Alternatives and similar repositories for Consensus_Clustering

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

• ChihyunPark / DNN_for_ADprediction
  ☆20Updated 4 years ago
• KrishnaswamyLab / Multiscale_PHATE
  Creating multi-resolution embeddings and clusters from high dimensional data
  ☆56Updated last year
• 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
• bowang87 / SIMLR_PY
  Python Implementation of SIMLR for single-cell visualization and analysis
  ☆24Updated 3 years ago
• cantinilab / momix-notebook
  ☆66Updated 2 years ago
• nicococo / scRNA
  Python framework for single-cell RNA-seq clustering with special focus on transfer learning.
  ☆18Updated 6 years ago
• KrishnaswamyLab / AAnet
  Archetypal Analysis network (AAnet)
  ☆37Updated 9 months ago
• KrishnaswamyLab / SAUCIE
  ☆101Updated last year
• rezacsedu / Deep-Learning-for-Clustering-in-Bioinformatics
  Deep Learning-based Clustering Approaches for Bioinformatics
  ☆141Updated 4 years ago
• trungnt13 / sisua
  SemI-SUpervised generative Autoencoder models for single cell data
  ☆18Updated 4 years ago
• vandijklab / scGAT
  Code to reproduce results in Ravindra NG* & Sehanobish A* et al. 2020, "Disease State Prediction From Single-Cell Data Using Graph Attent…
  ☆18Updated 5 years ago
• scvae / scvae
  Deep learning for single-cell transcript counts
  ☆89Updated 8 months ago
• CaiGroup / seqFISH-PLUS
  ☆52Updated 4 years ago
• zhangxiaoyu11 / OmiVAE
  End-to-end deep learning model for low dimensional latent space extraction and multi-class classification on multi-omics datasets.
  ☆34Updated 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
• willtownes / glmpca-py
  generalized principal component analysis (GLM-PCA) implemented in python
  ☆60Updated 4 years ago
• dpeerlab / PhenoGraph
  Subpopulation detection in high-dimensional single-cell data
  ☆71Updated 5 years ago
• xiaoyeye / GCNG
  using graph convolutional neural network and spaital transcriptomics data to infer cell-cell interactions
  ☆56Updated 4 years ago
• rmarkello / snfpy
  Similarity network fusion in Python
  ☆88Updated 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
• ttgump / scDCC
  scDCC: Single Cell Deep Constrained Clustering
  ☆41Updated last year
• BoyuLyu / DL-based-Tumor-Classification
  Deep Learning Based Tumor Type Classification Using Gene Expression Data
  ☆26Updated last year
• davidbuterez / CellVGAE
  An unsupervised scRNA-seq analysis workflow with graph attention networks
  ☆26Updated 2 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
• Christensen-Lab-Dartmouth / PyMethylProcess
  Preprocessing methylation pipeline, written in python. Easy to use and highly parallelized.
  ☆36Updated 5 years ago
• GaoLabXDU / MultiOmicsIntegrationStudy
  Experimental evaluation and comparison of multi-omics data integration methods for cancer subtyping
  ☆14Updated 4 years ago
• xiaoyeye / CNNC
  covolutional neural network based coexpression analysis
  ☆79Updated 5 years ago
• maxconway / SNFtool
  Similarity Network Fusion
  ☆37Updated 10 years ago
• auranic / Elastic-principal-graphs
  Matlab implementation of the Elastic Principal Graphs (ElPiGraph) method
  ☆14Updated 2 years ago
• zeochoy / tcga-embedding
  using shallow neural network layer (embedding) to infer gene-gene/sample relationship from gene expression data
  ☆21Updated 7 years ago