TRANA

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Taxonomic Reconstruction and Analysis of NGS Amplicons - A pipeline based on EMU, a taxonomic profiler optimized for long 16S rRNA reads.

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# TRANA

[![Nextflow](https://img.shields.io/badge/nextflow%20DSL2-%E2%89%A522.10.1-23aa62.svg)](https://www.nextflow.io/)
[![Run with conda](http://img.shields.io/badge/run%20with-conda-3EB049?labelColor=000000&logo=anaconda)](https://docs.conda.io/en/latest/)
[![Run with docker](https://img.shields.io/badge/run%20with-docker-0db7ed?labelColor=000000&logo=docker)](https://www.docker.com/)
[![Run with singularity](https://img.shields.io/badge/run%20with-singularity-1d355c.svg?labelColor=000000)](https://sylabs.io/docs/)

## Introduction

TRANA (previously known as gms_16S) bioinformatics analysis pipeline for the [EMU tool](https://github.com/treangenlab/emu).

This Nextflow pipeline utilizes FastQC, Nanoplot, MultiQC, Porechop_ABI,
Filtlong, EMU, and Krona. EMU is the tool that does the taxonomic profiling of
16S rRNA reads. The results are displayed with Krona. Built with Nextflow, it
ensures portability and reproducibility across different computational
infrastructures. It has been tested on Linux and on mac M1 (not recommended,
quite slow). FastQC and Nanoplot performs quality control, Porechop_ABI trims
adapters (optional), Filtlong filters the fastq-files such that only reads
that are close to 1500 bp are used (optional), EMU assigns taxonomic
classifications, and Krona visualises the result table from EMU. The pipeline
enables microbial community analysis, offering insights into the diversity in
samples.

The pipeline is built using [Nextflow](https://www.nextflow.io), a workflow
tool to run tasks across multiple compute infrastructures in a very portable
manner. It uses Docker/Singularity containers making installation trivial and
results highly reproducible. The [Nextflow DSL2](https://www.nextflow.io/docs/latest/dsl2.html) implementation of this
pipeline uses one container per process which makes it much easier to maintain
and update software dependencies.

## Pipeline summary

![Pipeline overview image](https://raw.githubusercontent.com/genomic-medicine-sweden/TRANA/main/docs/images/emu_workflow_20251010_300dpi.png)

The Nanopore and shortread workflow is available.
Minor testing has been done for PacBio and it seems to work.
MultiQC collects only info from FastQC and some information about software versions and
pipeline info.

![Krona plot](https://raw.githubusercontent.com/genomic-medicine-sweden/TRANA/main/docs/images/krona_example_data_.svg)

Krona plot

![Likelihood heatmap per sample](https://raw.githubusercontent.com/genomic-medicine-sweden/TRANA/main/docs/images/medium_Mock_dil_1_2_BC1_assignment_heatmap.png)
Heatmap generated from from likelihood data. Each read has a likelihood that it is derived from a certain taxon.
The likelihoods for a read always sums up to one.

![sample-control bar plot comparison. Abundance](https://raw.githubusercontent.com/genomic-medicine-sweden/TRANA/main/docs/images/medium_Mock_dil_1_2_BC1_counts_vs_controls.png)
If your data has one or two controls e.g., a negative and a positive control or spike, then it is possible to generate bar plots for a quick comparison
between each sample and each control. This is supported for absolute abundance and relative abundance (see image below)

![sample-control bar plot comparison. Relative abundance](https://raw.githubusercontent.com/genomic-medicine-sweden/TRANA/main/docs/images/medium_Mock_dil_1_2_BC1_vs_controls.png)
Relative abundance comparison to controls

## Quick Start

1. Install [Nextflow](https://www.nextflow.io/docs/latest/getstarted.html#installation) (`>=22.10.1`)
2. Install any of [Docker](https://docs.docker.com/engine/installation/),
   [Singularity](https://www.sylabs.io/guides/3.0/user-guide/) (you can follow
   [this tutorial](https://singularity-tutorial.github.io/01-installation/)),
   [Podman](https://podman.io/), [Shifter](https://nersc.gitlab.io/development/shifter/how-to-use/)
   or [Charliecloud](https://hpc.github.io/charliecloud/) for full pipeline
   reproducibility (you can use [Conda](https://conda.io/miniconda.html) both
   to install Nextflow itself and also to manage software within pipelines.
   Please only use it within pipelines as a last resort. See
   [docs](https://nf-co.re/usage/configuration#basic-configuration-profiles)).
3. Add you samples to an input file e.g., `sample_sheet.csv`. See examples.
4. Run `make install` which will gunzip all gzipped files in the database
   directory (`assets/databases/emu_database`) and the krona/taxonomy directory
   (`assets/databases/krona/taxonomy`)
5. Run your command:

```bash
nextflow run main.nf \
  --input sample_sheet.csv
  --outdir [absolute path]/trana/results \
  --db /[absolute path]/trana/assets/databases/emu_database \
  --seqtype map-ont \
   -profile singularity,test \
  --quality_filtering \
  --longread_qc_qualityfilter_minlength 1200 \
  --longread_qc_qualityfilter_maxlength 1800
```

