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commands.sh
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commands.sh
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#!/usr/bin/env bash
#file: docs/talk.md
#extracted 2018-12-07 13:03:45.450991
source activate qiime2-2018.11
# use `\` to break up long lines
qiime tools import \
--type 'SampleData[SequencesWithQuality]' \
--input-path ubc_manifest.csv \
--output-path ubc_data.qza \
--input-format SingleEndFastqManifestPhred33
qiime demux summarize --i-data ubc_data.qza --o-visualization qualities.qzv
qiime dada2 denoise-single \
--i-demultiplexed-seqs ubc_data.qza \
--p-trunc-len 220 --p-trim-left 10 \
--output-dir dada2 --verbose
qiime phylogeny align-to-tree-mafft-fasttree \
--i-sequences dada2/representative_sequences.qza \
--output-dir tree
qiime diversity core-metrics-phylogenetic \
--i-table dada2/table.qza \
--i-phylogeny tree/rooted_tree.qza \
--p-sampling-depth 8000 \
--m-metadata-file samples.tsv \
--output-dir diversity
qiime diversity alpha-group-significance \
--i-alpha-diversity diversity/shannon_vector.qza \
--m-metadata-file samples.tsv \
--o-visualization diversity/alpha_groups.qzv
qiime feature-classifier classify-sklearn \
--i-reads dada2/representative_sequences.qza \
--i-classifier gg-13-8-99-515-806-nb-classifier.qza \
--o-classification taxa.qza
qiime taxa barplot \
--i-table dada2/table.qza \
--i-taxonomy taxa.qza \
--m-metadata-file samples.tsv \
--o-visualization taxa_barplot.qzv
qiime taxa collapse \
--i-table dada2/table.qza \
--i-taxonomy taxa.qza \
--p-level 6 \
--o-collapsed-table genus.qza
qiime composition add-pseudocount --i-table genus.qza --o-composition-table added_pseudo.qza
qiime composition ancom \
--i-table added_pseudo.qza \
--m-metadata-file samples.tsv \
--m-metadata-column status \
--o-visualization ancom.qzv
qiime diversity core-metrics \
--i-table crc_dataset.qza \
--p-sampling-depth 100000 \
--m-metadata-file crc_metadata.tsv \
--output-dir crc_diversity
qiime feature-table relative-frequency \
--i-table crc_dataset.qza \
--o-relative-frequency-table crc_relative.qza
qiime perc-norm percentile-normalize \
--i-table crc_relative.qza \
--m-metadata-file crc_metadata.tsv \
--m-metadata-column disease_state \
--m-batch-file crc_metadata.tsv \
--m-batch-column study \
--p-otu-thresh 0.0 \
--o-perc-norm-table percentile_normalized.qza
python -e 'exec("""from qiime2 import Artifact
import pandas as pd
df = Artifact.load("percentile_normalized.qza").view(pd.DataFrame)
converted = Artifact.import_data("FeatureTable[Frequency]", df)
converted.save("pnorm_freq.qza")
""")'
qiime diversity beta \
--i-table pnorm_freq.qza \
--p-metric braycurtis \
--o-distance-matrix pnorm_bray.qza
qiime diversity pcoa --i-distance-matrix pnorm_bray.qza --o-pcoa pnorm_pcoa.qza
qiime emperor plot \
--i-pcoa pnorm_pcoa.qza \
--m-metadata-file crc_metadata.tsv \
--o-visualization pnorm_pcoa_emperor.qzv
qiime feature-table filter-samples \
--i-table crc_dataset.qza \
--m-metadata-file crc_metadata.tsv \
--p-where "study=='baxter'" \
--o-filtered-table baxter_table.qza
qiime feature-table filter-samples \
--i-table crc_dataset.qza \
--m-metadata-file crc_metadata.tsv \
--p-where "study=='zeller'" \
--o-filtered-table zeller_table.qza
python wilcoxon_test.py -i baxter_table.qza -m crc_metadata.tsv
python wilcoxon_test.py -i zeller_table.qza -m crc_metadata.tsv
python wilcoxon_test.py -i crc_dataset.qza -m crc_metadata.tsv
python wilcoxon_test.py -i pnorm_freq.qza -m crc_metadata.tsv
python wilcoxon_test.py -i pnorm_freq.qza -m crc_metadata.tsv -a 0.01 -t 0.1