Reverse Dependencies of scvi-tools

The following projects have a declared dependency on scvi-tools:

• 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.
• cansig — Discovering de novo shared transcriptional programs in single cancer cells
• cell2location — cell2location: High-throughput spatial mapping of cell types
• cellcharter — A Python package for the identification, characterization and comparison of spatial clusters from spatial -omics data.
• contrastive-vi — no summary
• cpa-tools — Compositional Perturbation Autoencoder (CPA)
• CSNet — short description
• dcpredictor — transfer learning approach
• methyl-vi — no summary
• mrvi — Multi-resolution analysis of single-cell data.
• multigrate — Multigrate: multimodal data integration for single-cell genomics.
• omicverse — OmicVerse: A single pipeline for exploring the entire transcriptome universe
• panpipes — Panpipes - multimodal single cell pipelines
• pegasuspy — Pegasus is a Python package for analyzing sc/snRNA-seq data of millions of cells
• pertpy — Perturbation Analysis in the scverse ecosystem.
• pertvi — deep mechanistic modeling of single-cell atlas using variational inference
• popv — Consensus prediction of cell type labels with popV
• pyrovelocity — A multivariate RNA Velocity model to estimate future cell states with uncertainty using probabilistic modeling with pyro.
• scAnnot — single cell annotation
• scArches — Transfer learning with Architecture Surgery on Single-cell data
• scArchest — Transfer learning with Architecture Surgery on Single-cell data
• scBC — a single-cell transcriptome Bayesian biClustering framework
• scButterfly — A versatile single-cell cross-modality translation method via dual-aligned variational autoencoders
• scgen — ScGen - Predicting single cell perturbations.
• scgpt — Large-scale generative pretrain of single cell using transformer.
• scib — Evaluating single-cell data integration methods
• scib-metrics — Accelerated and Python-only scIB metrics
• scLift — File read and write operations
• scrnatools — Tools for single cell RNA sequencing pipelines
• scUNAGI — A Python package for UNAGI
• scvega — VEGA: a VAE Enhanced by Gene Annotations for interpretable scRNA-seq deep learning
• scvelo — RNA velocity generalized through dynamical modeling
• scvi-criticism — Evaluation metrics for scvi-tools models
• scvi-tools — Deep probabilistic analysis of single-cell omics data.
• simvi — Spatial Interaction Modeling using Variational Inference
• sobolev-alignment — Sobolev alignment of deep probabilistic models for comparing single cell profiles
• SPACEL — SPACEL: characterizing spatial transcriptome architectures by deep-learning
• spVIPES — Shared-private Variational Inference with Product of Experts and Supervision
• stereoAlign — A toolkit package of data integration
• velovi — Estimation of RNA velocity with variational inference.