Fig. 8
From: SAE-Impute: imputation for single-cell data via subspace regression and auto-encoders
Overview of SAE-impute. A acquiring single-cell sequencing data and its systematic organization, B employing subspace regression models for predictive analyses, and C identifying dropout values, subsequently addressing them through imputation utilizing autoencoder models. Subsequently, D the imputation results are generated, and the experiments are comprehensively compared, evaluated, and analyzed