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<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
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<title>FRIdata</title>
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</head>
<body>
<header>
<h1>FRIdata</h1>
<p>High-performance protein structure data processing with Dask</p>
<div class="badges">
<img src="https://img.shields.io/badge/license-BSD--3--Clause-blue.svg?style=flat-square" alt="License">
<img src="https://img.shields.io/badge/python-3.11%20%7C%203.14-blue.svg?style=flat-square&logo=python" alt="Python">
<img src="https://github.com/Tomasz-Lab/FRIdata/actions/workflows/ci.yml/badge.svg" alt="CI">
<img src="https://img.shields.io/badge/impl-Dask-blue" alt="Dask">
</div>
<div style="margin-top:1.2rem;">
<a href="https://github.com/Tomasz-Lab/FRIdata" class="btn">View on GitHub</a>
<a href="https://github.com/Tomasz-Lab/FRIdata/issues" class="btn btn-outline">Issues</a>
</div>
</header>
<main>
<div class="cards">
<div class="card">
<h3>Purpose</h3>
<p>Generate sequences, coordinates, distograms, and embeddings from protein structures at scale.</p>
</div>
<div class="card">
<h3>Backend</h3>
<p>Built on <a href="https://docs.dask.org/">Dask</a> for distributed, parallel processing on CPU and GPU clusters.</p>
</div>
<div class="card">
<h3>HPC Ready</h3>
<p>Comes with SLURM scripts for PLGrid infrastructure. Supports AlphaFold DB (AFDB) structures.</p>
</div>
</div>
<details class="section" open>
<summary>Installation & Activation</summary>
<div class="section-body">
<ol>
<li>Clone the repository
<pre><code>git clone https://github.com/Tomasz-Lab/FRIdata.git
cd FRIdata</code></pre>
</li>
<li><a href="https://www.anaconda.com/docs/getting-started/miniconda/install">Install Miniconda</a>, then install mamba:
<pre><code># prioritize the conda-forge channel
conda config --add channels conda-forge
conda update -n base --all
conda install -n base mamba</code></pre>
</li>
<li>Create the environment (recommended). The setup script creates the conda
environment, installs the pip dependencies, and installs a PyTorch build
matched to your GPU driver:
<pre><code># default install
./scripts/setup_env.sh
# custom environment name
./scripts/setup_env.sh -n fridata_gpu_verify
# CPU-only systems
./scripts/setup_env.sh --cpu</code></pre>
</li>
<li>Activate the environment
<pre><code># shell type is one of: bash, cmd.exe, dash, fish, nu, posix, powershell, tcsh, xonsh, zsh
eval "$(mamba shell hook --shell <shell type>)"
mamba activate fridata_env</code></pre>
</li>
<li> (Optional) Run tests to verify the installation
<pre><code>pytest ./tests</code></pre>
</li>
</ol>
<p style="margin-top:1rem;"><strong>Manual installation</strong> — if you prefer to run the steps yourself:</p>
<pre><code>mamba env create -f fridata_env_conda.yml -n fridata_env
mamba run -n fridata_env python -m pip install -r requirements-fridata.txt
./scripts/install_pytorch.sh</code></pre>
<p>Pip dependencies live in <code>requirements-fridata.txt</code> rather than
<code>fridata_env_conda.yml</code> so environment creation works from read-only
repository checkouts.</p>
<p style="margin-top:1rem;"><strong>Troubleshooting</strong> — if you see
<code>Error opening for writing ".../mambaf..."</code> while creating the
environment, libmamba is trying to write a temporary pip requirements file next
to the environment YAML. Use <code>./scripts/setup_env.sh</code> instead, or
ensure the directory containing <code>fridata_env_conda.yml</code> is writable.</p>
</div>
</details>
<details class="section">
<summary>Running on AFDB Structures Locally</summary>
<div class="section-body">
