--- name: bio-microbiome-qiime2-workflow description: QIIME2 command-line workflow for 16S/ITS amplicon analysis. Alternative to DADA2/phyloseq R workflow with built-in provenance tracking. Use when preferring CLI over R, needing reproducible provenance, or working within QIIME2 ecosystem. tool_type: cli primary_tool: qiime2 --- ## Version Compatibility Reference examples tested with: DADA2 1.30+, MAFFT 7.520+, QIIME2 2024.2+, phyloseq 1.46+, scanpy 1.10+, scikit-learn 1.4+ Before using code patterns, verify installed versions match. If versions differ: - CLI: ` --version` then ` --help` to confirm flags If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying. # QIIME2 Amplicon Workflow **"Run my amplicon analysis through QIIME2"** -> Process 16S/ITS amplicon data end-to-end using the QIIME2 CLI with built-in provenance tracking, from import through denoising, taxonomy, and diversity analysis. - CLI: `qiime dada2 denoise-paired`, `qiime diversity core-metrics-phylogenetic` ## Import Data ```bash # Import paired-end FASTQ with manifest qiime tools import \ --type 'SampleData[PairedEndSequencesWithQuality]' \ --input-path manifest.tsv \ --output-path demux.qza \ --input-format PairedEndFastqManifestPhred33V2 # View demultiplexed summary qiime demux summarize \ --i-data demux.qza \ --o-visualization demux.qzv ``` ## Denoise with DADA2 ```bash # DADA2 denoising (creates ASV table + representative sequences) qiime dada2 denoise-paired \ --i-demultiplexed-seqs demux.qza \ --p-trunc-len-f 240 \ --p-trunc-len-r 160 \ --p-trim-left-f 0 \ --p-trim-left-r 0 \ --p-max-ee-f 2 \ --p-max-ee-r 2 \ --p-n-threads 0 \ --o-table table.qza \ --o-representative-sequences rep-seqs.qza \ --o-denoising-stats denoising-stats.qza # View denoising stats qiime metadata tabulate \ --m-input-file denoising-stats.qza \ --o-visualization denoising-stats.qzv ``` ## Alternative: Deblur Denoising ```bash # Quality filter first qiime quality-filter q-score \ --i-demux demux.qza \ --o-filtered-sequences demux-filtered.qza \ --o-filter-stats filter-stats.qza # Deblur denoise qiime deblur denoise-16S \ --i-demultiplexed-seqs demux-filtered.qza \ --p-trim-length 250 \ --p-sample-stats \ --o-representative-sequences rep-seqs-deblur.qza \ --o-table table-deblur.qza \ --o-stats deblur-stats.qza ``` ## Taxonomy Assignment ```bash # Download pre-trained classifier (SILVA 138) # wget https://data.qiime2.org/2024.5/common/silva-138-99-nb-classifier.qza # Classify with sklearn naive Bayes qiime feature-classifier classify-sklearn \ --i-classifier silva-138-99-nb-classifier.qza \ --i-reads rep-seqs.qza \ --o-classification taxonomy.qza # Visualize taxonomy qiime metadata tabulate \ --m-input-file taxonomy.qza \ --o-visualization taxonomy.qzv # Taxonomic barplot qiime taxa barplot \ --i-table table.qza \ --i-taxonomy taxonomy.qza \ --m-metadata-file metadata.tsv \ --o-visualization taxa-barplot.qzv ``` ## Phylogenetic Tree ```bash # Build phylogeny with MAFFT + FastTree qiime phylogeny align-to-tree-mafft-fasttree \ --i-sequences rep-seqs.qza \ --o-alignment aligned-rep-seqs.qza \ --o-masked-alignment masked-aligned-rep-seqs.qza \ --o-tree unrooted-tree.qza \ --o-rooted-tree rooted-tree.qza ``` ## Diversity Analysis ```bash # Core metrics (alpha + beta diversity) qiime diversity core-metrics-phylogenetic \ --i-phylogeny rooted-tree.qza \ --i-table table.qza \ --p-sampling-depth 10000 \ --m-metadata-file metadata.tsv \ --output-dir core-metrics-results # Alpha diversity significance qiime diversity alpha-group-significance \ --i-alpha-diversity core-metrics-results/shannon_vector.qza \ --m-metadata-file metadata.tsv \ --o-visualization shannon-significance.qzv # Beta diversity significance (PERMANOVA) qiime diversity beta-group-significance \ --i-distance-matrix core-metrics-results/weighted_unifrac_distance_matrix.qza \ --m-metadata-file metadata.tsv \ --m-metadata-column Group \ --p-method permanova \ --o-visualization weighted-unifrac-permanova.qzv ``` ## Differential Abundance (ANCOM) **Goal:** Identify taxa with significantly different abundances between groups using QIIME2's ANCOM implementation. **Approach:** Collapse the feature table to genus level, add pseudocounts for log-ratio computation, and run ANCOM to test for differential abundance per taxon. ```bash # Collapse to genus level qiime taxa collapse \ --i-table table.qza \ --i-taxonomy taxonomy.qza \ --p-level 6 \ --o-collapsed-table table-l6.qza # Add pseudocount and run ANCOM qiime composition add-pseudocount \ --i-table table-l6.qza \ --o-composition-table comp-table-l6.qza qiime composition ancom \ --i-table comp-table-l6.qza \ --m-metadata-file metadata.tsv \ --m-metadata-column Group \ --o-visualization ancom-l6.qzv ``` ## Export to R/Python ```bash # Export feature table to BIOM qiime tools export \ --input-path table.qza \ --output-path exported # Convert BIOM to TSV biom convert \ -i exported/feature-table.biom \ -o feature-table.tsv \ --to-tsv # Export taxonomy qiime tools export \ --input-path taxonomy.qza \ --output-path exported # Export tree qiime tools export \ --input-path rooted-tree.qza \ --output-path exported ``` ## Manifest File Format ``` # manifest.tsv (tab-separated) sample-id forward-absolute-filepath reverse-absolute-filepath sample1 /path/to/sample1_R1.fastq.gz /path/to/sample1_R2.fastq.gz sample2 /path/to/sample2_R1.fastq.gz /path/to/sample2_R2.fastq.gz ``` ## Metadata File Format ``` # metadata.tsv (tab-separated) sample-id Group Timepoint sample1 Treatment Day0 sample2 Control Day0 sample3 Treatment Day7 ``` ## Related Skills - amplicon-processing - DADA2 R workflow alternative - taxonomy-assignment - More database options - diversity-analysis - phyloseq R alternative - differential-abundance - ALDEx2/ANCOM-BC in R