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scCATCH
Automatic Annotation on Cell Types of Clusters from Single-Cell RNA Sequencing Databulk2space
a spatial deconvolution method based on deep learning frameworks, which converts bulk transcriptomes into spatially resolved single-cell expression profilesscDeepSort
Cell-type Annotation for Single-cell Transcriptomics using Deep Learning with a Weighted Graph Neural NetworkSpaTalk
Knowledge-graph-based cell-cell communication inference for spatially resolved transcriptomic datascRank
A computational method to rank and infer drug-responsive cell population towards in-silico drug perturbation using a target-perturbed gene regulatory network (tpGRN) for single-cell transcriptomic dataCellTalkDB
A manually curated database of literature-supported ligand-receptor interactions in human and mousescSpace
an integrative algorithm to distinguish spatially variable cell subclusters by reconstructing cells onto a pseudo space with spatial transcriptome referencesscCube
an SRT simulator for simulating multiple spatial variability in spatial resolved transcriptomics and generating unbiased simulated SRT datascCATCH_performance_comparison
The source code and results of performance comparison on the detail of the process among scCATCH, CellAssign, Garnett, SingleR, scMap and CHETAH, and CellMatch databasescDeepSort_performance_comparison
The source code and results for different methods on annotating external testing datsets of human and mouse.CCL-cGPS
A clinical genomics-guided prioritizing strategy enables accurately selecting proper cancer cell lines for biomedical researchSpaTrio
SCOTCH
SCOTCH is a Single-Cell multi-modal integration method leveraging the Optimal Transport algorithm and a cell matCHing strategyTCMChat
Repo for TCMChat: A Generative Large Language Model for Traditional Chinese MedicinescDeepTalk
Infer cell-cell communications based on feed-forward neural networkscTITANS
Identifying key genes and cell subclusters for time-series single cell sequencing datascDisProcema
SAMBA
scCrossTalk
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