<p>Requires a directory of AFDB structures and a text file listing AFDB IDs (one
per line, <code>\n</code> delimited). Assumes the installation steps above succeeded.</p>
<pre><code>FRIDATA_PATH="<repository path>"
AFDB_PATH="<AFDB structures directory path>"
IDS_PATH="<AFDB IDs file path>"
cd ${FRIDATA_PATH}
EMBEDDER_TYPE=esm2_t33_650M_UR50D
# (macOS only) fix for OpenMP multiple runtime error
export KMP_DUPLICATE_LIB_OK=TRUE
PYTHONPATH='.' python3 -u ${FRIDATA_PATH}/fridata.py \
generate_data \
-t sequences,coordinates,distograms,embeddings \
-d AFDB \
-c subset \
--version test \
-i ${IDS_PATH} \
--input-path ${AFDB_PATH} \
-e ${EMBEDDER_TYPE}</code></pre>
<p>For subset runs with <code>--input-path</code>, new datasets store canonical keys
as <code>{line_from_ids_file}_{chain}</code> (for example <code>A0A2K6V5L6_A</code>),
not the full AlphaFold CIF filename stem. The dataset's
<code>input_structures.idx</code> maps each canonical key to the source structure
filename. Older datasets created before this convention may still use long
AF-style keys.</p>
</div>
</details>
<details class="section">
<summary>Running as a CLI Tool</summary>
<div class="section-body">
<p>From the <code>FRIdata</code> directory, install it as a CLI tool:</p>
<pre><code>python3 -m pip install -e .
# now available as
fridata <...></code></pre>
<p>Use <code>ids_file</code> tokens (e.g. plain UniProt) plus chain as the canonical
dataset index keys.</p>
</div>
</details>
<details class="section">
<summary>Running on HPC (PLGrid / SLURM)</summary>
<div class="section-body">
<p>Running FRIdata on HPC differs between CPU and GPU nodes. These instructions are
valid for HPC hosted in PLGrid infrastructure; other infrastructures may require
additional adjustments.</p>
<p><strong>Prerequisites:</strong></p>
<ul>
<li>An active grant valid on the HPC</li>
<li>Loaded modules: <code>miniconda3</code> and <code>gcc</code></li>
<li>Mandatory environment variables (ideally set in <code>.bashrc</code>):
<ul>
<li><code>DEEPFRI_PATH</code> — parent directory of this repo</li>
<li><code>IDS_PATH</code> — text file with AFDB indexes listed</li>
<li><code>AFDB_PATH</code> — path to AFDB structures (may be an empty
directory — structures will be fetched there)</li>
<li><code>DATA_PATH</code> — parent directory of all generated output data</li>
</ul>
</li>
<li>Optional environment variables (with defaults):
<ul>
<li><code>COMMON_SLURM_PATH</code> — defaults to <code>$DEEPFRI_PATH/FRIdata/scripts/hpc/common_slurm.sh</code></li>
<li><code>LAUNCH_WORKER_SLURM_PATH</code> — defaults to <code>$DEEPFRI_PATH/FRIdata/scripts/hpc/launch_workers_slurm.sh</code></li>
<li><code>MEMORY_LIMIT</code> — memory limit per Dask worker, defaults to <code>288GiB</code></li>
<li><code>IP_INTERFACE</code> — network interface where Dask workers connect, defaults to <code>ens1f0</code></li>
<li><code>CONDA_ENV_PATH</code> — path to conda environment, defaults to <code>$DEEPFRI_PATH/conda_dev</code></li>
</ul>
</li>
</ul>
<p><strong>Preperation steps:</strong></p>
<pre><code># 1. Clone the repo
git clone https://github.com/Tomasz-Lab/FRIdata.git
cd FRIdata
# 2. Update run permissions
chmod u+x -R scripts/hpc/cpu
# 3. Initialize SLURM (add --cpu when running on a CPU cluster)
./scripts/hpc/initialize_slurm.sh <path to .conda> [--cpu]</code></pre>
<p>Then, schedule the sbatch script. Operations: <code>sequences</code>,
<code>coordinates</code>, <code>embeddings</code>, <code>distograms</code>.</p>
<pre><code># CPU nodes
sbatch --cpus-per-task=<cpus> --time=<HH:MM:SS> --nodes=<nodes> \
--account=<grant name> scripts/hpc/run_slurm.sh sequences,coordinates
# GPU nodes
sbatch --gres=gpu[:gpu-number] --time=<HH:MM:SS> --account=<grant name> \
