Reverse Dependencies of igraph

The following projects have a declared dependency on igraph:

• aideml — Autonomous AI for Data Science and Machine Learning
• aif360 — IBM AI Fairness 360
• aif360-fork2 — IBM AI Fairness 360
• aksara — Aksara is an Indonesian NLP tool that conforms to the Universal Dependencies (UD) v2
• anomalous — Server anomaly detection.
• atopile — A toolchain bringing the best of software development to the real-world!
• avici — Amortized Inference for Causal Structure Learning
• Bering — Bering: Transfer Learning of Cell Segmentation and Annotation for Spatial Omics
• bgenv — no summary
• biocomet — A brief description of the biocomet package
• bipartitepandas — Python tools for bipartite labor data
• bn2vec — Boolean Network To Vector
• brokerscore — Meso level network measure pbroker score as defined by Paquet-Clouston and Bouchard
• celescope — Single Cell Analysis Pipelines
• cell2sentence — cell2sentence: create cell sentences from sequencing data
• cellrank — CellRank: dynamics from multi-view single-cell data
• cglearn — cglearn is a Python library that aims to spark probabilistic reasoning and analysis via chain graphs.
• cglearnlatest — Description of your package
• cglearntemp — cglearn is a Python library that aims to spark probabilistic reasoning and analysis via chain graphs.
• clairvoyance2 — clairvoyance2: a Unified Toolkit for Medical Time Series
• clustree — Visualize relationship between clusterings at different resolutions
• cnmfsns — cNMF Solution Network Space
• Cobra2D — A package for building time- and space-resolved metabolic models.
• code-evaluation — A module to bundle xml using xpath
• contextualized-ml — A statistical machine learning toolbox for estimating models, distributions, and functions with sample-specific parameters.
• cso-classifier — A light-weight Python app for classifying scientific documents with the topics from the Computer Science Ontology (https://cso.kmi.open.ac.uk/home).
• cuTradeNet — GPU-Accelerated Kinetic Wealth Exchange Models on Complex Networks
• cwas — Category-wide association study (CWAS). This is a data analytic tool to perform stringent association tests to find non-coding loci associated with autism spectrum disorder (ASD).
• daggen — A Python Wrapper for the daggen tool proposed by Frederic Suter
• dagma — Implementation of the DAGMA algorithm
• dagsim — A framework and specification language for simulating data based on user-defined graphical models
• DBRetina — DBRetina Python Package
• DeepTalk-ST — Cell-cell communication prediction for ST data
• deepvelo — Deep Velocity
• dibs-lib — DiBS: Differentiable Bayesian Structure Learning
• dijkstra-conda — A test project
• drive-ibd — cli tool to identify networks of individuals who share IBD segments overlapping loci of interest
• dspin — Regulatory network models from single-cell perturbation profiling
• dumbo-asp — Utilities for Answer Set Programming
• dynamo-release — Mapping Vector Field of Single Cells
• EA-Toolkit — Some Utils for Entity Alignment and GCN.
• ecoscope — Standard Analytical Reporting Framework for Conservation
• edgeseraser — A short description of the project
• epiaster — ASTER: accurate estimation of cell-type numbers in single-cell chromatin accessibility data
• epicarousel — EpiCarousel: memory- and time-efficient identification of metacells for atlas-level single-cell chromatin accessibility data
• er-evaluation — An end-to-end evaluation framework for entity resolution systems.
• explorerscript — ExplorerScript and SSBScript: Script languages for decompiled SSB (Pokémon Mystery Dungeon Explorers of Sky)
• FactorioSolver — Tools to solve the Factorio problem
• filip — [FI]WARE [Li]brary for [P]ython
• gene-trajectory — Compute gene trajectories
• genomap — Genomap converts tabular gene expression data into spatially meaningful images.
• genopyc — no summary
• georouting — Geo routing for Python users
• giotto-tda — Toolbox for Machine Learning using Topological Data Analysis.
• giotto-tda-nightly — Toolbox for Machine Learning using Topological Data Analysis.
• glhf — Good luck, have fun! A generals.io bot framework.
• glhmm — Gaussian Linear Hidden Markov Model
• GNNSubNet — Disease Subnetwork Detection with Explainable Graph Neural Networks
• graphbin — graphbin: Refined binning of metagenomic contigs using assembly graphs.
• graphcol — no summary
• graphcoltests — no summary
• graphcompass — Spatial metrics for differential analyses of cell organization across conditions
• graphistry — A visual graph analytics library for extracting, transforming, displaying, and sharing big graphs with end-to-end GPU acceleration
• graphlot — no summary
• GSG — no summary
• hypernetx — HyperNetX is a Python library for the creation and study of hypergraphs.
• ibdcluster — A CLI tool to help identify ibd sharing within networks across a locus of interest at biobank scale and then test for phenotypic enrichment within these networks.
• icat-sc — Identify cell states across treatments in single-cell RNA sequencing experiments
• influential — Identification and Classification of the Most Influential Nodes
• ireiat — Intermodal Routing and Environmental Impact Analysis Tool
• iscan-dag — Implementation of the iSCAN algorithm for detecting distribution shifts
• keypartx — A Graph-based Perception(Text) Representation
• kglab — A simple abstraction layer in Python for building knowledge graphs
• leidenalg — Leiden is a general algorithm for methods of community detection in large networks.
• lightning-thunder — Lightning Thunder project.
• lingpy — Python library for quantitative tasks in historical linguistics
• linguado — Linguado is a tool which compares the AST of two or more files
• louvain — louvain is a general algorithm for methods of community detection in large networks.
• louvainvsleiden — For sampling the louvain method and leiden method on different networks
• manyworlds — Organize BDD scenarios as hierarchical trees for more concise and expressive feature files
• mappymatch — Package for mapmatching.
• markovdecisionprocess — Markov Decision Process
• maxfuse — Cross-modality matching of single cells via iterative fuzzy smoothed embedding
• mesh2vec — mesh2vec
• metacoag — MetaCoAG: Binning Metagenomic Contigs via Composition, Coverage and Assembly Graphs
• mipathway — MIPath pathway analysis method
• MIPMLP — no summary
• modisco-lite — Transcription Factor MOtif Discovery from Importance SCOres - lite
• modularitypruning — Pruning tool to identify small subsets of network partitions that are significant from the perspective of stochastic block model inference.
• mosaic-clustering — Correlation based feature selection for MD data
• mosaicmpi — mosaicMPI: Mosaic Multi-resolution Program Integration
• MuLP — Python implementation of the Multilayer Personalized Page Rank algorithm
• navis — Neuron Analysis and Visualization library
• NEExT — Unsupervised Graph Analysis Framework.
• netket — Netket : Machine Learning toolbox for many-body quantum systems.
• nngt — Python package to generate and study graphs and detailed
• omicverse — OmicVerse: A single pipeline for exploring the entire transcriptome universe
• omniplot — To draw scientific plots easily
• omnipose — cell segmentation algorithm improving on the Cellpose framework
• open-darts — Delft Advanced Research Terra Simulator