Figure 4.
- ID
- ZDB-FIG-220214-36
- Publication
- Minnoye et al., 2020 - Cross-species analysis of enhancer logic using deep learning
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Human-trained deep learning model applied to cross-species ATAC-seq data. (A) Performance of DeepMEL and Cluster-Buster (cbust) in classifying MEL and MES differential peaks in human and dog. (B) Percentage of MEL- and MES-predicted ATAC-seq regions across all samples in our cohort and in human melanocytes. Samples are ordered according to the ratio of the number of MES/MEL-predicted regions. (C) Pearson's correlation of deep layer scores between MEL-predicted regions near orthologous MEL genes between human and another species (Human-Species) or between MEL-predicted regions near different MEL genes within one species (Species-Species). P-values of unpaired two-sample Wilcoxon tests are reported. (D) (I) Evolutionary distance between human and other species in branch length units. (II) ATAC-seq profiles of the ERBB3 locus in the six species. MEL-specific enhancers that were predicted by DeepMEL and that were also found (gray) or not found (green) via liftOver of the human MEL enhancer are highlighted. (III) DeepExplainer plots for the multiple-aligned MEL-predicted ERBB3 enhancers. Red and blue dots represent point and indel mutations, respectively. |