrix.
- heatmap: Generate heatmap of important features.
- metatable: Convert (and merge) positive numeric metadata (in)to feature table.
- regress-samples: Train and test a cross-validated supervised learning regressor.
- Methods
- classify-samples-ncv: Nested cross-validated supervised learning classifier.
- fit-classifier: Fit a supervised learning classifier.
- fit-regressor: Fit a supervised learning regressor.
- predict-classification: Use trained classifier to predict target values for new samples.
- predict-regression: Use trained regressor to predict target values for new samples.
- regress-samples-ncv: Nested cross-validated supervised learning regressor.
- split-table: Split a feature table into training and testing sets.
- Visualizers
- Pipelines
- stats: Plugin for statistical analyses.
- taxa: Plugin for working with feature taxonomy annotations.
- types: Plugin defining types for microbiome analysis.
- Methods
- collate-feature-data-mags: Collate MAGs
- collate-ortholog-annotations: Collate ortholog annotations.
- collate-orthologs: Collate orthologs
- collate-sample-data-mags: Collate MAGs
- partition-feature-data-mags: Partition MAGs
- partition-orthologs: Partition orthologs
- partition-sample-data-mags: Partition MAGs
- Methods
- vizard: Generalized microbiome data visualization.
- vsearch: Plugin for clustering and dereplicating with vsearch.
- Pipelines
- Methods
- cluster-features-closed-reference: Closed-reference clustering of features.
- cluster-features-de-novo: De novo clustering of features.
- dereplicate-sequences: Dereplicate sequences.
- merge-pairs: Merge paired-end reads.
- uchime-denovo: De novo chimera filtering with vsearch.
- uchime-ref: Reference-based chimera filtering with vsearch.
- Visualizers