xldg 0.3.8

XLDataGraph is a library for crosslinking data analysis and visualization.

XLDataGraph

XLDataGraph is a feature-rich Python library for processing, filtering, comparing, and visualizing crosslinking mass spectrometry results. Built for advanced structural biology and proteomics workflows, it offers seamless integration of sequence, domain, and structural data, supporting publication-ready visualizations and network analyses.

Table of Contents

• Features
• Installation
• Supported File Types
• Quick Start Example
• API Overview
  • Data Loading & Filtering
  • Visualization
  • Structural Prediction
• Detailed Method Documentation
• Examples
• Contributing
• License
• Contact
• Project Status

Features

• Crosslink data: Imports MeroX .zhrm results and extracts crosslink site data.
• Metadata: Includes support for domain (.dmn), FASTA (.fasta), protein chain (.pcd), and structure (.cif, .pdb) files.
• Flexible filtering: By score, replica number, crosslink type (inter/intra/homeotypic).
• Data merging/replica handling: Directly support combining, blanking, and comparing datasets.
• Visualization suite:
  • Circos protein interaction plots with domain coloring.
  • Venn diagrams for cross-dataset overlap.
  • Gephi-compatible exports (AAI/PPI networks).
  • ChimeraX pseudo-bond distance constraints.
• Structural predictions: Fast CA-CA or advanced A* path-based 3D predictions for hypothetical crosslinks.
• Scriptable and extensible for custom workflows.

Installation

pip install xldg

Supported File Types

Extension	Description
.fasta	Protein sequences (Uniprot, Araport11, Custom)
.dmn	Protein domain annotation
.zhrm	MeroX result
.pcd	Protein-chain assignment descriptor
.cif/.pdb	Structure files (mmCIF or PDB format)

Quick Start Example

import os
from xldg.data import Path, MeroX, Domain, Fasta, CrossLink
from xldg.graphics import CircosConfig, Circos

cwd = './examples/files'
fasta = Fasta.load_data(os.path.join(cwd, 'example.fasta'), 'Custom')
domains = Domain.load_data(Path.list_given_type_files(cwd, 'dmn'))
crosslinks = MeroX.load_data(Path.list_given_type_files(cwd, 'zhrm'), 'DSBU')
combined = CrossLink.combine_all(crosslinks)
config = CircosConfig(fasta, domains)
circos = Circos(combined, config)
circos.save(os.path.join(cwd, 'results', 'circos_basic.svg'))

API Overview

Data Loading & Filtering

Loading Data

• Fasta.load_data(path, fasta_format, remove_parenthesis=False)
  • Load one or more FASTA files. See below for argument details.
• Domain.load_data(path)
  • Load one or more domain annotation files.
• MeroX.load_data(path, linker=None)
  • Import one or more .zhrm crosslink result files.
• ProteinChain.load_data(path)
  • Load a protein-chain map (.pcd).
• ProteinStructure.load_data(path)
  • Load a 3D structure file (.pdb or .cif).

Filtering and Dataset Manipulation

• CrossLink.filter_by_score(dataset, min_score=0, max_score=sys.maxsize)
  • Keep only crosslinks in the specified score window.
• CrossLink.filter_by_replica(dataset, min_replica=1, max_replica=sys.maxsize)
  • Filter crosslinks by replica count.
• CrossLink.remove_interprotein(dataset)
  • Remove all interprotein crosslinks.
• CrossLink.remove_intraprotein(dataset)
  • Remove all intraprotein crosslinks.
• CrossLink.remove_homeotypic(dataset)
  • Remove all homeotypic crosslinks (same residue/peptide on both sides).
• CrossLink.combine_all([datasets])
  • Merge given datasets as a single dataset.
• CrossLink.combine_replicas(dataset_list, n)
  • Combine every n datasets into a multi-replicate dataset group.
• CrossLink.blank_replica(dataset)
  • Set all replica counts to 1 for plotting/overlap analyses.

Visualization

• CircosConfig: Configures Circos protein plot visuals and filters.
• Circos: Generates and saves Circos plots.
• VennConfig: Configures Venn diagrams.
• Venn2/Venn3: 2- or 3-group overlap plots.
• CrossLinkDataset.export_ppis_for_gephi(folder, filename, pcd)
  • Exports protein-protein interaction graphs for Gephi visualization.
• CrossLinkDataset.export_aais_for_gephi(folder, filename, pcd)
  • Exports residue-residue networks.
• CrossLinkDataset.export_for_chimerax(...)
  • Exports .pb pseudo-bond files for ChimeraX (see below for expanded argument docs).

Structural Prediction

• ProteinStructureDataset.predict_crosslinks(...)
  • Predicts possible crosslinks based on atomic-residue coordinates; can use direct or sampled pathfinding.

Detailed Method Documentation

Data Loading and Filtering

Fasta.load_data(path, fasta_format, remove_parenthesis=False)

• path: str or list of str. Filepaths to FASTA files.
• fasta_format: str. "Uniprot", "Araport11", or "Custom" (header parser).
• remove_parenthesis: bool (optional). Remove parentheses content from headers.
• returns: FastaDataset.

Domain.load_data(path)

• path: str or list of str. Path(s) to .dmn file(s).
• returns: DomainDataset.

MeroX.load_data(path, linker=None)

• path: str or list of str. Path(s) to .zhrm zipped result file(s).
• linker: str (optional). Linker type, for annotation purposes.
• returns: One CrossLinkDataset for single file; list of datasets for multiple files.

