Journal
BIOCHIMICA ET BIOPHYSICA ACTA-GENERAL SUBJECTS
Volume 1867, Issue 6, Pages -Publisher
ELSEVIER
DOI: 10.1016/j.bbagen.2023.130360
Keywords
scATAC-seq; Tensor decomposition; Large sparse matrices; UMAP; Single-cell applications
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TD method can be used to process large sparse matrix generated from scATAC-seq, providing UMAP embedding consistent with tissue specificity, and selecting genes associated with various biological enrichment terms and transcription factor targeting.
ATAC-seq is a powerful tool for measuring the landscape structure of a chromosome. scATAC-seq is a recently updated version of ATAC-seq performed in a single cell. The problem with scATAC-seq is data sparsity and most of the genomic sites are inaccessible. Here, tensor decomposition (TD) was used to fill in missing values. In this study, TD was applied to massive scATAC-seq datasets generated by approximately 200 bp intervals, and this number can reach 13,627,618. Currently, no other methods can deal with large sparse matrices. The proposed method could not only provide UMAP embedding that coincides with tissue specificity, but also select genes associated with various biological enrichment terms and transcription factor targeting. This suggests that TD is a useful tool to process a large sparse matrix generated from scATAC-seq.
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