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Chromatin-accessibility estimation from single-cell ATAC data with scOpen

ABSTRACT: We propose a computational method for quantifying the open chromatin status of regulatory regions from single cell ATAC-seq experiments. scOpen, which is based on positive-unlabeled learning of matrices, is able to estimate the probability that a region is open at a given cell mitigating the sparsity of scATAC-seq matrices. We demonstrate that scOpen improves all down-stream analysis steps of scATAC-seq data as clustering, visualization, detection of transcription factors and chromatin conformation in several scATAC-seq data.

ORGANISM(S): Mus musculus Homo sapiens

PROVIDER: GSE139950 | GEO | 2021/09/17

REPOSITORIES: GEO

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