Shanghai Dogs

Support repository for the study

Capturing global pet dog gut microbial diversity and hundreds of near-finished bacterial genomes by using long-read metagenomics in a Shanghai cohort by Anna Cuscó, Yiqian Duan, Fernando Gil, Alexei Chklovski, Nithya Kruthi, Shaojun Pan, Sofia Forslund, Susanne Lau, Ulrike Löber, Xing-Ming Zhao, and Luis Pedro Coelho (bioRxiv PREPRINT 2025)

See also the MAG collection at the Shanghai MAG collection website.

Directories

• data/ (not on git): raw data and results to upload (to ENA/Zenodo/...)
• data/ShanghaiDogsMetadata (on git): dog-associated information
• external-data/code (on git): code to download external data
• external-data/data (not on git): external data downloaded
• intermediate-outputs/ (not on git): results of preprocessing for convenience
• resource_generation/: scripts to generate assemblies, MAGs, annotations, ...
• analysis/

Data

1. ShanghaiDogsFastQ/: Raw FastQs from service provider
2. ShanghaiDogsMetadata/: Metadata for the samples
3. ShanghaiDogsAssemblies/: Polished assemblies
4. ShanghaiDogsMAGs/: MAGs (FASTA files)
5. ShanghaiDogsMAGAnnotations/: Annotations of MAGs, including EMapper and Barrnap subdirectories
6. ShanghaiDogsMAGsTables/: Tables with MAGs, including singleM and mOTU subdirectories
7. ShanghaiDogs_OtherResources/: Other resources, including gene and smORF catalogues (and their respective annotations)

External data

1. GMGC MAGs
2. singleM profiles from sandpiper (inside dog_microbiome_archive_otu_tables subdirectory)
3. mOTU profiles for canid/felid

Preprocessed

1. Quality controled FQs
2. Not fully polished assemblies
3. singleM/mOTU output tables

Copyright & License

This is made available under the MIT License. See LICENSE for details.

This code is intended as Extended Methods code for the above-cited manuscript. It is not designed for widespread use, but intended to ensure reproducibility and provide documentation. However, please cite the manuscript if you use this code or data. If relevant, please also cite any underlying tools and datasets used, as described in the manuscript.