Deep probabilistic analysis of single-cell and spatial omics data
- scrna-seq
- variational-bayes
- variational-autoencoder
- cite-seq
Repository Index
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- foundation-model
- gpt
- single-cell
Fast, sensitive and accurate integration of single-cell data with Harmony
Spatial Single Cell Analysis in Python
- single-cell-rna-seq
- single-cell-genomics
- spatial-transcriptomics
- spatial-analysis
R package for detecting doublets in single-cell RNA sequencing data
A tool for semi-automatic cell type classification
- python
- single-cell
- machine-learning
- scrna-seq
SCENIC is an R package to infer Gene Regulatory Networks and cell types from single-cell RNA-seq data.
Graph-linked unified embedding for single-cell multi-omics data integration
- bioinformatics
- deep-learning
- single-cell
- single-cell-multiomics
Reference mapping for single-cell genomics
- single-cell
- deep-learning
- rna-seq-analysis
- data-integration
UCE is a zero-shot foundation model for single-cell gene expression data
Native R and Python sample-deletion robustness for omics: candidate certificates, minimum deletion bounds, Bioconductor model refits and donor-level pseudobulk
- bioinformatics
- exact-optimization
- metabolomics
- paired-data
Haplotype-aware CNV analysis from single-cell RNA-seq, ATAC-seq, and multiome
- cancer-genomics
- cnv-detection
- single-cell
- phylogeny
scPerturb: A resource and a python/R tool for single-cell perturbation data
- cite-seq
- database
- perturbation
- scatac-seq
Repository for Nicheformer: a foundation model for single-cell and spatial omics
🏃 The go-to single-cell Foundation Model
- batch-correction
- cell-biology
- celltype-annotation
- denoising
Code for "Predicting Cellular Responses to Novel Drug Perturbations at a Single-Cell Resolution", NeurIPS 2022.
- disentanglement
- drug-discovery
- genomics
- perturbation
CASSIA: A Multi-Agent LLM-Based Single-Cell Cell Type Annotation Framework
- ai4science
- llm
- multiagent-systems
- prompt-engineering
PRnet is a flexible and scalable perturbation-conditioned generative model predicting transcriptional responses to unseen complex perturbations at bulk and single-cell levels.
PyTorch implementation of the MIDAS algorithm for single-cell multimodal data integration (Nature Biotechnology 2024).
- deep-generative-model
- deep-learning
- single-cell-data-integration
- single-cell-multiomics
Repository for paper scMulan: a multitask generative pre-trained language model for single-cell analysis.
- foundation-models
- gpt
- single-cell
Autonomous multi-agent framework to optimize scientific software
- acceleration
- agentic-ai
- ai-agents
- bioinformatics
Deep learning model for single-cell inference of multi-omic profiles from a single input modality.
- single-cell
- scrna-seq
- scatac-seq
- deep-neural-networks
MCP server for spatial transcriptomics analysis through natural language interfaces.
- bioinformatics
- cell-communication
- deconvolution
- machine-learning
Multigrate: multiomic data integration for single-cell genomics