--nodes=1 --partition=<partition name> --cpus-per-task=<cpus> \
scripts/hpc/run_slurm.sh embeddings</code></pre>
</div>
</details>
<details class="section">
<summary>Available Parameters</summary>
<div class="section-body">
<p>FRIdata is organized into sub-commands. The most common is <code>generate_data</code>,
which creates a dataset and generates the requested data types in one run.</p>
<h3 style="font-size:1rem;color:#e6edf3;margin:1.2rem 0 0.5rem;">Sub-commands</h3>
<div class="table-wrap">
<table>
<thead>
<tr><th>Command</th><th>Description</th></tr>
</thead>
<tbody>
<tr><td><code>generate_data</code></td><td>Create a dataset and generate sequences, coordinates, distograms and embeddings</td></tr>
<tr><td><code>create_dataset</code></td><td>Create a protein dataset only</td></tr>
<tr><td><code>generate_sequence</code></td><td>Generate sequences from a dataset</td></tr>
<tr><td><code>generate_distograms</code></td><td>Generate distograms from a dataset</td></tr>
<tr><td><code>generate_embeddings</code></td><td>Generate embeddings from a dataset</td></tr>
<tr><td><code>read_distograms</code></td><td>Read distograms from a dataset</td></tr>
<tr><td><code>read_pdbs</code></td><td>Read PDBs (print to terminal or extract with <code>--to_directory</code>)</td></tr>
<tr><td><code>verify_chains</code></td><td>Verify chains in a dataset</td></tr>
<tr><td><code>create_archive</code></td><td>Build one merged PDB <code>.zip</code> from the dataset index</td></tr>
<tr><td><code>create_dashboard</code></td><td>Export a single-file HTML report for dataset indexes</td></tr>
<tr><td><code>inspect_h5</code></td><td>Inspect an <code>.h5</code> file (tree, keys, structures, numeric dumps)</td></tr>
<tr><td><code>inspect_idx</code></td><td>Pretty-print an <code>.idx</code> (JSON) file</td></tr>
<tr><td><code>remove_dataset</code></td><td>Remove all traces of a dataset</td></tr>
</tbody>
</table>
</div>
<h3 style="font-size:1rem;color:#e6edf3;margin:1.6rem 0 0.5rem;">Dataset options</h3>
<div class="table-wrap">
<table>
<thead>
<tr><th>Flag</th><th>Description</th></tr>
</thead>
<tbody>
<tr><td><code>-p</code>, <code>--file-path</code></td><td>Existing dataset directory (with <code>dataset.json</code>) or path to <code>dataset.json</code></td></tr>
<tr><td><code>-d</code>, <code>--db</code></td><td>Database type (see choices below)</td></tr>
<tr><td><code>-c</code>, <code>--collection</code></td><td>Collection type (see choices below)</td></tr>
<tr><td><code>-t</code>, <code>--type</code></td><td>Comma-separated types to generate: <code>dataset</code>, <code>sequences</code>, <code>coordinates</code>, <code>distograms</code>, <code>embeddings</code>, or <code>all</code> (<code>generate_data</code> only)</td></tr>
<tr><td><code>-e</code>, <code>--embedder</code></td><td>Embedder type (see choices below)</td></tr>
<tr><td><code>-i</code>, <code>--ids</code></td><td>File with IDs used to create a subset</td></tr>
<tr><td><code>-s</code>, <code>--seqres</code></td><td>FASTA file to use as the sequence source</td></tr>
<tr><td><code>--input-path</code></td><td>Input directory or archive (zip/tar.gz) of protein files (pdb/cif)</td></tr>
<tr><td><code>--archive</code></td><td>Path to a tar.gz archive containing structure files</td></tr>
<tr><td><code>--proteome</code></td><td>Precise proteome of an AFDB <code>part</code> dataset</td></tr>
<tr><td><code>--version</code></td><td>String to differentiate datasets (default: current date)</td></tr>
<tr><td><code>-b</code>, <code>--batch-size</code></td><td>Batch size</td></tr>
<tr><td><code>-o</code>, <code>--overwrite</code></td><td>Overwrite existing files (default: false)</td></tr>
