Fig. 6: Identification by TRAPT of transcriptional regulators associated with cell fate and tissue identity. | Nature Communications

Fig. 6: Identification by TRAPT of transcriptional regulators associated with cell fate and tissue identity.

From: TRAPT: a multi-stage fused deep learning framework for predicting transcriptional regulators based on large-scale epigenomic data

Fig. 6

a Visualization of principal component analysis (PCA) derived from scRNA-seq data. b Classic model of the landscape of hematopoietic differentiation. c Heat map displaying the MRR scores of lineage-specific transcriptional regulators obtained by TRAPT across directions of cell differentiation. d Heat map showing the top 100 TRs according to MRR scores, predicted by TRAPT across 30 human tissues. The right side shows the top 10 TRs predicted for each of the 30 tissues by TRAPT. The TRs for each tissue are ranked in descending order by their MRR scores, with different colors denoting distinct tissues. The TRs in varying colors below the heatmap represent tissue-specific TRs from the top-10 predicted TRs. The smaller heat maps below highlight important TRs within their respective tissues.

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