Alternatives and similar repositories for cellot

Users that are interested in cellot are comparing it to the libraries listed below

• theislab / CellFlow
  Modeling complex perturbations with CellFlow
  ☆95Updated last week
• theislab / cpa
  The Compositional Perturbation Autoencoder (CPA) is a deep generative framework to learn effects of perturbations at the single-cell leve…
  ☆118Updated last year
• theislab / sc-pert
  Models and datasets for perturbational single-cell omics
  ☆167Updated 3 years ago
• Genentech / sVAE
  ☆63Updated 2 years ago
• theislab / nicheformer
  Repository for Nicheformer: a foundation model for single-cell and spatial omics
  ☆115Updated 7 months ago
• ArcInstitute / cell-eval
  Comprehensive suite for evaluating perturbation prediction models
  ☆100Updated last week
• nitzanlab / biolord
  ☆86Updated last year
• EperLuo / scDiffusion
  A model developed for the generation of scRNA-seq data
  ☆78Updated 8 months ago
• const-ae / linear_perturbation_prediction-Paper
  ☆58Updated 3 months ago
• theislab / moscot
  Multi-omic single-cell optimal transport tools
  ☆177Updated this week
• snap-stanford / UCE
  UCE is a zero-shot foundation model for single-cell gene expression data
  ☆224Updated 8 months ago
• theislab / ncem
  Learning cell communication from spatial graphs of cells
  ☆114Updated last year
• OmicsML / CellPLM
  Official repo for CellPLM: Pre-training of Cell Language Model Beyond Single Cells.
  ☆99Updated last year
• sanderlab / scPerturb
  scPerturb: A resource and a python/R tool for single-cell perturbation data
  ☆151Updated 8 months ago
• theislab / chemCPA
  Code for "Predicting Cellular Responses to Novel Drug Perturbations at a Single-Cell Resolution", NeurIPS 2022.
  ☆129Updated 9 months ago
• aaronwtr / PertEval
  Evaluation suite for transcriptomic perturbation effect prediction models. Includes support for single-cell foundation models.
  ☆29Updated 3 months ago
• xianglin226 / Benchmarking-Single-Cell-Perturbation
  Single-Cell (Perturbation) Model Library
  ☆81Updated 2 months ago
• snap-stanford / GEARS
  GEARS is a geometric deep learning model that predicts outcomes of novel multi-gene perturbations
  ☆309Updated 9 months ago
• scverse / pertpy
  Single-cell perturbation analysis
  ☆212Updated last week
• rsinghlab / SCOT
  Gromov-Wasserstein based optimal transport for aligning single-cell multi-omics data
  ☆77Updated last year
• welch-lab / PerturbNet
  PerturbNet is a deep generative model that can predict the distribution of cell states induced by chemical or genetic perturbation
  ☆53Updated 4 months ago
• cantinilab / scPRINT
  🏃 The go-to single-cell Foundation Model
  ☆117Updated last week
• kodaim1115 / scMM
  ☆18Updated 4 years ago
• PayamDiba / SERGIO
  A simulator for single-cell expression data guided by gene regulatory networks
  ☆69Updated last year
• theislab / prophet
  ☆37Updated 2 weeks ago
• Murali-group / Beeline
  BEELINE: evaluation of algorithms for gene regulatory network inference
  ☆197Updated last month
• microsoft / zero-shot-scfoundation
  ☆73Updated last year
• HantaoShu / DeepSEM
  ☆85Updated 2 years ago
• YosefLab / scib-metrics
  Accelerated, Python-only, single-cell integration benchmarking metrics
  ☆77Updated this week
• snap-stanford / SATURN
  ☆143Updated last year