daifengwanglab / CMOT
Cross Modality Optimal Transport for multimodal inference
☆9Updated last year
Related projects ⓘ
Alternatives and complementary repositories for CMOT
- Variational Estimation of Latent Velocity from Expression with Time-resolution☆11Updated 5 months ago
- SpatialGlue is a novel deep learning methods for spatial multi-omics data integration.☆42Updated 5 months ago
- ☆15Updated 2 years ago
- Unsupervised cell functional annotation for single-cell RNA-Seq☆22Updated last year
- ☆48Updated 7 months ago
- Transcriptional Regulatory Inference Analysis from Gene Expression (TRIAGE)☆9Updated 9 months ago
- A computational method scSemiProfiler that provides affordable single-cell data for large-scale disease cohorts using deep generative mod…☆13Updated 3 weeks ago
- Nonnegative spatial factorization for multivariate count data☆57Updated last year
- Enhancing spatial transcriptomics data by predicting the expression of unmeasured genes from a dissociated scRNA-seq data☆29Updated 4 months ago
- Single cell STEM (scSTEM) is a shiny app based R package for visualizing and clustering genes in pseudotime ordered single cell RNA-seq d…☆18Updated 2 years ago
- a unified single-cell data integration framework by optimal transport☆31Updated last month
- Scripts for data and figure generation in SAVER paper☆17Updated 3 years ago
- ☆21Updated last year
- SIMBA: SIngle-cell eMBedding Along with features☆17Updated 7 months ago
- Matilda is a multi-task framework for learning from single-cell multimodal omics data. Matilda leverages the information from the multi-m…☆19Updated this week
- Spatially aware dimension reduction for spatial transcriptomics.☆40Updated 7 months ago
- Tutorials on using latest dynamo package☆24Updated 3 weeks ago
- Imputation method for scRNA-seq based on low-rank approximation☆73Updated 11 months ago
- resVAE is a restricted latent variational autoencoder that we wrote to uncover hidden structures in gene expression data, especially usin…☆12Updated last year
- STAligner: Integrating spatial transcriptomics data across different conditions, technologies, and developmental stages☆19Updated 11 months ago
- ☆28Updated 2 months ago
- BERMUDA (Batch Effect ReMoval Using Deep Autoencoders) is a novel transfer-learning-based method for batch correction in scRNA-seq data.☆27Updated 4 years ago
- Deconvoluting Spatial Transcriptomics Data through Graph-based Artificial Intelligence☆34Updated 2 years ago
- ☆13Updated last year
- SoptSC for single cell data analysis: unsupervised inference of clustering, cell lineage, pseudotime and cell-cell communication network …☆21Updated 3 years ago
- Marker Selection by matching manifolds and elastic net☆23Updated last month
- netNMF-sc: A network regularization algorithm for dimensionality reduction and imputation of single-cell expression data☆22Updated 3 years ago
- ☆10Updated last year
- R package for transfer learning of single-cell RNA-seq denoising☆29Updated 2 years ago
- a variational autoencoder method for clustering single-cell mutation data☆10Updated 7 months ago