Single-cell classification and analysis, optimized for embryonic and fetal development
Project description
PySingleCellNet: a computational toolkit for the single cell analysis and comparison of embryos and embryo models
PySingleCellNet (PySCN) predicts the 'cell type' of query scRNA-seq data by Random forest multi-class classification. See Tan & Cahan 2019 for more details. PySCN includes functionality to aid in the analysis of engineered cell populations (i.e. cells derived via directed differentiation of pluripotent stem cells or via direct conversion).
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