Alternatives and similar repositories for SpatialEntropy

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

• andrewcharlesjones / spatial-alignment
  Alignment of spatial genomics data using deep Gaussian processes
  ☆32Updated 2 years ago
• Teichlab / celcomen
  ☆16Updated last month
• yuanzhiyuan / MENDER
  ☆12Updated last year
• ZigaSajovic / Consensus_Clustering
  An implementation of Consensus clustering in Python
  ☆62Updated last year
• labsyspharm / CRC_atlas_2022
  ☆16Updated 6 months ago
• feiyoung / PRECAST
  an efficient data integration method for multiple spatial transcriptomics data with non- cluster-relevant effects such as the complex batc…
  ☆11Updated last week
• raphael-group / paste_reproducibility
  ☆13Updated 2 years ago
• haotianteng / FICT
  FISH Iterative Cell Typing
  ☆11Updated last year
• MICS-Lab / novae
  Graph-based foundation model for spatial transcriptomics data. Zero-shot spatial domain inference, batch-effect correction, and many othe…
  ☆55Updated this week
• bioFAM / FISHFactor
  A probabilistic factor model for spatial transcriptomics data with subcellular resolution
  ☆23Updated 2 years ago
• BodenmillerGroup / SCPathology_publication
  The Single-Cell Pathology Landscape of Breast Cancer
  ☆27Updated 5 years ago
• jianhuupenn / ItClust
  Iterative transfer learning with neural network improves clustering and cell type classification in single-cell RNA-seq analysis
  ☆55Updated 4 months ago
• calico / spatial_lda
  Probabilistic topic model for identifying cellular micro-environments.
  ☆28Updated 2 years ago
• camlab-bioml / astir
  astir | Automated cell identity from single-cell multiplexed imaging and proteomics 🖥🔬✨
  ☆56Updated 3 months ago
• AltschulerWu-Lab / MUSE
  MUSE is a deep learning approach characterizing tissue composition through combined analysis of morphologies and transcriptional states f…
  ☆35Updated 3 years ago
• ElementoLab / utag
  ☆39Updated last year
• GaoLabXDU / MultiOmicsIntegrationStudy
  Experimental evaluation and comparison of multi-omics data integration methods for cancer subtyping
  ☆14Updated 4 years ago
• BiomedicalMachineLearning / Spacell
  ☆26Updated 5 years ago
• CaiGroup / seqFISH-PLUS
  ☆52Updated 4 years ago
• FridleyLab / spatialGE
  Methods for visualization and analysis of spatially-resolved gene expression
  ☆21Updated last month
• MICS-Lab / scyan
  Biology-driven deep generative model for cell-type annotation in cytometry. Scyan is an interpretable model that also corrects batch-effe…
  ☆36Updated 10 months ago
• KrishnaswamyLab / Multiscale_PHATE
  Creating multi-resolution embeddings and clusters from high dimensional data
  ☆56Updated last year
• bioFAM / mofax
  Work with trained factor models in Python
  ☆35Updated 11 months ago
• willtownes / glmpca-py
  generalized principal component analysis (GLM-PCA) implemented in python
  ☆59Updated 4 years ago
• xiaoyeye / GCNG
  using graph convolutional neural network and spaital transcriptomics data to infer cell-cell interactions
  ☆56Updated 4 years ago
• wanglab-broad / ClusterMap
  ClusterMap for multi-scale clustering analysis of spatial gene expression
  ☆46Updated 3 months ago
• biocompibens / pySpacell
  A Python package for single-cell spatial image analysis.
  ☆18Updated 2 years ago
• histocartography / athena
  Computational Framework to Analyse Spatial Heterogeneity in Visum, IMC or MIBI data sets
  ☆12Updated 3 years ago
• shangll123 / SpatialPCA
  Spatially aware dimension reduction for spatial transcriptomics.
  ☆56Updated 6 months 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