<tr><td><code>--binary</code></td><td>Download binary CIF in the PDB database</td></tr>
<tr><td><code>--slurm</code></td><td>Use the SLURM job scheduler</td></tr>
<tr><td><code>-v</code>, <code>--verbose</code></td><td>Enable verbose logging</td></tr>
<tr><td><code>--log-file</code></td><td>Path to a log file for file logging</td></tr>
<tr><td><code>--config</code></td><td>Path to a config JSON file (default: <code>./config.json</code>)</td></tr>
</tbody>
</table>
</div>
<h3 style="font-size:1rem;color:#e6edf3;margin:1.6rem 0 0.5rem;">Choices</h3>
<div class="table-wrap">
<table>
<thead>
<tr><th>Option</th><th>Accepted values</th></tr>
</thead>
<tbody>
<tr><td><code>-d</code>, <code>--db</code></td><td><code>PDB</code>, <code>AFDB</code>, <code>ESMatlas</code>, <code>other</code></td></tr>
<tr><td><code>-c</code>, <code>--collection</code></td><td><code>all</code>, <code>clust</code>, <code>part</code>, <code>subset</code></td></tr>
<tr><td><code>-e</code>, <code>--embedder</code></td><td><code>esm2_t30_150M_UR50D</code>, <code>esm2_t33_650M_UR50D</code>, <code>esmc_300m</code>, <code>esmc_600m</code>, <code>gLM2_150M</code>, <code>gLM2_650M</code></td></tr>
</tbody>
</table>
</div>
</div>
</details>
<details class="section">
<summary>Example usage</summary>
<div class="section-body">
<p>Each sub-command below shows its <code>--help</code> output. Run
<code>fridata <subcommand> --help</code> to reproduce it.</p>
<details class="subcmd">
<summary>generate_data</summary>
<pre><code>usage: fridata generate_data [-h] [--slurm] [-p FILE_PATH] [-d name] [-c name]
[-t [name]] [--proteome [name]]
[--version VERSION] [-i IDS] [-s SEQRES] [-o]
[-b BATCH_SIZE] [--binary]
[--input-path INPUT_PATH] [--archive ARCHIVE]
[-v] [-e name]
options:
-h, --help show this help message and exit
--slurm Use SLURM job scheduler
-p FILE_PATH, --file-path FILE_PATH
Existing dataset directory (with dataset.json) or path
to dataset.json
-d name, --db name Database Types: PDB AFDB ESMatlas other
-c name, --collection name
Collection Types: all clust part subset
-t [name], --type [name]
Comma-separated types to generate: dataset, sequences,
coordinates, distograms, embeddings; or 'all'. For
generate_data only; ignored by create_dataset.
--proteome [name] Precise proteome of AFDB part dataset
--version VERSION String to differentiate datasets; default: current
date
-i IDS, --ids IDS File with ids to create subset
-s SEQRES, --seqres SEQRES
fasta file to use as sequence source
-o, --overwrite Should overwrite existing files? Default - false
-b BATCH_SIZE, --batch-size BATCH_SIZE
--binary Download binary CIF in PDB db
--input-path INPUT_PATH
Path to input directory or archive (zip/tar.gz) with
protein files (pdb/cif)
--archive ARCHIVE Path to tar.gz archive containing structure files
-v, --verbose Enable verbose logging mode
-e name, --embedder name
Embedder Types: esm2_t30_150M_UR50D
esm2_t33_650M_UR50D esmc_300m esmc_600m gLM2_150M
gLM2_650M</code></pre>
</details>
<details class="subcmd">
<summary>create_dataset</summary>
<pre><code>usage: fridata create_dataset [-h] [--slurm] -d name -c name [-t [name]]
[--proteome [name]] [--version VERSION] [-i IDS]
[-s SEQRES] [-o] [-b BATCH_SIZE] [--binary]
[--input-path INPUT_PATH] [--archive ARCHIVE]
[-v] [-e name]
options:
-h, --help show this help message and exit
--slurm Use SLURM job scheduler
-d name, --db name Database Types: PDB AFDB ESMatlas other
-c name, --collection name
Collection Types: all clust part subset
-t [name], --type [name]
Comma-separated types to generate: dataset, sequences,
coordinates, distograms, embeddings; or 'all'. For
generate_data only; ignored by create_dataset.