## Runs with Nanopore barcode directories

You can run with or without a sample sheet. If no sample_sheet is used, the
results will be named according to the barcode. If a sample sheet is used the
results will be named after whats in the second column of the sample sheet. Note
that the `--input` flag is not needed when `--merge_fastq_pass` is defined.

Run without barcode sample sheet:

```bash
nextflow run main.nf \
  --outdir [absolute path]/trana/results \
  --db /[absolute path]/trana/assets/databases/emu_database \
  --seqtype map-ont \
   -profile singularity,test \
  --quality_filtering \
  --longread_qc_qualityfilter_minlength 1200 \
  --longread_qc_qualityfilter_maxlength 1800 \
  --merge_fastq_pass /[absolute path]/trana/fastq_pass/
```

Run with barcode sample sheet:

```bash
nextflow run main.nf \
  --outdir /[absolute path to]/trana/results \
  --db /[absolute path to database]/trana/assets/databases/emu_database \
  --seqtype map-ont \
   -profile singularity,test \
  --quality_filtering \
  --longread_qc_qualityfilter_minlength 1200 \
  --longread_qc_qualityfilter_maxlength 1800 \
  --merge_fastq_pass /[absolute path to fastq_pass]/fastq_pass/ \
  --barcodes_samplesheet /[absolute path to barcode sample sheet]/sample_sheet_merge.csv
```

## Runs with shortreads

When running TRANA with short reads, the primer sequences are trimmed using Cutadapt by default using the provided primer sequences.
The primer sequences can be provided in the sample-sheet or passed as arguments (FW_primer, RV_primer). Primer trimming with Cutadapt can be skipped with --skip_cutadapt.

```bash
sample,fastq_1,fastq_2,FW_primer,RV_primer
SAMPLE,/absolute_path/trana/Sample_R1_001.fastq.gz,/absolute_path/trana/Sample_R2_001.fastq.gz,GTGCCAGCMGCCGCGGTAA,GGACTACNVGGGTWTCTAAT
```

```bash
nextflow run main.nf \
  --input sample_sheet.csv
  --outdir [absolute path]/trana/results \
  --db /[absolute path]/trana/assets/databases/emu_database \
  --seqtype sr \
   -profile singularity \
  --FW_primer AGCTGNCCTG\
  --RV_primer TGCATNCTGA
```

## Sample sheets

There are two types of sample sheets that can be used:

1. If the fastq files are already concatenated/merged i.e., the fastq-files in
   Nanopore barcode directories have been concatenated already, the `--input` can
   be used. `--input` expects a `.csv` sample sheet with 3 columns (note the
   header names). It looks like this (See also the `examples` directory):
   ```csv
   sample,fastq_1,fastq_2
   SAMPLE_1,/absolute_path/trana/assets/test_assets/medium_Mock_dil_1_2_BC1.fastq.gz,
   SAMPLE_2,/absolute_path/trana/assets/test_assets/medium_Mock_dil_1_2_BC3.fastq.gz,
   ```
2. If the fastq files are separated in their respective barcode folder i.e., you
   have several fastq files for each sample and they are organized in barcode
   directories in a fastq_pass directory.
   a) If you do not want to create a sample sheet for the barcodes, then the
   results will be named according to the barcode folders. flag
   `--merge_fastq_pass`
   b) If you want your own sample names on the results, then use
   `--merge_fastq_pass` in combination with `--barcodes_samplesheet`. This
   requires a barcode sample sheet which is comma separated. See example file
   `sample_sheet_merge.csv` in `examples` for a demonstration.

## Useful env variables

```config
NXF_WORK = working directory. # work directory,
                              # set this to a shared place.
                              # export NXF_WORK=/path/to/your/working/dir
APPTAINER_TMPDIR
NXF_SINGULARITY_CACHEDIR
APPTAINER_CACHEDIR
```

## Multiqc report

Fastqc results will be shown only for unprocessed reads. For runs using the 'map-ont' flag, qc-results from nanoplot will be
shown for unprocessed and processed reads.

