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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
├── interim/
│ ├── mzmine/ # MZmine output: feature table, MS/MS spectra (.mgf), annotations, networks (.graphml)
│ ├── transxpress/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
│ └── cdhit/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.
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