--proteome [name] Precise proteome of AFDB part dataset
--version VERSION String to differentiate datasets; default: current
date
-i IDS, --ids IDS File with ids to create subset
-s SEQRES, --seqres SEQRES
fasta file to use as sequence source
-o, --overwrite Should overwrite existing files? Default - false
-b BATCH_SIZE, --batch-size BATCH_SIZE
--binary Download binary CIF in PDB db
--input-path INPUT_PATH
Path to input directory or archive (zip/tar.gz) with
protein files (pdb/cif)
--archive ARCHIVE Path to tar.gz archive containing structure files
-v, --verbose Enable verbose logging mode
-e name, --embedder name
Embedder Types: esm2_t30_150M_UR50D
esm2_t33_650M_UR50D esmc_300m esmc_600m gLM2_150M
gLM2_650M</code></pre>
</details>
<details class="subcmd">
<summary>generate_sequence</summary>
<pre><code>usage: fridata generate_sequence [-h] [--slurm] -p FILE_PATH [-v]
[--log-file LOG_FILE] [--ca_mask]
[--no_substitution]
options:
-h, --help show this help message and exit
--slurm Use SLURM job scheduler
-p FILE_PATH, --file-path FILE_PATH
-v, --verbose Enable verbose logging
--log-file LOG_FILE Path to log file for file logging
--ca_mask Require a carbon alpha atom to include an amino acid
in a sequence
--no_substitution Don't substitute non standard amino acids</code></pre>
</details>
<details class="subcmd">
<summary>generate_distograms</summary>
<pre><code>usage: fridata generate_distograms [-h] [--slurm] -p FILE_PATH [-v]
[--log-file LOG_FILE]
options:
-h, --help show this help message and exit
--slurm Use SLURM job scheduler
-p FILE_PATH, --file-path FILE_PATH
-v, --verbose Enable verbose logging
--log-file LOG_FILE Path to log file for file logging</code></pre>
</details>
<details class="subcmd">
<summary>generate_embeddings</summary>
<pre><code>usage: fridata generate_embeddings [-h] [--slurm] -p FILE_PATH [-v]
[--log-file LOG_FILE] -e name
options:
-h, --help show this help message and exit
--slurm Use SLURM job scheduler
-p FILE_PATH, --file-path FILE_PATH
-v, --verbose Enable verbose logging
--log-file LOG_FILE Path to log file for file logging
-e name, --embedder name
Embedder Types: esm2_t30_150M_UR50D
esm2_t33_650M_UR50D esmc_300m esmc_600m gLM2_150M
gLM2_650M</code></pre>
</details>
<details class="subcmd">
<summary>read_distograms</summary>
<pre><code>usage: fridata read_distograms [-h] [--slurm] -p FILE_PATH [-v]
[--log-file LOG_FILE]
options:
-h, --help show this help message and exit
--slurm Use SLURM job scheduler
-p FILE_PATH, --file-path FILE_PATH
-v, --verbose Enable verbose logging
--log-file LOG_FILE Path to log file for file logging</code></pre>
</details>
<details class="subcmd">
<summary>read_pdbs</summary>
<pre><code>usage: fridata read_pdbs [-h] [--print] [--to_directory TO_DIRECTORY] [-i IDS]
[--slurm] -p FILE_PATH [-v] [--log-file LOG_FILE]
options:
-h, --help show this help message and exit
--print Print PDB files to the terminal
--to_directory TO_DIRECTORY
Extract PDB files to the provided directory
-i IDS, --ids IDS File with ids to extract
--slurm Use SLURM job scheduler
-p FILE_PATH, --file-path FILE_PATH
-v, --verbose Enable verbose logging
--log-file LOG_FILE Path to log file for file logging</code></pre>
</details>
<details class="subcmd">
<summary>verify_chains</summary>
<pre><code>usage: fridata verify_chains [-h] [--slurm] -p FILE_PATH [-v]
[--log-file LOG_FILE]
