Reverse Dependencies of anndata

The following projects have a declared dependency on anndata:

• acdc-py — A package to quickly identify unbiased graph-based clusterings via parameter optimization in Python
• ACTIONet — ACTIONet single-cell analysis framework
• adata-query — Fetch and format data matrices from AnnData.
• adpbulk — Pseudo-Bulking Single-Cell RNA-seq
• ai4scr-scQUEST — scQUEST package
• akey — akey
• allcools — Toolkit for single-cell DNA methylome and multiomic data analysis.
• alphastats — An open-source Python package for automated and scalable statistical analysis of mass spectrometry-based proteomics
• anansescanpy — implementation of scANANSE for scanpy objects in Python
• ann-gsea — ann-gsea - integrate GSEA molecular signatures with AnnData
• ann-nmf — ann_nmf - AnnData wrapper of the ARD-NMF module from SignatureAnalyzer
• anndata-sdk — anndata_sdk
• anndata2ri — no summary
• anngtf — anngtf - lift annotations from a `.gtf` file to your AnnData object.
• annoyance — annoyance - single-cell AnnData wrapper of Spotify's Annoy library.
• ArchR-h5ad — ArchR_h5ad: Read .arrow files (from ArchR) to anndata.
• astir — no summary
• asto — asto
• autogenes — Automatic Gene Selection for Bulk Deconvolution
• baredSC — baredSC: Bayesian Approach to Retreive Expression Distribution of Single Cell
• batchglm — Fast and scalable fitting of over-determined generalized-linear models (GLMs)
• bengrn — benchmarking gene regulatory networks
• bento-tools — A toolkit for subcellular analysis of RNA organization
• besca — Collection of BEDA internal python functions for analysing single cell RNAseq data.
• biolord — A deep generative framework for disentangling known and unknown attributes in single-cell data.
• bioplexpy — Python-side access to PPI data from Gygi lab
• biorag — BioRAG: A tool for textual and gene set search against ARCHS4 data
• biotranslator — BioTranslator: Cross-modal Translation for Zero-shot Biomedical Classification
• BlueWhale3-SingleCell — Add-on for bioinformatics analysis of single cell data.
• bolero — sequence
• bolero-process — Data preprocessing for bolero package
• booleabayes — A suite for network inference from transcriptomics data
• cansig — Discovering de novo shared transcriptional programs in single cancer cells
• cap-anndata — Partial read of AnnData files for low-memory operations with large datasets.
• capital — Single-Cell Analysis, comparing pseudotime trajectories with tree alignment
• card-scrnaseq-pipeline — A collection of command-line wrappers for scanpy scRNA-seq
• cas-tools — Cell Annotation Schema tools.
• cat-python — Cluster Alignment Tool
• CeLEryPy — Leverage spatial transcriptomics data to recover cell locations in single-cell RNA RNA-seq
• celescope — Single Cell Analysis Pipelines
• cell-ann — cell-ann: Cell approximate nearest neighbors
• Cell-BLAST — Single-cell transcriptome querying tool
• cell-tools — cell_tools - Analysis Tools for Single-Cell Data
• cell2sentence — cell2sentence: create cell sentences from sequencing data
• cellanova — Cell state space analysis of variance for signal recovery with batch correction
• cellarium-ml — Machine learning library for single-cell data analysis
• cellbender — A software package for eliminating technical artifacts from high-throughput single-cell RNA sequencing (scRNA-seq) data
• cellcharter — A Python package for the identification, characterization and comparison of spatial clusters from spatial -omics data.
• celldancer — Study RNA velocity through neural network.
• celligner — A useful module for alligning cell lines to tumors
• cellmap — CellMap - RNA landscape inference method
• cellograph — cellograph
• cellpath — CellPath, multiple trajectories inference in single cell RNA-Seq data from RNA velocity
• CellPhoneDB — Inferring cell-cell communication.
