diff --git a/README.md b/README.md index bec823f5..5d1fcfb2 100644 --- a/README.md +++ b/README.md @@ -193,14 +193,14 @@ pip install -e . | BackBone | Model | Algorithm | Year | CheckIn | | ------------------- | ------------ | ------------------------------------------------------------------------------------------------------------ | ---- | ------- | -| GNN | GraphSCI | Imputing Single-cell RNA-seq data by combining Graph Convolution and Autoencoder Neural Networks | 2021 | ✅ | +| GNN | GraphSCI | Imputing Single-cell RNA-seq data by combining Graph Convolution and Autoencoder Neural Networks | 2021 | ✅ | | GNN | scGNN (2020) | SCGNN: scRNA-seq Dropout Imputation via Induced Hierarchical Cell Similarity Graph | 2020 | P1 | -| GNN | scGNN (2021) | scGNN is a novel graph neural network framework for single-cell RNA-Seq analyses | 2021 | ✅ | +| GNN | scGNN (2021) | scGNN is a novel graph neural network framework for single-cell RNA-Seq analyses | 2021 | ✅ | | GNN | GNNImpute | An efficient scRNA-seq dropout imputation method using graph attention network | 2021 | P1 | | Graph Diffusion | MAGIC | MAGIC: A diffusion-based imputation method reveals gene-gene interactions in single-cell RNA-sequencing data | 2018 | P1 | | Probabilistic Model | scImpute | An accurate and robust imputation method scImpute for single-cell RNA-seq data | 2018 | P1 | | GAN | scGAIN | scGAIN: Single Cell RNA-seq Data Imputation using Generative Adversarial Networks | 2019 | P1 | -| NN | DeepImpute | DeepImpute: an accurate, fast, and scalable deep neural network method to impute single-cell RNA-seq data | 2019 | ✅ | +| NN | DeepImpute | DeepImpute: an accurate, fast, and scalable deep neural network method to impute single-cell RNA-seq data | 2019 | ✅ | | NN + TF | Saver-X | Transfer learning in single-cell transcriptomics improves data denoising and pattern discovery | 2019 | P1 | | Model | Evaluation Metric | Mouse Brain (current/reported) | Mouse Embryo (current/reported) | PBMC (current/reported) | @@ -215,12 +215,12 @@ pip install -e . | BackBone | Model | Algorithm | Year | CheckIn | | ----------------------- | ------------- | ------------------------------------------------------------------------------------------------------------- | ---- | ------- | -| GNN | ScDeepsort | Single-cell transcriptomics with weighted GNN | 2021 | ✅ | -| Logistic Regression | Celltypist | Cross-tissue immune cell analysis reveals tissue-specific features in humans. | 2021 | ✅ | -| Random Forest | singleCellNet | SingleCellNet: a computational tool to classify single cell RNA-Seq data across platforms and across species. | 2019 | ✅ | -| Neural Network | ACTINN | ACTINN: automated identification of cell types in single cell RNA sequencing. | 2020 | ✅ | +| GNN | ScDeepsort | Single-cell transcriptomics with weighted GNN | 2021 | ✅ | +| Logistic Regression | Celltypist | Cross-tissue immune cell analysis reveals tissue-specific features in humans. | 2021 | ✅ | +| Random Forest | singleCellNet | SingleCellNet: a computational tool to classify single cell RNA-Seq data across platforms and across species. | 2019 | ✅ | +| Neural Network | ACTINN | ACTINN: automated identification of cell types in single cell RNA sequencing. | 2020 | ✅ | | Hierarchical Clustering | SingleR | Reference-based analysis of lung single-cell sequencing reveals a transitional profibrotic macrophage. | 2019 | P1 | -| SVM | SVM | A comparison of automatic cell identification methods for single-cell RNA sequencing data. | 2018 | ✅ | +| SVM | SVM | A comparison of automatic cell identification methods for single-cell RNA sequencing data. | 2018 | ✅ | | Model | Evaluation Metric | Mouse Brain 2695 (current/reported) | Mouse Spleen 1759 (current/reported) | Mouse Kidney 203 (current/reported) | | ------------- | ----------------- | ----------------------------------- | ------------------------------------ | ----------------------------------- | @@ -234,12 +234,12 @@ pip install -e . | BackBone | Model | Algorithm | Year | CheckIn | | ----------- | ------------- | ------------------------------------------------------------------------------------------------------------ | ---- | ------- | -| GNN | graph-sc | GNN-based embedding for clustering scRNA-seq data | 2022 | ✅ | -| GNN | scTAG | ZINB-based Graph Embedding Autoencoder for Single-cell RNA-seq Interpretations | 2022 | ✅ | -| GNN | scDSC | Deep structural clustering for single-cell RNA-seq data jointly through autoencoder and graph neural network | 2022 | ✅ | +| GNN | graph-sc | GNN-based embedding for clustering scRNA-seq data | 2022 | ✅ | +| GNN | scTAG | ZINB-based Graph