options:
-h, --help show this help message and exit
--slurm Use SLURM job scheduler
-p FILE_PATH, --file-path FILE_PATH
-v, --verbose Enable verbose logging
--log-file LOG_FILE Path to log file for file logging</code></pre>
</details>
<details class="subcmd">
<summary>create_archive</summary>
<pre><code>usage: fridata create_archive [-h] [--keep-shard-zips] [--slurm] -p FILE_PATH
[-v] [--log-file LOG_FILE]
options:
-h, --help show this help message and exit
--keep-shard-zips Keep per-shard zip files under _staging/ after merge
(default: remove staging)
--slurm Use SLURM job scheduler
-p FILE_PATH, --file-path FILE_PATH
-v, --verbose Enable verbose logging
--log-file LOG_FILE Path to log file for file logging
Working directory: pass an absolute -p/--file-path to the dataset directory (the folder containing dataset.json), or cd to <data_path>/datasets first if you want to use a short folder name.
Invocation: run `fridata create_archive ...`, or `python -m fridata create_archive ...` if the console script is not on PATH.</code></pre>
</details>
<details class="subcmd">
<summary>create_dashboard</summary>
<pre><code>usage: fridata create_dashboard [-h] [--root ROOT] [--index-types INDEX_TYPES]
[--output-dir OUTPUT_DIR]
dataset
positional arguments:
dataset Dataset: filesystem path (directory or dataset.json),
slug (folder suffix after --), or full folder name
under --root when not an existing path
options:
-h, --help show this help message and exit
--root ROOT Override datasets root (default: <data_path>/datasets)
--index-types INDEX_TYPES
Comma-separated index types
(dataset,sequences,coordinates,embeddings,distograms)
or 'all'
--output-dir OUTPUT_DIR
Output directory for reports (default:
<repo_root>/reports)</code></pre>
</details>
<details class="subcmd">
<summary>inspect_h5</summary>
<pre><code>usage: fridata inspect_h5 [-h]
[--mode {preview,structures,keys,distograms,coordinates,embeddings}]
[--name KEYS] [--save [FILEPATH]]
file
positional arguments:
file Path to h5 file
options:
-h, --help show this help message and exit
--mode {preview,structures,keys,distograms,coordinates,embeddings}
preview: H5 tree; keys: id list; structures: full PDB
text (files group); distograms|coordinates|embeddings:
numeric preview (or full dump with --name)
--name KEYS Comma-separated protein keys. Only with --mode
structures|distograms|coordinates|embeddings. For
numeric modes, emits a full array dump. Use inspect_h5
--mode keys to list keys.
--save [FILEPATH] Write output to a file instead of vi. Omit FILEPATH to
write a persistent temp file and print its path.</code></pre>
</details>
<details class="subcmd">
<summary>inspect_idx</summary>
<pre><code>usage: fridata inspect_idx [-h] file
positional arguments:
file Path to idx file
options:
-h, --help show this help message and exit</code></pre>
</details>
<details class="subcmd">
<summary>remove_dataset</summary>
<pre><code>usage: fridata remove_dataset [-h] name
positional arguments:
name Dataset name (e.g. AFDB-subset--20250609_1333)
options:
-h, --help show this help message and exit</code></pre>
</details>
</div>
</details>
</main>
<footer>
FRIdata — <a href="https://github.com/Tomasz-Lab/FRIdata/blob/main/LICENSE">BSD-3-Clause License</a>
— <a href="https://github.com/Tomasz-Lab">Tomasz-Lab</a>
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