Reverse Dependencies of anndata
The following projects have a declared dependency on anndata:
- scmallet — Python wrapper of MALLET for LDA analysis on single-cell data
- scMDCF — Aligned Cross-modal Integration and Characterization of Single-Cell Multiomic Data with Deep Contrastive Learning
- scmmd — Maximum mean discrepancy comparisons single cell profiles
- scMMT — A package for cell annotation, protein prediction, and low dimensional embedding representation
- scnym — Semi supervised adversarial network networks for single cell classification
- scPANTHEON — A graphical interface for single cell analysis.
- scplot — Single cell plotting
- scpopcorn — PopCorn is a new method for the identification of sub-populations of cells present within individual single cell experiments and mapping of these sub-populations across the experiments.
- scprel — Single-cell data preprocessing for multiple samples.
- scprep — scprep
- scProject — Transfer learning framework for single cell gene expression analysis in Python
- scpy4reactome — python service for single cell analysis in Reactome
- scRADO — doublet detection algorithm for droplet-based single-cell sequencing data
- scrainbow — RAINBOW: accurate cell type annotation method via contrastive learning and reference guidance for scCAS data
- screcode — RECODE - resolution of the curse of dimensionality in single-cell data analysis
- screen-tools — crispr_tools - Analysis Tools for CRISPR Screen Design and Analysis
- scReGAT — A GAT-based computational framework to predict long-range gene regulatory relationships
- scRFE — Single-cell identity definition using random forest modelling and recursive feature elimination
- scripro — Single-cell gene regulation network inference by large-scale data integration Pro
- scrnatools — Tools for single cell RNA sequencing pipelines
- scSAMP — scRNA-seq data sampling toolkit.
- scselpy — A tool to select cells on scanpy-based scRNA-seq analysis pipelines.
- scsims — Scalable, Interpretable Deep Learning for Single-Cell RNA-seq Classification
- scslat — A graph deep learning based tool to align single cell spatial omics data
- scTAPE — deep learning tools for bulk RNA-seq deconvolution and gene expression analysis
- sctdl — no summary
- scTM — A toolbox for single cell topic models
- sctour — a deep learning architecture for robust inference and accurate prediction of cellular dynamics
- sctransfer — Python part for scRNA-seq transfer learning denoising tool SAVER-X
- sctreeshap — sctreeshap: a cluster tree data structure, and for shap analysis
- scvega — VEGA: a VAE Enhanced by Gene Annotations for interpretable scRNA-seq deep learning
- scvelo — RNA velocity generalized through dynamical modeling
- scverse — scverse bundle
- scvi — Single-cell Variational Inference
- scvi-criticism — Evaluation metrics for scvi-tools models
- scvi-tools — Deep probabilistic analysis of single-cell omics data.
- scvr — single cell VR preprocess
- scvr-prep — single cell VR preprocess
- scyan — Single-cell Cytometry Annotation Network
- sdcd — Stable differentiable causal discovery for interventional data.
- sdevelo — SDEvelo: a deep generative approach for transcriptional dynamics with cell-specific latent time and multivariate stochastic modeling
- SEACells — no summary
- SEAGAL — Spatial Enrichment Analysis of Gene Association using L-index
- serotiny — A framework of tools to structure, configure and drive deep learning projects
- SEVtras — sEV-containing droplet identification in scRNA-seq data
- sfaira — sfaira is a model and a data repository for single-cell data in a single python package.
- shadows — Low-memory data interfaces for scverse
- sift-sc — Biological signal filtering in single-cell data.
- SimTissue — no summary
- simvi — Spatial Interaction Modeling using Variational Inference
- SingleCellExperiment — Container class for single-cell experiments
- singleCellHaystack — A Python implementation of singleCellHaystack.
- sketchKH — Distribution-based sketching of single-cell samples
- sleep-models — Models to learn the mapping between the transcriptome of cells and their sleep/wake state
- Slpapy — Spatial_lipomic_and_proteomic_analysis
- SMOPCA — A novel spatially aware multi-omics dimension reduction method
- smqpp — Smartseq2 preprocessing toolkit
- SNAF — A Python package to predict, prioritize and visualize splicing derived neoantigens, including MHC-bound peptides (T cell antigen) and altered surface protein (B cell antigen)
- snapatac2 — SnapATAC: Single Nucleus Analysis Pipeline for ATAC-seq
- SOAPy-st — Spatial Omics Analysis in Python
- sobolev-alignment — Sobolev alignment of deep probabilistic models for comparing single cell profiles
- socube — A simple python package for doublet detection in scRNA-seq data
- somacore — Python-language API specification and base utilities for implementation of the SOMA system.
- SOMENDER — TBD
- SpaceFlow — Identifying Spatiotemporal Patterns of Cells for Spatial Transcriptome Data
- spaco-release — Spaco: a comprehensive tool for coloring spatial data at single-cell resolution
- SpaDecon — SpaDecon: cell-type deconvolution in spatial transcriptomics with semi-supervised learning
- SpaGCN — SpaGCN: Integrating gene expression and histology to identify spatial domains and spatially variable genes using graph convolutional networks
- spametric — Metric learning for Spatial transcriptomics
- sparcl — Relational Contrastive Learning for Spatial Transcriptomics
- spasrl — Spatially aware self-representation learning
- spateo-release — Spateo: multidimensional spatiotemporal modeling of single-cell spatial transcriptomics
- spatial-eggplant — Landmark-based transfer of spatial transcriptomics data
- spatialcorr-sim — SpatialCorr
- spatialdata — Spatial data format.
- spatialdata-io — SpatialData IO for common techs
- SpatialDM — SpatialDM: Spatial co-expression Detected by bivariate Moran
- spatialtis — Ultra-fast spatial analysis toolkit for large-scale spatial single-cell data
- SpatialTools — spatial tools for S1000
- SpatialViewPy — no summary
- spherpro — Tool to analize tumor spheroid data
- spicemix — SpiceMix: a probabilistic graphical model for spatial transcriptomics data
- spider-st — Identifying spatially variable interactions
- spiderYa — Identifying spatially variable interactions
- spsam — spSAM: 10X visium spot Split Align Map
- spVIPES — Shared-private Variational Inference with Product of Experts and Supervision
- squidpy — Spatial Single Cell Analysis in Python
- SR3 — SR3 fusion clustering
- st-spider — A tools to simulate spatial transcriptomics data.
- STACCI — STACCI for STCase
- stDiff-sc — a diffusion model to impute ST data by learn scRNA-seq data
- steinbock — A toolkit for processing multiplexed tissue images
- StereoUtils — scanpy extra function for STOmics
- STFD — STFD: Series of deep learning-based foundation models for spatial transcriptomic data analysis
- STMiner — Python package for spatial transcriptomics data analysis
- STpipe-sc — STpipe is designed to analyze spatial transcriptomic data.
- stTransfer — Transfer learning for spatial transcriptomics data and single-cell RNA-seq data.
- SummarizedExperiment — Container to represent data from genomic experiments
- superexacttestpy — Python implementation of the SuperExactTest algorithm
- supirfactor-dynamical — Dynamical Model Extension of the Supirfactor Model