Alternatives and similar repositories for DeepSEM

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

• OSU-BMBL / deepmaps
  Single-cell biological network inference using a heterogeneous graph transformer
  ☆73Updated 4 months ago
• hui2000ji / scETM
  A generative topic model that facilitates integrative analysis of large-scale single-cell RNA sequencing data.
  ☆50Updated 3 years ago
• zpliulab / GENELink
  ☆33Updated 2 years ago
• pinellolab / simba
  SIMBA: SIngle-cell eMBedding Along with features
  ☆63Updated 8 months ago
• Su-informatics-lab / DSTG
  Deconvoluting Spatial Transcriptomics Data through Graph-based Artificial Intelligence
  ☆39Updated 2 years ago
• theislab / scib-reproducibility
  Additional code and analysis from the single-cell integration benchmarking project
  ☆67Updated 2 years ago
• zhanglab-wbgcas / STGRNS
  ☆29Updated 2 years ago
• kodaim1115 / scMM
  ☆17Updated 3 years ago
• theislab / sc-pert
  Models and datasets for perturbational single-cell omics
  ☆153Updated 2 years ago
• melobio / Concerto-reproducibility
  ☆38Updated 2 years ago
• sunyolo / DeepTFni
  A VGAE-based model to infer transcription factor regulatory network
  ☆27Updated 2 years ago
• theislab / scgen-reproducibility
  ☆29Updated 4 years ago
• wukevin / babel
  Deep learning model for single-cell inference of multi-omic profiles from a single input modality.
  ☆42Updated last year
• theislab / cpa
  The Compositional Perturbation Autoencoder (CPA) is a deep generative framework to learn effects of perturbations at the single-cell leve…
  ☆102Updated 11 months ago
• HelloWorldLTY / scEval
  Codes for paper: Evaluating the Utilities of Large Language Models in Single-cell Data Analysis.
  ☆71Updated 3 weeks ago
• yhr91 / GEARS_misc
  ☆19Updated 9 months ago
• welch-lab / PerturbNet
  PerturbNet is a deep generative model that can predict the distribution of cell states induced by chemical or genetic perturbation
  ☆34Updated this week
• ZJUFanLab / scDeepSort
  Cell-type Annotation for Single-cell Transcriptomics using Deep Learning with a Weighted Graph Neural Network
  ☆103Updated 2 years ago
• xiaoyeye / CCST
  Cell clustering for spatial transcriptomics data with graph neural network
  ☆63Updated 2 years ago
• nitzanlab / biolord
  ☆80Updated 11 months ago
• YangLabHKUST / SpatialScope
  A unified approach for integrating spatial and single-cell transcriptomics data by leveraging deep generative models
  ☆67Updated last year
• yulun-rayn / graphVCI
  Predicting Cellular Responses with Variational Causal Inference and Refined Relational Information (ICLR 2023)
  ☆19Updated 3 weeks ago
• cole-trapnell-lab / sci-plex
  repository containing analysis scripts and auxiliary files
  ☆34Updated 5 years ago
• jiang-q19 / scPRAM
  scPRAM accurately predicts single-cell gene expression perturbation response based on attention mechanism
  ☆15Updated 8 months ago
• sanderlab / scPerturb
  scPerturb: A resource and a python/R tool for single-cell perturbation data
  ☆129Updated 4 months ago
• jsxlei / SCALEX
  Online single-cell data integration through projecting heterogeneous datasets into a common cell-embedding space
  ☆79Updated last month
• theislab / scTab
  ☆59Updated 10 months ago
• zcang / SpaOTsc
  ☆45Updated 2 years ago
• altoslabs / perturbench
  ☆28Updated last month
• PayamDiba / SERGIO
  A simulator for single-cell expression data guided by gene regulatory networks
  ☆63Updated last year