• cellrank — CellRank: dynamics from multi-view single-cell data
• CellSNAP — A package for enhancing single-cell population delineation by integrating cross-domain information.
• cellvgae — CellVGAE uses the connectivity between cells (such as k-nearest neighbour graphs) with gene expression values as node features to learn high-quality cell representations in a lower-dimensional space
• cellxgene-census — API to facilitate the use of the CZ CELLxGENE Discover Census. For more information about the API and the project visit https://github.com/chanzuckerberg/cellxgene-census/
• chame — Chromatin accessibility module
• cinemaot — Causal INdependent Effect Module Attribution + Optimal Transport
• cirrocumulus — Bring your single-cell data to life
• clehrity — Clehrity
• cna — covarying neighborhood analysis
• cnmfsns — cNMF Solution Network Space
• commot — Cell-cell communications inference for spatial transcriptomics data via optimal transport.
• ComSeg — single cell RNA profiling analysis of imaging-based spatial transcriptomics data
• convexgating — ConvexGating is a Python tool to infer optimal gating strategies for flow cytometry and cyTOF data.
• cosg — Accurate and fast cell marker gene identification with COSG
• cospar — CoSpar: integrating state and lineage information for dynamic inference
• countASAP — A software for converting ASAPseq FASTQs to count matrices
• cpa-tools — Compositional Perturbation Autoencoder (CPA)
• crispr-screen — crispr_tools - Analysis Tools for CRISPR Screen Design and Analysis
• crispr-tools — crispr_tools - Analysis Tools for CRISPR Screen Design and Analysis
• cspot — CELL SPOTTER (CSPOT): A scalable framework for automated processing of highly multiplexed tissue images
• cstreet — CStreet is a python script (python 3.6, 3.7 or 3.8) for cell state trajectory construction by using k-nearest neighbors graph algorithm for time-series single-cell RNA-seq data.
• cyto-dl — Collection of representation learning models, techniques, callbacks, utils, used to create latent variable models of cell shape, morphology and intracellular organization.
• cytopath — Simulation based inference of differentiation trajectories from RNA velocity fields.
• CytoSimplex — Simplex Visualization of Cell Fate Similarity in Single-Cell Data
• dcpredictor — transfer learning approach
• DEAPLOG — A tool to perform differentially expression analysis and calculate the pseudotime and coodinates of genes by using single cell RNA-seq data
• decare — Detection of spatial chromatin accessibility patterns with inter-cellular correlations
• decoupler — Ensemble of methods to infer biological activities from omics data
• DeepTalk-ST — Cell-cell communication prediction for ST data
• degex — Detect Gene Expression in Single-CEll data
• DeltaTopic — Packages to implement BALSAM and DeltaTopic as described in the paper: Unraveling dynamically-encoded latent transcriptomic patterns in pancreatic cancer cells by topic modelling
• delve-fs — Feature selection for preserving biological trajectories from single-cell data
• deseqpyodide — no summary
• DeSide — A DEep-learning and SIngle-cell based DEconvolution method for solid tumors
• destinynet — This is a code to predict cell's fate
• devcellpy — devCellPy -- hierarchical multilayered classification of cells based on scRNA-seq
• diffxpy — Fast and scalable differential expression analysis on single-cell RNA-seq data
• doubletdetection — Method to detect and enable removal of doublets from single-cell RNA-sequencing.
• dpks — Data processing package for the analysis of omics data
• drug2cell — Gene group activity utility functions for scanpy
• dspin — Regulatory network models from single-cell perturbation profiling
• dynamo-release — Mapping Vector Field of Single Cells
• EAGS — EAGS: efficient and adaptive Gaussian smoothing applied to high-resolved spatial transcriptomics
• ecmanalysis — Tools for analysis of the extracellular matrix
• emobject — data abstraction and libraries for spatial omics
• enhancerai — A deep learning toolkit for investigating the gene regulatory code