ITS2 pipeline Sequences were amplified following the EMP, http://www.earthmicrobiome.org/protocols-and-standards/its/ Illumina Hiseq 2500, 250 bp paired-end reads.
Trans2_rc_in_20_sequences CTGTCTCTTATACACATCTCCGAGCCCACGAGAC
Trans1_rc CTGTCTCTTATACACATCTGACGCTGCCGACGA
Reverse complement of 3′ Illumina adapter -> CAAGCAGAAGACGGCATACGAGAT Golay barcode -> NNNNNNNNNN Reverse primer linker -> CG Reverse primer (ITS2; Note: This is identical to ITS2 from White et al., 1990.) -> GCTGCGTTCTTCATCGATGC
qiime tools import --type 'FeatureData[Taxonomy]' --source-format HeaderlessTSVTaxonomyFormat --input-path sh_ --output-path qiime-ref-taxonomy_99.qz
qiime tools import --type 'FeatureData[Taxonomy]' --source-format HeaderlessTSVTaxonomyFormat --input-path sh_ --output-path q iime-ref-taxonomy_99.qz
sbatch ./cutadapt_trim_adapters_and_primers.sh
qiime tools import --type 'SampleData[PairedEndSequencesWithQuality]' --input-path cutadapt_data/ --source-format CasavaOneEightSingleLanePerSampleDirFmt --output-path cutadapt-paired-end.qza
Step 1 NEW! : Trim sequences and remove primers in qiime2 : Make sure there are no reverse primsers on your forward reads cutadapt plugin which provides trim-paired option
qiime tools import --type 'SampleData[PairedEndSequencesWithQuality]' --input-path raw_data/ --source-format CasavaOneEightSingleLanePerSampleDirFmt --output-path raw-paired-end.qza
qiime cutadapt trim-paired --i-demultiplexed-sequences raw-paired-end.qza --o-trimmed-sequences trimmed-paired-end.qza --p-cores 60 --p-anywhere-f CTGTCTCTTATACACATCTCCGAGCCCACGAGAC --p-anywhere-r CTGTCTCTTATACACATCTGACGCTGCCGACGA --p-front-f CAAGCAGAAGACGGCATACGAGAT
Step 2: DADA2 : after trimming primers, you may want to disable truncation filtering entirely by setting trunc_len to 0
qiime dada2 denoise-paired --p-trim-left-f 0 --p-trim-left-r 0 --p-trunc-len-f 0 --p-trunc-len-r 0 --i-demultiplexed-seqs trimmed-paired-end.qza --o-table trimmed-0-0-table --o-representative-sequences trimmed-req-seqs --verbose --p-n-threads 60
qiime dada2 denoise-single --p-trim-left 0 --p-trunc-len 0 --i-demultiplexed-seqs cutadapt-single-end.qza --o-table cutadapt-single-end-0-0-tqble --o-representative-sequences cutadapt-single-end-rep-seqs --verbose --p-n-threads 60
qiime feature-classifier classify-consensus-blast --i-query trimmed-req-seqs.qz --i-reference-taxonomy reference_UNITE/qiime-ref-taxonomy_99.qza --i-reference-reads reference_UNITE/qiime_fasta_99.qza --o-classification unite_99_9_trimmed-paired-end-classification_blast.qza --p-perc-identity 0.9 --p-maxaccepts 1
qiime feature-classifier classify-consensus-blast --i-query cutadapt-single-end-rep-seqs.qza --i-reference-taxonomy reference_UNITE/qiime-ref-taxonomy_99.qza --i-reference-reads reference_UNITE/qiime_fasta_99.qza --o-classification unite_99_9_cutadapt-single-end-classification_blast.qza --p-perc-identity 0.9 --p-maxaccepts 1
Make blast database for taxonomy assignment (go into database rep set) only if using joes taoxnomy assignment
makeblastdb -dbtype nucl -in 99_otus.fasta -out 99_otus
mkdir raw_reads & cd raw_reads
mv /path/to/project/dir//R1 ./ mv /path/to/project/dir//R3 ./
for your data I simply needed to fix the ones with ITS in it. (remove the -n to actually make the change)
rename -v -n 's/(.)-(.)__(.*)/$1$2_$3/' *
cd raw_reads join_reads_and_prep_for_qiime.py ./
truncate_reverse_primer.py -f seqs.fna -m mapping_file.txt -o truncate_reverse_primers
