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The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/)
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and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
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## v2.0.0 - 03/04/2025
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## v2.0.0 - 22/05/2025
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nf-core/coproid v2.0 is based on [nf-core](https://nf-co.re/) DSL2 template.
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This release is a complete rewrite of the original nf-core/coproid pipeline, originally written in Nextflow DSL1. It also includes new features, and/or updated tools.
Copy file name to clipboardExpand all lines: README.md
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It combines the analysis of putative host (ancient) DNA with a machine learning prediction of the faeces source based on microbiome taxonomic composition:
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1. First coproID performs comparative mapping of all reads agains two (or three) target genomes (genome1, genome2, and potentially genome3) and computes a host-DNA species ratio (NormalisedProportion).
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2. Then coproID performs metagenomic taxonomic profiling, and compares the obtained profiles to modern reference samples of the target species metagenomes. Using machine learning, coproID then estimates the host source from the metagenomic taxonomic composition (SourcepredictProportion).
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3. Finally, coproID combines A and B proportions to predict the likely host of the metagenomic sample.
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A. First coproID performs comparative mapping of all reads agains two (or three) target genomes (genome1, genome2, and potentially genome3) and computes a host-DNA species ratio (NormalisedProportion).
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B. Then coproID performs metagenomic taxonomic profiling, and compares the obtained profiles to modern reference samples of the target species metagenomes. Using machine learning, coproID then estimates the host source from the metagenomic taxonomic composition (SourcepredictProportion).
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C. Finally, coproID combines the A and B proportions to predict the likely host of the metagenomic sample.
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<!-- Workflow overview -->
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1. Fastp to remove adapters and low-complexity reads ([`fastp`](https://doi.org/10.1002/imt2.107))
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1. Mapping or reads to multiple reference genomes ([`Bowtie2`](https://bowtie-bio.sourceforge.net/bowtie2))
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1. Lowest Common Ancestor analysis to retain only genome specific reads ([`sam2lca`](github.com/maxibor/sam2lca))
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1. Ancient DNA damage estimation with [pyDamage](https://pydamage.readthedocs.io/en/latest/README.html) and [DamageProfiler](https://github.com/Integrative-Transcriptomics/DamageProfiler)
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1. Taxonomic profiling of unmapped reads ([`kraken2`](https://ccb.jhu.edu/software/kraken2/))
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1. Source predicting based on taxonic profiles ([`sourcepredict`](https://sourcepredict.readthedocs.io/))
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1. Combining host and microbial predictions to calculate overall proportions.
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