Embedding Autoencoder for Single-cell RNA-seq Interpretations | 2022 | ✅ | +| GNN | scDSC | Deep structural clustering for single-cell RNA-seq data jointly through autoencoder and graph neural network | 2022 | ✅ | | GNN | scGAC | scGAC: a graph attentional architecture for clustering single-cell RNA-seq data | 2022 | P1 | -| AutoEncoder | scDeepCluster | Clustering single-cell RNA-seq data with a model-based deep learning approach | 2019 | ✅ | -| AutoEncoder | scDCC | Model-based deep embedding for constrained clustering analysis of single cell RNA-seq data | 2021 | ✅ | +| AutoEncoder | scDeepCluster | Clustering single-cell RNA-seq data with a model-based deep learning approach | 2019 | ✅ | +| AutoEncoder | scDCC | Model-based deep embedding for constrained clustering analysis of single cell RNA-seq data | 2021 | ✅ | | AutoEncoder | scziDesk | Deep soft K-means clustering with self-training for single-cell RNA sequence data | 2020 | P1 | | Model | Evaluation Metric | 10x PBMC (current/reported) | Mouse ES (current/reported) | Worm Neuron (current/reported) | Mouse Bladder (current/reported) | @@ -256,12 +256,12 @@ pip install -e . | BackBone | Model | Algorithm | Year | CheckIn | | ---------------- | ------------------------ | -------------------------------------------------------------------------------------------------- | ---- | ------- | -| GNN | ScMoGCN | Graph Neural Networks for Multimodal Single-Cell Data Integration | 2022 | ✅ | +| GNN | ScMoGCN | Graph Neural Networks for Multimodal Single-Cell Data Integration | 2022 | ✅ | | GNN | ScMoLP | Link Prediction Variant of ScMoGCN | 2022 | P1 | | GNN | GRAPE | Handling Missing Data with Graph Representation Learning | 2020 | P1 | -| Generative Model | SCMM | SCMM: MIXTURE-OF-EXPERTS MULTIMODAL DEEP GENERATIVE MODEL FOR SINGLE-CELL MULTIOMICS DATA ANALYSIS | 2021 | ✅ | -| Auto-encoder | Cross-modal autoencoders | Multi-domain translation between single-cell imaging and sequencing data using autoencoders | 2021 | ✅ | -| Auto-encoder | BABEL | BABEL enables cross-modality translation between multiomic profiles at single-cell resolution | 2021 | ✅ | +| Generative Model | SCMM | SCMM: MIXTURE-OF-EXPERTS MULTIMODAL DEEP GENERATIVE MODEL FOR SINGLE-CELL MULTIOMICS DATA ANALYSIS | 2021 | ✅ | +| Auto-encoder | Cross-modal autoencoders | Multi-domain translation between single-cell imaging and sequencing data using autoencoders | 2021 | ✅ | +| Auto-encoder | BABEL | BABEL enables cross-modality translation between multiomic profiles at single-cell resolution | 2021 | ✅ | | Model | Evaluation Metric | GEX2ADT (current/reported) | ADT2GEX (current/reported) | GEX2ATAC (current/reported) | ATAC2GEX (current/reported) | | ------------------------ | ----------------- | -------------------------- | -------------------------- | --------------------------- | --------------------------- | @@ -274,10 +274,10 @@ pip install -e . | BackBone | Model | Algorithm | Year | CheckIn | | ---------------- | ------------------------ | -------------------------------------------------------------------------------------------------- | ---- | ------- | -| GNN | ScMoGCN | Graph Neural Networks for Multimodal Single-Cell Data Integration | 2022 | ✅ | +| GNN | ScMoGCN | Graph Neural Networks for Multimodal Single-Cell Data Integration | 2022 | ✅ | | GNN/Auto-ecnoder | GLUE | Multi-omics single-cell data integration and regulatory inference with graph-linked embedding | 2021 | P1 | -| Generative Model | SCMM | SCMM: MIXTURE-OF-EXPERTS MULTIMODAL DEEP GENERATIVE MODEL FOR SINGLE-CELL MULTIOMICS DATA ANALYSIS | 2021 | ✅ | -| Auto-encoder | Cross-modal autoencoders | Multi-domain translation between single-cell imaging and sequencing data using autoencoders | 2021 | ✅ | +| Generative Model | SCMM | SCMM: MIXTURE-OF-EXPERTS MULTIMODAL DEEP GENERATIVE MODEL FOR SINGLE-CELL MULTIOMICS DATA ANALYSIS | 2021 | ✅ | +| Auto-encoder | Cross-modal autoencoders | Multi-domain translation between single-cell imaging and sequencing data using autoencoders | 2021 | ✅ | | Model | Evaluation Metric | GEX2ADT (current/reported) | GEX2ATAC (current/reported) | | ------------------------ | ----------------- | -------------------------- | --------------------------- | @@ -289,11 +289,11 @@ pip install -e . | BackBone | Model | Algorithm | Year | CheckIn | | ---------------- | ------- | ----------------------------------------------------------------------------------------------------- | ---- | ------- | -| GNN | ScMoGCN | Graph Neural Networks for Multimodal Single-Cell Data Integration | 2022 | ✅ | -| Auto-encoder | scMVAE | Deep-joint-learning