--- license: mit --- # PiperNET data Data for PiperNET, a multi-*omics* platform for elucidating the biosynthetic origin of plant specialized metabolites. It holds LC-MS metabolomics and RNA-Seq transcriptomics data from several *Piper* species and tissues, with biological replicates. Code and pipeline: [github.com/titodamiani/PiperNET](https://github.com/titodamiani/PiperNET). ## Download With the [`hf` command line tool](https://huggingface.co/docs/huggingface_hub/guides/cli): ```bash hf download titodamiani/PiperNET --repo-type dataset --local-dir data ``` To download one folder only, add `--include`, for example `--include "processed/*"`. To run the code on this data, follow the installation steps in the [code repository](https://github.com/titodamiani/PiperNET). ## Structure ``` data/ ├── README.md # this dataset card ├── raw/ │ ├── lcms/ │ │ ├── rawfiles/ # LC-MS raw files, mzML (140 files) │ │ └── metadata.tsv # sample metadata, read by MZmine │ └── rnaseq/piperNN/ # transXpress output, one folder per sample ID (13) │ ├── transcriptome.fasta # de novo assembly │ ├── transcriptome.pep # predicted proteins │ ├── transcriptome_expression_isoform.tsv │ ├── busco_report.txt │ └── annotations/ # Pfam, BLASTp, SignalP, TargetP, TMHMM ├── interim/ │ ├── lcms_mzmine/ # MZmine output: feature table, MS/MS spectra (.mgf), annotations, networks (.graphml) │ └── rnaseq_clstr/piperNN/ # CD-HIT clustered proteomes ├── external/ │ ├── molecular_networks/ │ │ └── gnps2/ # GNPS2 feature-based molecular networking results │ ├── sirius/ # SIRIUS results: CSI:FingerID structures, CANOPUS classes │ ├── orthogroups/ │ │ ├── sonicpd/ # SonicParanoid orthogroups and the genes in no orthogroup │ │ └── orthofinder/ # OrthoFinder orthogroups, MCL clusters, species tree and run log │ ├── speclibs/ # MS/MS spectral libraries for annotation in MZmine │ ├── known_enzymes/ # known enzymes table │ ├── customDB.csv # manually curated list of known LC-MS features, for targeted feature detection in MZmine │ ├── standardDB.csv # read by MZmine and the LC-MS data preparation │ └── novelty_scores.csv # preliminary └── processed/ ├── ftable_clean.csv # LC-MS feature table ├── ntable_clean.csv # GNPS2 node table, for Cytoscape ├── proteomes/piperNN/ # proteome.pep, proteome.csv, blastDB/ └── proteomes_all.csv # all proteomes with SonicParanoid and OrthoFinder orthogroups ``` ## IDs - `ftable_clean.csv` and `ntable_clean.csv`: `network_id` > 0 is a molecular network. A singleton feature is its own network, with `network_id` = -`feat_id`. - `proteomes_all.csv`: 4 columns per orthogroup tool, with the prefix `sonicpd_` (SonicParanoid) or `orthofinder_` (OrthoFinder): `_id`, `_size` (genes), `_sp_in_grp` (species), `_intersp` (species joined with `;`). - A singleton transcript is its own orthogroup, with a negative ID (-1, -2, ...). `sonicpd_id` starts at 1. `orthofinder_id` is the number in the OrthoFinder ID (`OG0000123` is 123), so it starts at 0. `scripts/README.md` in the [code repository](https://github.com/titodamiani/PiperNET) describes how each file is made.