Dataset Viewer
The dataset viewer is not available for this split.
Cannot extract the features (columns) for the split 'train' of the config 'default' of the dataset.
Error code: FeaturesError
Exception: ParserError
Message: Error tokenizing data. C error: Expected 1 fields in line 17, saw 2
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 244, in compute_first_rows_from_streaming_response
iterable_dataset = iterable_dataset._resolve_features()
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 4408, in _resolve_features
features = _infer_features_from_batch(self.with_format(None)._head())
~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2679, in _head
return next(iter(self.iter(batch_size=n)))
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2861, in iter
for key, pa_table in ex_iterable.iter_arrow():
~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2395, in _iter_arrow
yield from self.ex_iterable._iter_arrow()
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 419, in _iter_arrow
for key, pa_table in self.generate_tables_fn(**gen_kwags):
~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/csv/csv.py", line 198, in _generate_tables
for batch_idx, df in enumerate(csv_file_reader):
~~~~~~~~~^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/pandas/io/parsers/readers.py", line 1843, in __next__
return self.get_chunk()
~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/pandas/io/parsers/readers.py", line 1985, in get_chunk
return self.read(nrows=size)
~~~~~~~~~^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/pandas/io/parsers/readers.py", line 1923, in read
) = self._engine.read( # type: ignore[attr-defined]
~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
nrows
^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/pandas/io/parsers/c_parser_wrapper.py", line 234, in read
chunks = self._reader.read_low_memory(nrows)
File "pandas/_libs/parsers.pyx", line 850, in pandas._libs.parsers.TextReader.read_low_memory
File "pandas/_libs/parsers.pyx", line 905, in pandas._libs.parsers.TextReader._read_rows
File "pandas/_libs/parsers.pyx", line 874, in pandas._libs.parsers.TextReader._tokenize_rows
File "pandas/_libs/parsers.pyx", line 891, in pandas._libs.parsers.TextReader._check_tokenize_status
File "pandas/_libs/parsers.pyx", line 2061, in pandas._libs.parsers.raise_parser_error
pandas.errors.ParserError: Error tokenizing data. C error: Expected 1 fields in line 17, saw 2Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
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.
Download
With the hf command line tool:
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.
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
│ ├── 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 orthogroups
└── scoring/ # input arrays for network-orthogroup scoring (.npy)
scripts/README.md in the code repository describes how each file is made.
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