Chromatin-accessibility estimation from single-cell ATAC-seq data with scOpen.
Zhijian LiChristoph KuppeSusanne ZieglerMingbo ChengNazanin KabganiSylvia MenzelMartin ZenkeRafael KramannIvan G CostaPublished in: Nature communications (2021)
A major drawback of single-cell ATAC-seq (scATAC-seq) is its sparsity, i.e., open chromatin regions with no reads due to loss of DNA material during the scATAC-seq protocol. Here, we propose scOpen, a computational method based on regularized non-negative matrix factorization for imputing and quantifying the open chromatin status of regulatory regions from sparse scATAC-seq experiments. We show that scOpen improves crucial downstream analysis steps of scATAC-seq data as clustering, visualization, cis-regulatory DNA interactions, and delineation of regulatory features. We demonstrate the power of scOpen to dissect regulatory changes in the development of fibrosis in the kidney. This identifies a role of Runx1 and target genes by promoting fibroblast to myofibroblast differentiation driving kidney fibrosis.
Keyphrases
- single cell
- genome wide
- rna seq
- transcription factor
- dna methylation
- high throughput
- gene expression
- minimally invasive
- dna damage
- circulating tumor
- single molecule
- electronic health record
- randomized controlled trial
- cell free
- big data
- transforming growth factor
- genome wide identification
- epithelial mesenchymal transition
- machine learning
- data analysis
- circulating tumor cells
- neural network
- nucleic acid