## Useful commands for developers

Note that there is a `Makefile` available with a few useful commands to use
when developing:

- `make check` to run most checks that are also run on CI:
  `pre-commit`/`prettier`, `nf-core` lint, and `nf-test test`).
  - **Note:** It is a good idea to run this command before pushing your changes
    to a new pull request!
- `make precommit` to only run pre-commit/prettier.
- `lint` to run the nf-core lint checks.
- `test` to run the nf-test tests.

**Tip:** To see which make commands are available, you can always type `make ` and
then hit `TAB` twice.

## Credits

TRANA was originally written by [@fwa93](https://github.com/fwa93) and is further developed and
maintained by gms-mikro from Genomic Medicine Sweden:
@samuell
@ryanjameskennedy
@sofstam
@AnderssonOlivia
@kdannenberg
@ikarls
@bokelund

This pipeline is not a formal nf-core pipeline but it partly uses code and
infrastructure developed and maintained by the [nf-core](https://nf-co.re)
community, reused here under the [MIT license](https://github.com/nf-core/tools/blob/master/LICENSE).

> The nf-core framework for community-curated bioinformatics pipelines.
>
> Philip Ewels, Alexander Peltzer, Sven Fillinger, Harshil Patel, Johannes
> Alneberg, Andreas Wilm, Maxime Ulysse Garcia, Paolo Di Tommaso & Sven
> Nahnsen.
>
> Nat Biotechnol. 2020 Feb 13. doi: 10.1038/s41587-020-0439-x.
> In addition, references of tools and data used in this pipeline are as follows:

### [Nextflow](https://pubmed.ncbi.nlm.nih.gov/28398311/)

> Di Tommaso P, Chatzou M, Floden EW, Barja PP, Palumbo E, Notredame C.
> Nextflow enables reproducible computational workflows. Nat Biotechnol. 2017
> Apr 11;35(4):316-319. doi: 10.1038/nbt.3820. PubMed PMID: 2839>

### Pipeline tools

- [FastQC](https://www.bioinformatics.babraham.ac.uk/projects/fastqc/)

- [MultiQC](https://pubmed.ncbi.nlm.nih.gov/27312411/)
  > Ewels P, Magnusson M, Lundin S, Käller M. MultiQC: summarize analysis
  > results for multiple tools and samples in a single report. Bioinformatics.
  > 2016 Oct 1;32(19):3047-8. doi: 10.1093/bioinformatics/btw354.>

### Software packaging/containerisation tools

- [Anaconda](https://anaconda.com)

> Anaconda Software Distribution. Computer software. Vers. 2-2.4.0. Anaconda,
  > Nov. 2016. Web.

- [Bioconda](https://pubmed.ncbi.nlm.nih.gov/29967506/)

> Grüning B, Dale R, Sjödin A, Chapman BA, Rowe J, Tomkins-Tinch CH, Valieris
  > R, Köster J; Bioconda Team. Bioconda: sustainable and comprehensive
  > software distribution for the life sciences. Nat Methods. 2018>

- [BioContainers](https://pubmed.ncbi.nlm.nih.gov/28379341/)

> da Veiga Leprevost F, Grüning B, Aflitos SA, Röst HL, Uszkoreit J, Barsnes
  > H, Vaudel M, Moreno P, Gatto L, Weber J, Bai M, Jimenez RC, Sachsenberg T,
  > Pfeuffer J, Alvarez RV, Griss J, Nesvizhskii AI, Perez-R>

- [Docker](https://dl.acm.org/doi/10.5555/2600239.2600241)

- [Singularity](https://pubmed.ncbi.nlm.nih.gov/28494014/)

> Kurtzer GM, Sochat V, Bauer MW. Singularity: Scientific containers for
  > mobility of compute. PLoS One. 2017 May 11;12(5):e0177459. doi:
  > 10.1371/journal.pone.0177459. eCollection 2017. PubMed PMID: 28494014; >

- [EMU](https://github.com/treangenlab/emu)
  > Kristen D. Curry et al., “Emu: Species-Level Microbial Community Profiling
  > of Full-Length 16S RRNA Oxford Nanopore Sequencing Data,” Nature Methods,
  > June 30, 2022, 1–9, https://doi.org/10.1038/s41592-022-015>

## Citations

An extensive list of references for the tools used by the pipeline can be found
in the [`CITATIONS.md`](CITATIONS.md) file.

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