analysis model of single cell transcriptome and open chromatin accessibility data | 2020 | ✅ | -| Auto-encoder | scDEC | Simultaneous deep generative modelling and clustering of single-cell genomic data | 2021 | ✅ | +| GNN | ScMoGCN | Graph Neural Networks for Multimodal Single-Cell Data Integration | 2022 | ✅ | +| Auto-encoder | scMVAE | Deep-joint-learning analysis model of single cell transcriptome and open chromatin accessibility data | 2020 | ✅ | +| Auto-encoder | scDEC | Simultaneous deep generative modelling and clustering of single-cell genomic data | 2021 | ✅ | | GNN/Auto-ecnoder | GLUE | Multi-omics single-cell data integration and regulatory inference with graph-linked embedding | 2021 | P1 | -| Auto-encoder | DCCA | Deep cross-omics cycle attention model for joint analysis of single-cell multi-omics data | 2021 | ✅ | +| Auto-encoder | DCCA | Deep cross-omics cycle attention model for joint analysis of single-cell multi-omics data | 2021 | ✅ | | Model | Evaluation Metric | GEX2ADT (current/reported) | GEX2ATAC (current/reported) | | ---------- | ----------------- | -------------------------- | --------------------------- | @@ -329,11 +329,11 @@ pip install -e . | BackBone | Model | Algorithm | Year | CheckIn | | -------------------------------- | ---------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ---- | ------- | -| GNN | SpaGCN | SpaGCN: Integrating gene expression, spatial location and histology to identify spatial domains and spatially variable genes by graph convolutional network | 2021 | ✅ | -| GNN | STAGATE | Deciphering spatial domains from spatially resolved transcriptomics with adaptive graph attention auto-encoder | 2021 | ✅ | +| GNN | SpaGCN | SpaGCN: Integrating gene expression, spatial location and histology to identify spatial domains and spatially variable genes by graph convolutional network | 2021 | ✅ | +| GNN | STAGATE | Deciphering spatial domains from spatially resolved transcriptomics with adaptive graph attention auto-encoder | 2021 | ✅ | | Bayesian | BayesSpace | Spatial transcriptomics at subspot resolution with BayesSpace | 2021 | P1 | -| Pseudo-space-time (PST) Distance | stLearn | stLearn: integrating spatial location, tissue morphology and gene expression to find cell types, cell-cell interactions and spatial trajectories within undissociated tissues | 2020 | ✅ | -| Heuristic | Louvain | Fast unfolding of community hierarchies in large networks | 2008 | ✅ | +| Pseudo-space-time (PST) Distance | stLearn | stLearn: integrating spatial location, tissue morphology and gene expression to find cell types, cell-cell interactions and spatial trajectories within undissociated tissues | 2020 | ✅ | +| Heuristic | Louvain | Fast unfolding of community hierarchies in large networks | 2008 | ✅ | | Model | Evaluation Metric | 151673 (current/reported) | 151676 (current/reported) | 151507 (current/reported) | | ------- | ----------------- | ------------------------- | ------------------------- | ------------------------- | @@ -346,10 +346,10 @@ pip install -e . | BackBone | Model | Algorithm | Year | CheckIn | | -------------------------- | ------------ | ------------------------------------------------------------------------------------------------------------- | ---- | ------- | -| GNN | DSTG | DSTG: deconvoluting spatial transcriptomics data through graph-based artificial intelligence | 2021 | ✅ | -| logNormReg | SpatialDecon | Advances in mixed cell deconvolution enable quantification of cell types in spatial transcriptomic data | 2022 | ✅ | -| NNMFreg | SPOTlight | SPOTlight: seeded NMF regression to deconvolute spatial transcriptomics spots with single-cell transcriptomes | 2021 | ✅ | -| NN Linear + CAR assumption | CARD | Spatially informed cell-type deconvolution for spatial transcriptomics | 2022 | ✅ | +| GNN | DSTG | DSTG: deconvoluting spatial transcriptomics data through graph-based artificial intelligence | 2021 | ✅ | +| logNormReg | SpatialDecon | Advances in mixed cell deconvolution enable quantification of cell types in spatial transcriptomic data | 2022 | ✅ | +| NNMFreg | SPOTlight | SPOTlight: seeded NMF regression to deconvolute spatial transcriptomics spots with single-cell transcriptomes | 2021 | ✅ | +| NN Linear + CAR assumption | CARD | Spatially informed cell-type deconvolution for spatial transcriptomics | 2022 | ✅ | | Model | Evaluation Metric | GSE174746 (current/reported) | CARD Synthetic (current/reported) | SPOTlight Synthetic (current/reported) | | ------------ | ----------------- | ---------------------------- | --------------------------------- | -------------------------------------- |