Alternatives and similar repositories for SIMLR_PY

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

• xiaoyeye / CNNC
  covolutional neural network based coexpression analysis
  ☆79Updated 5 years ago
• hui2000ji / scETM
  A generative topic model that facilitates integrative analysis of large-scale single-cell RNA sequencing data.
  ☆53Updated 3 years ago
• xiaoyeye / GCNG
  using graph convolutional neural network and spaital transcriptomics data to infer cell-cell interactions
  ☆56Updated 4 years ago
• davidbuterez / CellVGAE
  An unsupervised scRNA-seq analysis workflow with graph attention networks
  ☆26Updated 2 years ago
• snap-stanford / mars
  Discovering novel cell types across heterogenous single-cell experiments
  ☆123Updated 2 years ago
• wukevin / babel
  Deep learning model for single-cell inference of multi-omic profiles from a single input modality.
  ☆43Updated 2 years ago
• ZJUFanLab / scDeepSort_performance_comparison
  The source code and results for different methods on annotating external testing datsets of human and mouse.
  ☆12Updated 4 years ago
• AltschulerWu-Lab / scScope
  ☆48Updated 6 years ago
• jlakkis / CarDEC
  ☆19Updated 4 years ago
• xuyungang / scIGANs
  Generative adversarial networks for single-cell RNA-seq imputation
  ☆39Updated 5 years ago
• calico / scnym
  Semi-supervised adversarial neural networks for classification of single cell transcriptomics data
  ☆76Updated 10 months ago
• zeochoy / tcga-embedding
  using shallow neural network layer (embedding) to infer gene-gene/sample relationship from gene expression data
  ☆21Updated 6 years ago
• eleozzr / desc
  Deep Embedding for Single-cell Clustering
  ☆88Updated last year
• ChengF-Lab / autoCell
  ☆16Updated 3 years ago
• nicococo / scRNA
  Python framework for single-cell RNA-seq clustering with special focus on transfer learning.
  ☆18Updated 6 years ago
• trungnt13 / sisua
  SemI-SUpervised generative Autoencoder models for single cell data
  ☆18Updated 4 years ago
• lab-conrad / resVAE
  resVAE is a restricted latent variational autoencoder that we wrote to uncover hidden structures in gene expression data, especially usin…
  ☆12Updated 2 years ago
• lanagarmire / deepimpute
  An accurate and efficient deep learning method for single-cell RNA-seq data imputation
  ☆89Updated 3 years ago
• ZJUFanLab / scDeepSort
  Cell-type Annotation for Single-cell Transcriptomics using Deep Learning with a Weighted Graph Neural Network
  ☆106Updated 2 years ago
• Su-informatics-lab / DSTG
  Deconvoluting Spatial Transcriptomics Data through Graph-based Artificial Intelligence
  ☆39Updated 3 years ago
• theislab / trVAE
  Conditional out-of-distribution prediction
  ☆63Updated last year
• biomed-AI / GraphSCI
  Imputing Single-cell RNA-seq data by combining Graph Convolution and Autoencoder Neural Networks
  ☆20Updated last year
• cole-trapnell-lab / sci-plex
  repository containing analysis scripts and auxiliary files
  ☆36Updated 5 years ago
• ttgump / scDCC
  scDCC: Single Cell Deep Constrained Clustering
  ☆41Updated last year
• zcang / SpaOTsc
  ☆45Updated 3 months ago
• QSong-github / scGCN
  scGCN is a graph convolutional networks algorithm for knowledge transfer in single cell omics
  ☆41Updated 3 years ago
• LucasESBS / vega
  VEGA: VAE Enhanced by Gene Annotations
  ☆16Updated 3 years ago
• ushaham / BatchEffectRemoval
  ☆56Updated 5 years ago
• pinellolab / simba
  SIMBA: SIngle-cell eMBedding Along with features
  ☆63Updated last year
• txWang / BERMUDA
  BERMUDA (Batch Effect ReMoval Using Deep Autoencoders) is a novel transfer-learning-based method for batch correction in scRNA-seq data.
  ☆31Updated 5 years ago