Reverse Dependencies of anndata
The following projects have a declared dependency on anndata:
- enhancerai — A deep learning toolkit for investigating the gene regulatory code
- entrain — A single-cell analysis package to elucidate environmental factors controlling cell differentiation in RNA velocity and spatial datasets.
- entrain-spatial — A single-cell analysis package to elucidate environmental factors controlling cell differentiation in spatial datasets.
- epicarousel — EpiCarousel: memory- and time-efficient identification of metacells for atlas-level single-cell chromatin accessibility data
- epicascade — CASCADE: a scCAS cell type annotation method dedicated to differentiating and imbalanced types
- epiout — EpiOut: outlier detection for DNA accesibility data.
- ez-zarr — Give easy, high-level access to ome-zarr filesets.
- fast-tcrdist — Optimized TCRDist calculation for TCR repertoire data analysis
- fastlbp-baseline-imbg — A wrapper for Ben's LBP bio pipeline
- favapy — Infer Functional Associations using Variational Autoencoders on -Omics data.
- featherplot — featherplot
- feature-clock — Feature Clock, provides visualizations that eliminate the need for multiple plots to inspect the influence of original variables in the latent space. Feature Clock enhances the explainability and compactness of visualizations of embedded data.
- featuremap-learn — FeatureMAP
- fgread — Module for reading datasets shared on FASTGenomics
- flexinet — Flexible torch neural network architecture API
- Flow2Spatial — Reconstructing spatial proteomics through transfer learning
- fosfairy — TFs, IEGs and more!
- fractal-tasks-core — Core bioimage-analysis library and tasks of the Fractal analytics platform
- gatorpy — GATOR: A scalable framework for automated processing of highly multiplexed tissue images
- gefslim — A minimal reader for .gef files
- gemmapy — a Python Wrapper for the Gemma API
- GeneClust — Cofunctional grouping-based feature gene selection for unsupervised scRNA-seq clustering
- genes2genes — A tool for aligning gene expression trajectories of single-cell reference and query systems
- geniml — Genomic interval toolkit
- genomap — Genomap converts tabular gene expression data into spatially meaningful images.
- geome — Geometric Learning for Genome Data
- geomux — A tool to assign identifiers to cell barcodes
- geospace-st — GeoSpace method for identifying multiscale structure in spatial transcriptomic data
- glue-genes — Multidimensional data visualization for genomics
- GmGM — An implementation of the Gaussian multi-Graphical Model
- gptscannotation — Simple package for asking OpenAI GPT to do the scRNA-seq annotation based on the gene signatures
- graphcompass — Spatial metrics for differential analyses of cell organization across conditions
- graphtools — graphtools
- grnkit — A kit for running benchmarks on inferencing gene regulatory networks. (under construction)
- grnndata — Awesome gene regulatory network enhanced anndata
- GSG — no summary
- hiscanner — High-resolution copy number variant calling in single-cell whole-genome sequencing.
- HoloNet — Decoding functional cell–cell communication events by multi-view graph learning on spatial transcriptomics
- hotspotsc — Identifying informative genes (and gene modules) in a single-cell dataset.
- ikarus — no summary
- imc-analysis — A multi-file Python command line tool with commands qc, phenotype, and visualize.
- imspire — ImSpiRE is a python script (python 3.8+) for spatial resolution enhancenment by solving the entropic regularized fused Gromov-Wasserstein transport (FGW) problem for in situ capturing (ISC) spatial transcriptome.
- infercnvpy — Infercnv is a scalable python library to infer copy number variation (CNV) events from single cell transcriptomics data. It is heavliy inspired by InferCNV, but plays nicely with scanpy and is much more scalable.
- inferelator — Inferelator: Network Inference
- inferelator-velocity — Inferelator-Velocity Calcualtes Dynamic Latent Parameters
- intercode — Interpretable Autoencoder
- inVAE — Package for invariant VAE models on single-cell data
- ItClust — An Iterative Transfer learning algorithm for scRNA-seq Clustering
- ktplotspy — Python library for plotting Cellphonedb results. Ported from ktplots R package.
