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How to use qiime2

2025-03-25 Update From: SLTechnology News&Howtos shulou NAV: SLTechnology News&Howtos > Development >

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This article introduces the relevant knowledge of "how to use qiime2". In the operation of actual cases, many people will encounter such a dilemma, so let the editor lead you to learn how to deal with these situations. I hope you can read it carefully and be able to achieve something!

Qiime2 vsearch OTU pip finishing

# method 1. Merge both ends of DADA2 feature table to remove chimera Cut off the connector sequence and generate feature table in one step: cd $workdirmkdir dada2echo dada2 startdatecd dada2 qiime dada2 denoise-paired\-- i-demultiplexed-seqs $workdir/demux.qza\-- p-n-threads 1\-- p-trim-left-f 29-- p-trim-left-r 18\-- p-trunc-len-f 0-- p-trunc-len-r 0\ -- o-table dada2-table_biom.qza\-- o-representative-sequences dada2-repset-seqs.qza\-- o-denoising-stats denoising-stats.qzaecho dada2 enddate### method 2. External import feature table and representative sequence (commonly used) cd $workdirmkdir import_tablecd import_table# upload our generated OTU table otu_table.txt and representative sequence rep_set.fa# convert text to Biom1.0, note that biom-- version 2.1.5 Lex8 can 2.1.7 error qiime tools import-- input-path $workdir/otu_table.biom\-- type 'FeatureTable [Frequency]'-- input-format BIOMV100Format\-- output-path table_biom.qzaqiime tools import-- input-path $workdir/otus.fa\-- type 'FeatureData [Sequence]'\-- output-path repset-seqs.qza### method 3. Deblur feature table deblur can only input merged sequences, which is faster than dada2 # so do sequence processing first Remove primers, merge Filter low quality, etc. # Trim amplicon primers remove primer sequence # 341f # 806rqiime cutadapt trim-paired\-- i-demultiplexed-sequences $workdir/1.import_data/demux.qza\-- p-cores 4\-- p-no-indels\-- p-front-f CCTAYGGGRBGCASCAG\-- p-front-r GGACTACNNGGGTATCTAAT\-- o-trimmed-sequences primer-trimmed-demux.qza # Summarise the reads View result qiime demux summarize\-- I -data primer-trimmed-demux.qza\-- o-visualization primer-trimmed-demux.qzv\ # double-ended merge qiime vsearch join-pairs\-- i-demultiplexed-seqs primer-trimmed-demux.qza\-- p-threads 4\-- o-joined-sequences demux-joined.qza# to view the merger result qiime demux summarize\-- i-data demux-joined.qza\-- o-visualization demux-joined.qzv# quality control filter data qiime quality-filter Q- Score\-- i-demux demux-joined.qza\-- o-filtered-sequences demux-joined-filtered.qza\-- o-filter-stats demux-joined-filter-stats.qzaqiime metadata tabulate-- m-input-file demux-joined-filter-stats.qza\-- o-visualization demux-joined-filter-stats.qzv# production feature table comes with de-chimerism # deblur needs to enter a neat sequence of the same length when denoising So the trim needs to be the same length. Here we need to use the approximate length of the quality guaranteed sequence we wrote down in the previous join summary. The developers of D#eblur suggest setting a length (recommend setting this value to a length where the median quality score begins to drop too low) at which the mass score begins to decline rapidly. Yu # is in this example-- p-trim-length is 240. Qiime deblur denoise-16S\-- i-demultiplexed-seqs demux-joined-filtered.qza\-- p-trim-length 240\-- p-sample-stats\-- p-jobs-to-start 2\-- p-min-reads 1\-- o-representative-sequences rep-seqs.qza\-- o-table feature-table.qza\-- o-stats deblur-stats.qza# result visualization qiime feature-table summarize\-- i-table feature- Table.qza\-- o-visualization feature-table.qzvqiime deblur visualize-stats\-- i-deblur-stats deblur-stats.qza\-- o-visualization deblur-stats.qzv### method 4.Q2 vsearch otuecho vsearch startdatecd $workdirmkdir vsearchcd vsearchqiime vsearch dereplicate-sequences\-- i-sequences $workdir/deblur/demux-joined-filtered.qza\-- o-dereplicated-table table.qza\-- o-dereplicated-sequences rep-seqs.qzaecho vsearch denovo startdate#denovo pick otuqiime vsearch cluster-features -de-novo\-- i-table table.qza\-- i-sequences rep-seqs.qza\-- p-perc-identity 0.99\-- o-clustered-table table-dn-99.qza\-- o-clustered-sequences rep-seqs-dn-99.qzaecho vsearch close startdate#close reference qiime vsearch cluster-features-closed-reference\-- i-table table.qza\-- i-sequences rep-seqs.qza\-- i-reference-sequences 85 _ Otus.qza\-- p-perc-identity 0.85\-- o-clustered-table table-cr-85.qza\-- o-clustered-sequences rep-seqs-cr-85.qza\-- o-unmatched-sequences unmatched-cr-85.qzaecho vsearch open startdate#open referencedqiime vsearch cluster-features-open-reference\-- i-table table.qza\-- i-sequences rep-seqs.qza\-- i-reference-sequences 85_otus.qza\-- p -perc-identity 0.85\-- o-clustered-table table-or-85.qza\-- o-clustered-sequences rep-seqs-or-85.qza\-- o-new-reference-sequences new-ref-seqs-or-85.qzaecho vsearch open enddate#denovo removes chimera qiime vsearch uchime-denovo\-- i-table atacama-table.qza\-- i-sequences atacama-rep-seqs.qza\-- output-dir uchime-dn-out### Feature table and representative sequence statistics qiime feature-table summarize\-i-table table_biom.qza\-- o-visualization table.qzv\-- m-sample-metadata-file $fastmapqiime feature-table tabulate-seqs\-- i-data repset-seqs.qza\-- o-visualization rep-seqs.qzv# download qzv online view Dada2 only has more than 1, 000 ASV "how to use qiime2" content here, thank you for reading. 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