Alternatives and similar repositories for dyngen

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

• PayamDiba / SERGIO
  A simulator for single-cell expression data guided by gene regulatory networks
  ☆61Updated last year
• KrishnaswamyLab / scprep
  A collection of scripts and tools for loading, processing, and handling single cell data.
  ☆72Updated last year
• welch-lab / MultiVelo
  Multi-omic velocity inference
  ☆110Updated 7 months ago
• klarman-cell-observatory / scPhere
  ☆100Updated 2 years ago
• Murali-group / BoolODE
  Git Repo for simulating Boolean Models
  ☆34Updated 11 months ago
• brianhie / geosketch
  Geometry-preserving random sampling
  ☆82Updated 7 months ago
• livnatje / DIALOGUE
  DIALOGUE is a dimensionality reduction method that uses cross-cell-type associations to identify multicellular programs (MCPs) and map th…
  ☆110Updated last year
• romain-lopez / scVI-reproducibility
  Reproducing the experiments of the paper "Deep generative modeling for single-cell transcriptomics"
  ☆57Updated 6 years ago
• gifford-lab / prescient
  Codebase for PRESCIENT (Potential eneRgy undErlying Single Cell gradIENTs) for generative modeling of single-cell time-series.
  ☆47Updated 4 months ago
• Genentech / sVAE
  ☆63Updated last year
• flatironinstitute / inferelator
  Task-based gene regulatory network inference using single-cell or bulk gene expression data conditioned on a prior network.
  ☆49Updated 10 months ago
• const-ae / linear_perturbation_prediction-Paper
  ☆23Updated last month
• pinellolab / dictys
  Context specific and dynamic gene regulatory network reconstruction and analysis
  ☆117Updated 9 months ago
• ma-compbio / SpiceMix
  spatial transcriptome, single cell
  ☆68Updated 2 years ago
• zcang / SpaOTsc
  ☆45Updated 2 years ago
• calico / scnym
  Semi-supervised adversarial neural networks for classification of single cell transcriptomics data
  ☆75Updated 5 months ago
• YosefLab / SymSim
  ☆26Updated 8 months ago
• YosefLab / scib-metrics
  Accelerated, Python-only, single-cell integration benchmarking metrics
  ☆59Updated this week
• aertslab / arboreto
  A scalable python-based framework for gene regulatory network inference using tree-based ensemble regressors.
  ☆59Updated last year
• KrishnaswamyLab / MELD
  Quantifying experimental perturbations at single cell resolution
  ☆108Updated 8 months ago
• AltschulerWu-Lab / scScope
  ☆49Updated 5 years ago
• simslab / scHPF
  Single-cell Hierarchical Poisson Factorization
  ☆70Updated 2 years ago
• willtownes / nsf-paper
  Nonnegative spatial factorization for multivariate count data
  ☆58Updated last year
• aristoteleo / Scribe-py
  Regulatory networks with Direct Information in python
  ☆40Updated 2 years ago
• wukevin / babel
  Deep learning model for single-cell inference of multi-omic profiles from a single input modality.
  ☆42Updated last year
• Teichlab / bbknn
  Batch balanced KNN
  ☆161Updated last year
• berenslab / umi-normalization
  Companion repository to Lause, Berens & Kobak (2021): "Analytic Pearson residuals for normalization of single-cell RNA-seq UMI data", Gen…
  ☆40Updated 3 years ago
• altoslabs / perturbench
  ☆26Updated last week
• theislab / cpa
  The Compositional Perturbation Autoencoder (CPA) is a deep generative framework to learn effects of perturbations at the single-cell leve…
  ☆100Updated 9 months ago
• theislab / scib-reproducibility
  Additional code and analysis from the single-cell integration benchmarking project
  ☆65Updated 2 years ago