pick_open_reference_otus.py -i seqs.fna -o pick_references_output_open -r /home/genome/joseph7e/MEG_its_test/its_database/rep_set/97_otus.fasta -p parameters
qiime tools import
--input-path ../otu_table_mc2.biom
--type "FeatureTable[Frequency]"
--source-format BIOMV210Format
--output-path feature-table-from_qiime1.qza
qiime tools import
--type "FeatureData[Taxonomy]"
--input-path ../uclust_assigned_taxonomy/rep_set_tax_assignments.txt
--output-path taxonomy_from_qiime1
qiime feature-table summarize
--i-table feature-table-from_qiime1.qza
--o-visualization table.qzv
--m-sample-metadata-file ../../../Microbiome_ITS_Mapping_File.csv
qiime taxa barplot
--i-table feature-table-from_qiime1.qza
--i-taxonomy taxonomy_from_qiime1.qza
--m-metadata-file Microbiome_ITS_Mapping_File.tsv
--o-visualization taxa-bar-plots.qzv
qiime tools import
--type "FeatureData[Sequence]"
--input-path ../rep_set.fna
--output-path rep_set_from_qiime1
qiime alignment mafft
--i-sequences rep_set_from_qiime1.qza
--o-alignment aligned-rep-seqs.qza
qiime alignment mask
--i-alignment aligned-rep-seqs.qza
--o-masked-alignment masked-aligned-rep-seqs.qza
qiime phylogeny fasttree
--i-alignment masked-aligned-rep-seqs.qza
--o-tree unrooted-tree.qza
qiime phylogeny midpoint-root --i-tree tree_unrooted_from_qiime1.qza --o-rooted-tree rooted-tree.qza
my_numbers : 6092, 2130, 10065
sampling_depth=10065
qiime diversity core-metrics
--i-phylogeny rooted-tree.qza
--i-table feature-table-from_qiime1.qza
--p-sampling-depth $sampling_depth
--output-dir core-metric_$sampling_depth
qiime diversity alpha-group-significance
--i-alpha-diversity core-metric_$sampling_depth/faith_pd_vector.qza
--m-metadata-file Microbiome_ITS_Mapping_File.tsv
--o-visualization core-metric_$sampling_depth/faith-pd-group-significance.qzv
qiime diversity alpha-group-significance
--i-alpha-diversity core-metric_$sampling_depth/evenness_vector.qza
--m-metadata-file Microbiome_ITS_Mapping_File.tsv
--o-visualization core-metric_$sampling_depth/evenness-group-significance.qzv
qiime diversity alpha-correlation
--i-alpha-diversity core-metric_$sampling_depth/faith_pd_vector.qza
--m-metadata-file Microbiome_ITS_Mapping_File.tsv
--o-visualization core-metric_$sampling_depth/faith-pd-correlation.qzv
qiime diversity alpha-correlation
--i-alpha-diversity core-metric_$sampling_depth/evenness_vector.qza
--m-metadata-file Microbiome_ITS_Mapping_File.tsv
--o-visualization core-metric_$sampling_depth/evenness-correlation.qzv
categories: #SampleID,BarcodeSequence,LinkerPrimerSequence,SampleType,Year,State,WNSStatus,Species,Sex,Description
category=Year
qiime diversity beta-group-significance
--i-distance-matrix core-metric_$sampling_depth/unweighted_unifrac_distance_matrix.qza
--m-metadata-file Microbiome_ITS_Mapping_File.tsv
--m-metadata-category $category
--o-visualization core-metric_$sampling_depth/unweighted-unifrac-$category-significance.qzv
sampling_depth=2130 #category=WNSStatus
qiime emperor plot
--i-pcoa core-metric_$sampling_depth/unweighted_unifrac_pcoa_results.qza
--m-metadata-file ../../../../Microbiome_ITS_Mapping_File.txt
--o-visualization core-metric_$sampling_depth/unweighted-unifrac-emperor.qzv
qiime emperor plot
--i-pcoa core-metric_$sampling_depth/bray_curtis_pcoa_results.qza
--m-metadata-file ../../../../Microbiome_ITS_Mapping_File.txt
--o-visualization core-metric_$sampling_depth/bray-curtis-emperor.qzv
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