Reverse Dependencies of anndata
The following projects have a declared dependency on anndata:
- Orange3-SingleCell — Add-on for bioinformatics analysis of single cell data.
- orthomap — extract orthomap from OrthoFinder output for query species
- palantir — Palantir for modeling continuous cell state and cell fate choices in single cell data
- pandasaurus-cxg — Ontology enrichment tool for CxG standard AnnData files.
- paste2 — Probabilistic Alignment of Spatial Transcriptomics Experiments v.2
- pathml — Tools for computational pathology
- pcdl — physicell data loader (pcdl) provides a platform independent, python3 based, pip installable interface to load output, generated with the PhysiCell agent based modeling framework, into python3.
- pegasusio — Pegasusio is a Python package for reading / writing single-cell genomics data
- pegasuspy — Pegasus is a Python package for analyzing sc/snRNA-seq data of millions of cells
- perturb-tools — perturb-tools - Analysis Framework for Pooled CRISPR Genome Editing Screens.
- pertvi — deep mechanistic modeling of single-cell atlas using variational inference
- phate — PHATE
- phn — phn
- phylics — Single-cell CNV data analysis toolkit
- pianno — Pattern Image ANNOtation
- picturedrocks — Single Cell RNA Sequencing Marker Selection Package
- pixelgen-pixelator — A command-line tool and library to process and analyze sequencing data from Molecular Pixelation (MPX) assays.
- planktonspace — A point process analysis package
- plotplot — Drag and drop plotting, data selection, and filtering
- popari — Popari: a probabilistic graphical model for integrated spatial transcriptomics analysis
- popv — Consensus prediction of cell type labels with popV
- psite-recommender — RS for Proteomics
- py-outrider — Python backend package for OUTRIDER2 R package
- pyaging — A Python-based compendium of GPU-optimized aging clocks.
- pyBCS-bioturing — Create BioTuring Compressed Study (bcs) file
- pycallingcards — "Calling cards data analysis in Python."
- pychromvar — A python package for chromVAR
- pydeseq2 — A python implementation of DESeq2.
- pyLemur — A Python implementation of the LEMUR algorithm for analyzing multi-condition single-cell RNA-seq data.
- pyliger — The Python version of LIGER package.
- pymmdb — MMDB interface for python
- pypsupertime — PyPsupertime
- pyrovelocity — A multivariate RNA Velocity model to estimate future cell states with uncertainty using probabilistic modeling with pyro.
- pyslingshot — Python implementation of the Slingshot pseudotime algorithm
- pytometry — Pytometry is a Python package for flow and mass cytometry analysis.
- pyturbseq — no summary
- pyvdj — V(D)J sequencing data analysis
- quilt3 — Quilt: where data comes together
- rapids-singlecell — running single cell analysis on Nvidia GPUs
- readfcs — Parse fcs files into AnnData.
- Sagittarius-api-test — no summary
- salamander-learn — Salamander is a non-negative matrix factorization framework for signature analysis
- sbvar — Varying parameter analysis for SBML models
- sc-3D — Array alignment and 3D differential expression for 3D sc omics
- sc-catnip — sc-catnip - single-cell chromatin accessibility analysis tools in python
- sc-dandelion — sc-TCR/BCR-seq analysis tool
- sc-instant — InSTAnT is a toolkit to identify gene pairs which are d-colocalized from single molecule measurement data.
- sc-libra — LIBRA package
- SC-search — Single-cell search tool
- sc-tools — sc-tools - Analysis Tools for Single-Cell Data
- sc-utils — sc-utils: utility functions for single-cell analysis.
- scAAnet — An implementation of nonlinear archetypal analysis on single-cell RNA-seq data through autoencoder
- scab — Single cell analysis of B cells
- scaden — Cell type deconvolution using single cell data
- scAnnot — single cell annotation
- scanpy — Single-Cell Analysis in Python.
- scanpy-recipe — shortcut tools for scRNA-seq data analysis based on scanpy
- scArches — Transfer learning with Architecture Surgery on Single-cell data
- scArchest — Transfer learning with Architecture Surgery on Single-cell data
- scATAnno — no summary
- scAtlasVAE — scAtlasVAE: a deep learning framework for atlas-scale scRNA-seq integration and analysis
- scatrex — Map single-cell transcriptomes to copy number evolutionary trees.
- scbean — integration
- scCASE — no summary
- scCellFie — A tool for studying metabolic tasks from single-cell and spatial transcriptomics
- scCloud — scRNA-Seq analysis tools that scale to millions of cells
- scCODA — A Dirichlet-Multinomial approach to identify compositional changes in count data.
- sccover — A toolbox for deterministic subsampling of single-cell data.
- sccross — Single cell multi-omics cross modal generation, multi-omics simulation and perturbation
- scdataloader — a dataloader for single cell data in lamindb
- scdef — Extract hierarchical signatures of cell state from single-cell data.
- scDenorm — scDenorm: a denormalization tool for single-cell transcriptomics data
- scDesign3Py — The python interface for scDesign3 R package.
- scdiffeq — scDiffEq: modeling single-cell dynamics using neural differential equations.
- scdna-replication-tools — Code for analyzing single-cell replication dynamics
- scdrs — Single-cell disease-relevance score
- scegot — single cell trajectory inference framework based on Entropic Gaussian mixture Optimal Transport
- sceodesic — Generate sceodesic embeddings from an input scRNA-seq dataset.
- scETM — Single cell embedded topic model for integrated scRNA-seq data analysis.
- scFates — scanpy compatible python suite for fast tree inference and advanced pseudotime downstream analysis
- scflowpy — Python helper functions for scFlow
- scgen — ScGen - Predicting single cell perturbations.
- scgenome — Code for analyzing single cell whole genomes
- scglue — Graph-linked unified embedding for unpaired single-cell multi-omics data integration
- scGP — A package for simple scRNAseq analysis
- scHash — scHash package for scRNA-seq data integration
- schickit — a toolkit for processing single cell Hi-C data
- scHiCPTR — An unsupervised pseudotime inference pipeline through dual graph refinement for single cell Hi-C data.
- scHPL — Hierarchical progressive learning pipeline for single-cell RNA-sequencing datasets
- scib — Evaluating single-cell data integration methods
- scib-metrics — Accelerated and Python-only scIB metrics
- scimap — Spatial Single-Cell Analysis Toolkit
- scip — Scalable Cytometry Image Processing (SCIP) is an open-source tool that implements an image
- scip-workflows — no summary
- sciPENN — A package for integrative and predictive analysis of CITE-seq data
- scipr — Single Cell Iterative Point set Registration (SCIPR)
- scirpy — Python library for single-cell adaptive immune receptor repertoire (AIRR) analysis
- scKinetics — Biological prior guided single-cell kinetics inference.
- scLift — File read and write operations
- sclive — Single cell analysis plotting functions with interactive and web development friendly outputs.