- kttools — Kelvin's miscellaneous tools for python
- lamindb — A data framework for biology.
- laminlake — Lamin Lake.
- lantsa — Landmark-based transferable subspace analysis for single-cell and spatial transcriptomics
- LARRY-dataset — LARRY Dataset: lineage and RNA recovery
- LatInt — Collection of modules to easily interpret Deep Learned latent spaces
- liana — LIANA+: a one-stop-shop framework for cell-cell communication
- LingerGRN — Gene regulatory network inference
- litds — litds
- lndb_storage — Storage → object.
- magic-impute — MAGIC
- marcopolo-pytorch — MarcoPolo: a method to discover differentially expressed genes in single-cell RNA-seq data without depending on prior clustering
- MarsGT — MarsGT: A Python library for rare cell identification (Internal testing only)
- matchclot — Installable matchclot package.
- maxspin — Estimate spatial information in spatial -omics datasets.
- mazebox — A suite of tools for analyzing single-cell transcriptomics data
- mesa-py — Multiomics and Ecological Spatial Analysis for Quantitative Decoding of Cellular Neighborhoods and Tissue Compartments
- metadatamapping — A python library to fetch metadata from NCBI and MetaSRA for a list of NCBI accessions and data extraction from ARCHS4
- metaspace-converter — Convert Metaspace datasets to AnnData
- metatime — Beta MetaTiME: annotate TME scRNA cell states
- METIforST — METI: Deep profiling of tumor ecosystems by integrating cell morphology and spatial transcriptomics
- mex-gene-archive — matrix market tar archive access utilities
- mira-multiome — Single-cell multiomics data analysis
- mitea-hires — Infer single-cell and spatial microRNA activity from transcriptomics data
- mixmil — Attention-based Multi-instance Mixed Models
- mnmstpy — The initial package of MNMST
- mofapy2 — Multi-omics factor analysis
- molecule-info — no summary
- monkeybread — Analyze cellular niches in single-cell spatial transcriptomics data
- monod — the Monod package fits CME models to sequencing data.
- mosaicmpi — mosaicMPI: Mosaic Multi-resolution Program Integration
- moscot — Multi-omic single-cell optimal transport tools
- mousipy — Python package for translating between single-cell count data with mouse and human genes using orthologs from biomart and HCOP.
- mowgli — Mowgli is a novel method for the integration of paired multi-omics data with any type and number of omics, combining integrative Nonnegative Matrix Factorization and Optimal Transport.
- mrvi — Multi-resolution analysis of single-cell data.
- mubind — ML for biomolecular binding
- mucstpy — The initial package of MuCST
- mudata — Multimodal omics analysis framework
- multianndata — Multi-sample version of AnnData
- MultiAssayExperiment — Container class for representing and managing multi-omics genomic experiments
- multivelo — Multi-omic extension of single-cell RNA velocity
- muon — Multimodal omics analysis framework
- mvtcr — mvTCR: A multimodal generative model to learn a unified representation across TCR sequences and scRNAseq data for joint analysis of single-cell immune profiling data
- napari-spatialdata — Interactive visualization of spatial omics data with napari
- neuralee — NeuralEE: a GPU-accelerated elastic embedding dimensionality reduction method for visualization of large-scale scRNA-seq data
- nichejepa — Spatial omics foundation model
- novosparc — De novo spatial reconstruction of single-cell gene expression.
- oggmap — extract orthologous maps (short: orthomap) from OrthoFinder output for query species
- OnClass — Single Cell Annotation based on the Cell Ontology
- OpenAnnotatePy — A python package for efficiently annotating the chromatin accessibility of genomic regions.
- openst — The computational pipeline for the Open-ST method.