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R package for cell type prediction based on SVD and ML approaches

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scPred: Single cell prediction using singular value decomposition and machine learning classification

scPred is a general method to predict cell types based on variance structure decomposition. It selects the most cell type-informative principal components from a dataset and trains a prediction model for each cell type. The principal training axes are projected onto the test dataset to obtain the PCs scores for the test dataset and the trained model(s) is/are used to classify single cells.

For more details see our pre-print on bioRxiv:

scPred: Single cell prediction using singular value decomposition and machine learning classification

This introduction to scPred shows a basic workflow for cell type prediction.

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R package for cell type prediction based on SVD and ML approaches

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