CrossLink.filter_by_score(dataset, min_score=0, max_score=sys.maxsize)

• dataset: CrossLinkDataset or list. Input data.
• min_score / max_score: int. Score window.
• returns: Filtered dataset.

CrossLink.filter_by_replica(dataset, min_replica=1, max_replica=sys.maxsize)

• dataset: CrossLinkDataset or list. Input data.
• min_replica / max_replica: int. Allowed replica count window.
• returns: Filtered dataset.

CrossLink.remove_interprotein(dataset)

• dataset: CrossLinkDataset or list. Dataset(s) to filter.
• returns: Dataset with all crosslinks between distinct proteins removed (only intraprotein and homeotypic remain).[^2][^1]
• Effect: Used to focus on internal protein organization, e.g., in Circos plots.

CrossLink.remove_intraprotein(dataset)

• dataset: CrossLinkDataset or list. Dataset(s) to filter.
• returns: Dataset with all intra-protein crosslinks removed (only interprotein and homeotypic links remain).[^1][^2]
• Effect: Good for focusing on protein-protein interactions (interactions between different proteins).

CrossLink.remove_homeotypic(dataset)

• dataset: CrossLinkDataset or list. Dataset(s) to filter.
• returns: Dataset with all homeotypic crosslinks removed (where both sites correspond to the same residue or peptide).[^2][^1]
• Effect: Streamlines network/structural analyses by removing redundancy.

CrossLink.combine_all(datasets)

• datasets: list of CrossLinkDataset. All datasets to merge.
• returns: Combined CrossLinkDataset.

CrossLink.combine_replicas(dataset_list, n)

• dataset_list: List of datasets (e.g., by replicate).
• n: Number per group (e.g., n=3 for three-replicate overlays).
• returns: List of merged multi-replicate datasets.

CrossLink.blank_replica(dataset)

• dataset: CrossLinkDataset or list. All replica counts set to 1.
• returns: Dataset(s) for plotting or overlap comparison.

Visualization Methods

CircosConfig(fasta, domains=None, ...)

• fasta: FastaDataset.
• domains: DomainDataset (optional).
• legend, title: str (optional).
• figsize: (float, float), e.g. (9, 9) for image size.
• label_interval, space_between_sectors, font sizes, color overrides: See docstrings/defaults in code for advanced settings.
• returns: CircosConfig object.

Circos(crosslinks, config)

• crosslinks: CrossLinkDataset.
• config: CircosConfig.
• .save(path): Renders and saves Circos plot.

VennConfig(label_1, label_2, label_3=None, title=None, ...)

• label_1, label_2, label_3: str. Categories for Venn sets (up to 3).
• title: str (optional). Plot title and additional options for color and font size.
• returns: VennConfig.

Venn2(dataset1, dataset2, config)

• dataset1, dataset2: CrossLinkDataset. Sets to compare.
• config: VennConfig.
• .save(path): Save the Venn plot.

Venn3(dataset1, dataset2, dataset3, config)

• Add third dataset. Otherwise, usage as in Venn2.

CrossLinkDataset.export_ppis_for_gephi(folder, filename, pcd)

• folder: str. Output folder.
• filename: str. Output .gexf filename.
• pcd: ProteinChainDataset.
• returns: None. Writes file.

CrossLinkDataset.export_aais_for_gephi(folder, filename, pcd)

• Same as above, but for residue-residue/AAI level network.

CrossLinkDataset.export_for_chimerax(pcd, folder, filename, diameter=0.2, dashes=1, color_valid_distance='#48cae4', color_invalid_outsider='#d62828', protein_structure=None, min_distance=0, max_distance=sys.maxsize, atom_type='CA')

• pcd: ProteinChainDataset.
• folder: str.
• filename: str.
• diameter: float. Bond diameter for visualization.
• dashes: int. Style parameter for ChimeraX.
• color_valid_distance: str. For valid range links.
• color_invalid_outsider: str. For out-of-range links.
• protein_structure: ProteinStructureDataset (optional). Used for distance validation.
• min_distance/max_distance: float. Site distance boundaries.
• atom_type: str. (Usually "CA").
• returns: None. Writes one or more *.pb files for ChimeraX.

Structure-Based Crosslink Prediction

ProteinStructureDataset.predict_crosslinks(pcd, residues_1, residues_2, min_length=1.0, max_length=sys.maxsize, linker=None, atom_type='CA', direct_path=True, radius=1.925, node_multiplier=100, num_processes=1)

• pcd: ProteinChainDataset.
• residues_1/residues_2: str. Residue selectors, e.g. {K for N-term lysine, K for all lysines.
• min_length: float (angstrom). Minimum allowed CA-CA distance.
• max_length: float (angstrom). Maximum allowed distance.
• linker: str. Linker identifier.
• atom_type: str (default "CA"). On which atom dummy links will be modeled.
• direct_path: bool. If True, use direct CA-CA Euclidean distance; if False, use A* path sampling (models obstacles, slow).
• radius: float. Excluded-volume radius.
• node_multiplier: int. Controls sampling density if A* search used.
• num_processes: CPU count for parallel calculation (A* only).
• returns: CrossLinkDataset of predicted sites.

Examples

See examples/ directory for:

• Circos plotting
• Crosslink prediction and ChimeraX export
• Gephi (network) and Venn visualization
• Combined, advanced dataset filtering and merging

Contributing

Issues and pull requests welcome! See GitHub Issues.

License

This project is licensed under the GNU GPLv3.

Contact

• GitHub: @a-helix

Project Status

XLDataGraph is actively developed - please see the repository for the latest features, bugfixes, and documentation.