16S_QIIME2

This is a Snakemake based 16S QIIME2 pipeline.

Installation

To install, we assume you already have installed Miniconda3 (4.7.10+) (https://docs.conda.io/en/latest/miniconda.html)

• Clone this repository:

git clone https://github.com/PennChopMicrobiomeProgram/16S_QIIME2.git

• Create a conda environment:

cd 16S_QIIME2
conda create --name qiime2-2023.2 --file environment.yml

To run the pipeline, activate the envrionment (currently based on QIIME2 2023.2) by entering conda activate qiime2-2023.2

• The following software also need to be installed within the environment you created:
  • dnabc (https://github.com/PennChopMicrobiomeProgram/dnabc)
  • unassigner (https://github.com/kylebittinger/unassigner)

Required input files for the pipeline

To run the pipeline, we need

• Multiplexed R1/R2 read pairs (Undetermined_S0_L001_R1_001.fastq.gz, Undetermined_S0_L001_R2_001.fastq.gz), and
• QIIME2 compatible mapping file
  • Tab delimited
  • The first two columns should be SampleID (or #SampleID) and BarcodeSequence

Databases required

Qiime2 classifier (https://docs.qiime2.org/2023.2/data-resources/) dada2 training set (https://benjjneb.github.io/dada2/training.html)

How to run

• Create a project directory, e.g. ~/16S_QIIME2/test and put the mapping file, e.g. test_mapping_file.tsv in the project directory. If you are running this on the cluster, the data would be staged in a scratch drive e.g. /scr1/username
• Edit qiime2_config.yml so that it suits your project. In particular,
  • all: project: path to the project directory, e.g. ~/16S_QIIME2/test
  • all: mux_dir: the direcotry containing multiplexed R1/R2 read pairs, e.g. ~/16S_QIIME2/test/multiplexed_fastq
  • all: mapping: the name of mapping file, e.g. test_mapping_file.tsv
• Edit config.yaml for platform specific settings (currently formatted for SLURM on republica)
• (Optional) Edit rules\targets\targets.rules to comment out steps you don't need (e.g. #TARGET_PICRUST2)
• To run the pipeline, activate the envrionment by entering conda activate qiime2-2023.2, cd into 16S_QIIME2 and execute snakemake --profile ./
  • If using sbatch you can just execute the script ./run_snakemake.bash
  • You can also do a dryrun: ./dryrun_snakemake.bash

Intermediate steps and corresponding input/output

Demultiplexing

Input

• Multiplexed R1/R2 read pairs
• QIIME2 compatible mapping file

Output

• Demultiplexed fastq(.gz) files
• Total read count summary (tsv)
• QIIME2 compatible manifest file (csv)

QIIME2 import

Input

• QIIME2 compatible manifest file
• Demultiplexed fastq files

Output

• QIIME2 PairedEndSequencesWithQuality artifact and corresponding visualization
• QIIME2-generated demultiplexing stats

DADA2 denoise

Input

• QIIME2 PairedEndSequencesWithQuality artifact

Output

• Feature table (QIIME2 artifact, tsv)
• Representative sequences (QIIME2 artifact, fasta)

Taxonomy classification

Input

• Representative sequences

Output

• Taxonomy classification table (QIIME2 artifact, tsv)

Tree building

Input

• Representative sequences

Output

• Aligned sequence
• Masked (aligned) sequence
• Unrooted tree
• Rooted tree

Diversity calculation

Input

• Rooted tree

Output

• Various QIIME2 diversity metric artifacts
• Faith phylogenetic diversity vector (tsv)
• Weighted/unweighted UniFrac distance matrices (tsv)

Unassigner

Input

• Representative sequences (fasta)

Output

• Unassigner output (tsv) for species level classification of representative sequences

dada2_species

Input

• Representative sequences (fasta)

Output

• Dada2 species assignments (tsv)
• Dada2 Raw data for loading in R (RData format)

vsearch

Input

• Representative sequences (fasta)

Output

• Vsearch report (tsv) customized to be like BLAST results (see config.yml)
• Vsearch list of representative sequences that aligned (fasta)

NB: Currently picrust2-2021.11_0 does not work with qiime2 2023.2 but these would be the outputs if it did:

picrust2

Input

• Feature table (QIIME2 artifact, tsv)
• Representative sequences (QIIME2 artifact, fasta)

Output

• KEGG orthologs counts (tsv)
• Enzyme classification counts (QIIME2 artifact)
• KEGG pathway counts (QIIME2 artifact)