SDImpute: A statistical block imputation method based on cell-level and gene-level information for dropouts in single-cell RNA-seq data
Fig 6
SDImpute improves differential expression analysis in the Cell Type dataset.
(A) Box plots show expression levels of marker genes in raw data and SDImpute imputed data. (B) Density plots present the differential expression of two exemplary genes (LEFTY1 and DNMT3B) between H1 cells and DECs in the bulk data, raw data, and SDImpute imputed data, respectively. (C) Venn diagram of the differentially expressed genes (p-value <0.01) detected in raw data and SDImpute imputed data by DESeq2. (D) Enriched GO terms (p-value <10−3) related to the molecular function of the up-regulated genes of H1cells were only detected in SDImpute imputed data.