https://github.com/maxibor/adnamap
aDNA mapping to multiple genomes
https://github.com/maxibor/adnamap
Last synced: 5 months ago
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aDNA mapping to multiple genomes
- Host: GitHub
- URL: https://github.com/maxibor/adnamap
- Owner: maxibor
- License: mit
- Created: 2022-06-13T21:02:17.000Z (almost 4 years ago)
- Default Branch: master
- Last Pushed: 2025-02-04T15:38:46.000Z (over 1 year ago)
- Last Synced: 2025-12-17T09:42:33.616Z (6 months ago)
- Language: Nextflow
- Size: 30 MB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- Contributing: .github/CONTRIBUTING.md
- License: LICENSE
- Code of conduct: CODE_OF_CONDUCT.md
- Citation: CITATIONS.md
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README
# aDNAMap
**adnamap** is a bioinformatics best-practice analysis pipeline for aDNA mapping to mulitple genomes.
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. Where possible, these processes have been submitted to and installed from [nf-core/modules](https://github.com/nf-core/modules) in order to make them available to all nf-core pipelines, and to everyone within the Nextflow community!
On release, automated continuous integration tests run the pipeline on a full-sized dataset on the AWS cloud infrastructure. This ensures that the pipeline runs on AWS, has sensible resource allocation defaults set to run on real-world datasets, and permits the persistent storage of results to benchmark between pipeline releases and other analysis sources. The results obtained from the full-sized test can be viewed on the [nf-core website](https://nf-co.re/adnamap/results).
## Pipeline summary
1. Read QC ([`FastQC`](https://www.bioinformatics.babraham.ac.uk/projects/fastqc/))
2. Present QC for raw reads ([`MultiQC`](http://multiqc.info/))
## Quick Start
1. Install [`Nextflow`](https://www.nextflow.io/docs/latest/getstarted.html#installation) (`>=21.10.3`)
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. Download the pipeline and test it on a minimal dataset with a single command:
```console
nextflow run nf-core/adnamap -profile test,YOURPROFILE --outdir
```
Note that some form of configuration will be needed so that Nextflow knows how to fetch the required software. This is usually done in the form of a config profile (`YOURPROFILE` in the example command above). You can chain multiple config profiles in a comma-separated string.
> - The pipeline comes with config profiles called `docker`, `singularity`, `podman`, `shifter`, `charliecloud` and `conda` which instruct the pipeline to use the named tool for software management. For example, `-profile test,docker`.
> - Please check [nf-core/configs](https://github.com/nf-core/configs#documentation) to see if a custom config file to run nf-core pipelines already exists for your Institute. If so, you can simply use `-profile ` in your command. This will enable either `docker` or `singularity` and set the appropriate execution settings for your local compute environment.
> - If you are using `singularity`, please use the [`nf-core download`](https://nf-co.re/tools/#downloading-pipelines-for-offline-use) command to download images first, before running the pipeline. Setting the [`NXF_SINGULARITY_CACHEDIR` or `singularity.cacheDir`](https://www.nextflow.io/docs/latest/singularity.html?#singularity-docker-hub) Nextflow options enables you to store and re-use the images from a central location for future pipeline runs.
> - If you are using `conda`, it is highly recommended to use the [`NXF_CONDA_CACHEDIR` or `conda.cacheDir`](https://www.nextflow.io/docs/latest/conda.html) settings to store the environments in a central location for future pipeline runs.
4. Start running your own analysis!
```console
nextflow run nf-core/adnamap --input samplesheet.csv --genomes genome_sheet.csv --outdir -profile
```
## Documentation
The adnamap pipeline comes with documentation about the pipeline [usage](docs/usage), [parameters](docs/parameters) and [output](docs/output).
## Credits
nf-core/adnamap was originally written by Maxime Borry.
## Pipeline workflow
```mermaid
flowchart TD
subgraph fastq_process[FastQ preprocessing]
fastq{FastQ file}
fastqc_before[FastQC before]
fastp["fastp: \n Adapter and Quality trimming + merging + deduplication"]
fastqc_after[FastQC after]
fastq --> fastqc_before
fastq --> fastp
fastp -- Trimmed fastq --> fastqc_after
end
subgraph fastq_preproprecessing[FastA preprocessing]
fasta{Genome FastA file}
faidx[Samtools faidx]
fasta --compressed-->gunzip
gunzip-->bowtie2_build
bowtie2_build[Bowtie2-build]
fasta--not compressed--> bowtie2_build
gunzip-->faidx
fasta--not compressed-->faidx
end
subgraph alignment[Alignment]
bowtie2_align["Bowtie2 align subworkflow"]
bowtie2_build --Bowtie 2 index--> bowtie2_align
fastp --Trimmed fastq--> bowtie2_align
end
subgraph lca[LCA]
bowtie2_align --samtools merge--> merged_BAM["Merged BAM per sample"]
merged_BAM --sam2lca--> rank_BAM["taxon rank specific BAM"]
end
subgraph alignment_post[Alignment post_processing]
qualimap[Alignment stats reporting]
damageprofiler[DamageProfiler: aDNA stats]
fasta--decompressed-->damageprofiler
gunzip-->damageprofiler
rank_BAM--BAM+index-->damageprofiler
rank_BAM--BAM+index-->qualimap
end
subgraph variant_calling[Variant calling]
snpAD["snpAD: ancient DNA damage aware genotyper"]
freebayes["Freebayes: genotyper"]
rank_BAM--BAM+index-->snpAD
rank_BAM--BAM+index-->freebayes
fasta--decompressed-->snpAD
gunzip-->freebayes
faidx-->freebayes
fasta--decompressed-->snpAD
gunzip-->freebayes
faidx-->snpAD
vcf{VCF}
freebayes --> vcf
vcf-- bcftools consensus -->cons_fa["Consensus genome fasta"]
end
```
## Contributions and Support
If you would like to contribute to this pipeline, please see the [contributing guidelines](.github/CONTRIBUTING.md).
## Citations
An extensive list of references for the tools used by the pipeline can be found in the [`CITATIONS.md`](CITATIONS.md) file.
This pipeline integrates code templates and was made with tools from the [`nf-core` community](https://nf-co.re/). More in their publication below:
> **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](https://dx.doi.org/10.1038/s41587-020-0439-x).