Topic: scrnaseq-datasets Goto Github
Some thing interesting about scrnaseq-datasets
Some thing interesting about scrnaseq-datasets
scrnaseq-datasets,R package: {rfca} Random forest-based cell annotation methods for scRNAseq analysis. {rfca} contains methods which identifies cell types using machine learning trained on a diversity of cell types, without the need for a labelled training dataset. It also allows you to train your own cell prediction models with your own labels (cell type, subtype, cell state, cluster number etc). This package is best suited for researchers who want to annotate their datasets in a quick and unbiased way, phenotype their datasets based on cell identity proportions, and discover common cell states across different datasets and disease models.
User: kimberle9
Home Page: https://kimberle9.github.io/rfca/articles/vignette.html
scrnaseq-datasets,Repo linked to our recent publication in Science Advances
User: olivierraineteausbri
scrnaseq-datasets,The main repository for ACTIVA: realistic single-cell RNA-seq generation with automatic cell-type identification using introspective variational autoencoders
Organization: sindilab
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