h3k4me3 chip seq data  (Biotechnology Information)

Journal: Bioinformatics

Article Title: Deep5hmC: predicting genome-wide 5-hydroxymethylcytosine landscape via a multimodal deep learning model

doi: 10.1093/bioinformatics/btae528

Figure Lengend Snippet: Comparison of unimodal and multimodal Deep5hmC for predicting binary 5hmC modification sites. When using histone modification in the epigenetic modality, two unimodal models of Deep5hmC: Deep5hmC-Seq using only DNA sequence as the model input and Deep5hmC-His using only histone modification as the model input are compared to the default multimodal Deep5hmC-Seq+His using both DNA sequence and histone modification as the model input. 5hmC peaks from the EB stage “Forebrain Organoid” and two histone marks: H3K4me1 and H3K4me3 ChIP-seq data in all brain regions from Roadmap Epigenomics are used as the training set. ( A ) AUROC reported for three compared methods. ( B ) AUPRC reported three compared methods.

Article Snippet: Without loss of generality, we utilize 5hmC peaks from four developmental stages in “Forebrain Organoid” and ChIP-seq data from two histone marks, H3K4me1 and H3K4me3, collected from all brain regions in Roadmap Epigenomics ( ).

Techniques: Comparison, Modification, Sequencing, ChIP-sequencing