Alternatives and similar repositories for scRNA

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

• trungnt13 / sisua
  SemI-SUpervised generative Autoencoder models for single cell data
  ☆18Updated 4 years ago
• 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
• 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
• eleozzr / desc
  Deep Embedding for Single-cell Clustering
  ☆88Updated last year
• ChengF-Lab / autoCell
  ☆16Updated 3 years ago
• jwang-lab / scGNN
  scGNN (single cell graph neural networks) for single cell clustering and imputation using graph neural networks
  ☆11Updated 5 years ago
• WangShuxiong / SoptSC
  SoptSC for single cell data analysis: unsupervised inference of clustering, cell lineage, pseudotime and cell-cell communication network …
  ☆22Updated 4 years ago
• jianhuupenn / ItClust
  Iterative transfer learning with neural network improves clustering and cell type classification in single-cell RNA-seq analysis
  ☆55Updated 5 months ago
• bowang87 / SIMLR_PY
  Python Implementation of SIMLR for single-cell visualization and analysis
  ☆24Updated 3 years ago
• yycunc / SAFEclustering
  SAFE (Single-cell Aggregated clustering From Ensemble): Cluster ensemble for single-cell RNA-seq data
  ☆18Updated 4 years ago
• xuebaliang / scAnCluster
  Single-cell RNA-seq clustering and annotation
  ☆13Updated 5 years ago
• raphael-group / netNMF-sc
  netNMF-sc: A network regularization algorithm for dimensionality reduction and imputation of single-cell expression data
  ☆23Updated 4 years ago
• davidbuterez / CellVGAE
  An unsupervised scRNA-seq analysis workflow with graph attention networks
  ☆26Updated 2 years ago
• huBioinfo / CytoTalk
  A novel computational method for inferring cell-type-specific signaling networks using single-cell transcriptomics data for better charac…
  ☆19Updated 4 years ago
• theislab / trVAE
  Conditional out-of-distribution prediction
  ☆62Updated last year
• AltschulerWu-Lab / scScope
  ☆48Updated 6 years ago
• seasamgo / rescue
  Bootstrap imputation for scRNAseq data
  ☆12Updated 5 years ago
• bm2-lab / scMVP
  ☆33Updated 7 months ago
• xiaoyeye / CNNC
  covolutional neural network based coexpression analysis
  ☆79Updated 5 years ago
• kimmo1019 / scDEC
  Simultaneous deep generative modeling and clustering of single cell genomic data
  ☆32Updated 3 years ago
• jlakkis / CarDEC
  ☆19Updated 4 years ago
• kundajelab / alzheimers_parkinsons
  Collaboration with Montine, Chang, and Montgomery labs on Alzheimers / Parkinson's ATAC-seq analysis
  ☆46Updated 5 years ago
• lanagarmire / deepimpute
  An accurate and efficient deep learning method for single-cell RNA-seq data imputation
  ☆89Updated 3 years ago
• bm2-lab / scLearn
  scLearn：Learning for single cell assignment
  ☆35Updated 11 months ago
• KrishnaswamyLab / SAUCIE
  ☆101Updated last year
• BIOINSu / SNN-Cliq
  An algorithm used to classify the cell types from single cell rna sequence data.
  ☆10Updated 4 years ago
• Su-informatics-lab / DSTG
  Deconvoluting Spatial Transcriptomics Data through Graph-based Artificial Intelligence
  ☆39Updated 3 years ago
• zcang / SpaOTsc
  ☆45Updated 3 months ago
• tarot0410 / BREMSC
  Novel joint clustering method with scRNA-seq and CITE-seq data
  ☆10Updated 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