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DEconvolution of Tissue profiles with Accurate Interpretation of Locus-specific Signals DeepDETAILS
DeepDETAILS is a novel deep-learning framework that reconstructs cell-type-specific genomic signals from bulk tissue data with base-pair precision. Its core innovation is the use of readily available single-cell ATAC-seq data as a reference to deconvolve various other genomic datasets, such as those from nascent transcript sequencing or ChIP-seq.