A pipeline that incorporates different tools and stages of sequencing reads' analysis to reach a working classification of the fungal taxa in samples
ITS2-pipeline is an assembled flow of ITS2 amplification sequence analysis. It takes the user from the first initial stages of demultiplexed fastq's representing ITS2-amplification sequencing results all the way to taxonomic classification of ASVs and additional qiime2 types of outputs. The overall flow is:
demultiplexed fastq files (PE) --> merged pairs --> trim low quality reads and primer sequences --> within the qiime2 suite: dada2 generation and denoising ASVs --> ITSx facilited extraction of ITS2 regions from merged reads --> naive-bayes based classification of amplicons based on UNITE database version 8 sequences
After downloding or cloning the repository, run:
pip install -r requisites.txtThe UNITE database files required for classification can be downloaded from: Abarenkov, Kessy; Zirk, Allan; Piirmann, Timo; Pöhönen, Raivo; Ivanov, Filipp; Nilsson, R. Henrik; Kõljalg, Urmas (2020): UNITE QIIME release for Fungi. Version 04.02.2020. UNITE Community. https://doi.org/10.15156/BIO/786385
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A top-level 'home' directory should be selected.
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Modify the file 'basic_pipeline.py' with your selected home directory name under the define_params() function: paths['home'] = Path('')
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Under that directory, make a directory named 'samples'
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Under samples, for each sequencing library, make a directory with the library name, e.g. 'Library1'
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Under each library directory make three directories:
- 'fastq' - where sample fastq's of the library should be copied (zipped or unzipped)
- 'metadata' - place a qiime2 compatible, tab-delimited (.tsv) file with per-sample information. Each sample should at least have a 'sampleid' column. See the qiime2 documentation for details (https://docs.qiime2.org/2019.10/tutorials/metadata/)
python basic_pipe.py <Library name> (e.g. 'Library1')Several output files are generated in different subdirectories
| Subdirectory | Explanation |
|---|---|
| merged | Results of the PEAR merging of R1 and R2 |
| trimmed | Results of trimming primer sequences and filtering out short amplicons with cutadapt |
| qiime_ready | Results from qiime portion of pipeline (details below) |
| logs | Logging of pipeline stages |
Under the qiime_ready directory are several types of output files:
| File name | Explanation |
|---|---|
| .qzv files | for viewing the results in qiime2 viewer (https://view.qiime2.org/) |
| demux_seqs.qza | merged, trimmed, filtered amplicons from paired reads in library samples |
| rep-seqs-untrimmed.qza | Dada2 denoised ASVs |
| stats.qza | Dada2 statistics |
| table.qza | ASV per sample table |
| dna-sequences.fasta | fasta format of ASV sequences |
| its.* files | results files of running ITSx on ASV sequences, the its.ITS2.fasta file has the ITS2 portion |
| rep_seqs.qza/fasta | Extracted ITS2 portions from ASVs |
| feature-table.biom | BIOM table of ASV reads per sample |
| table.from_biom.txt | text version of biom table of ASVs' reads per sample |
| features.csv | feature IDs |
| ref_seqs.qza | primer extracted regions of UNITE ver8 sequences |
| unite_dev_dynamic_otus.qza, ref-taxonomy_unite_dev_dynamic.qza | qiime2 input ready version of UNITE version 8.2 (sh_refs_qiime_ver8_dynamic_04.02.2020.fasta, sh_taxonomy_qiime_ver8_dynamic_04.02.2020.txt) |
| classifier.qza | naive bayes trained classifier |
| taxonomy.qza/csv | feature ID, sequence, taxonomomic classification and classification confidence score |
| summary.csv | concatenated results - ASV feature id, taxonomic classification and score, ITSx classification, reads per sample |
| taxa_bar_plots.qzv | visual of stack bar plots of ASV relative abundance per sample |
Feel free to dive in! Open an issue or submit PRs.