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scBasset: sequence-based modeling of single-cell ATAC-seq using convolutional neural networks

scBasset: sequence-based modeling of single-cell ATAC-seq using convolutional neural networks

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_miscellaneous_2700313939

scBasset: sequence-based modeling of single-cell ATAC-seq using convolutional neural networks

About this item

Full title

scBasset: sequence-based modeling of single-cell ATAC-seq using convolutional neural networks

Author / Creator

Publisher

New York: Nature Publishing Group US

Journal title

Nature methods, 2022-09, Vol.19 (9), p.1088-1096

Language

English

Formats

Publication information

Publisher

New York: Nature Publishing Group US

More information

Scope and Contents

Contents

Single-cell assay for transposase-accessible chromatin using sequencing (scATAC) shows great promise for studying cellular heterogeneity in epigenetic landscapes, but there remain important challenges in the analysis of scATAC data due to the inherent high dimensionality and sparsity. Here we introduce scBasset, a sequence-based convolutional neura...

Alternative Titles

Full title

scBasset: sequence-based modeling of single-cell ATAC-seq using convolutional neural networks

Authors, Artists and Contributors

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_proquest_miscellaneous_2700313939

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_miscellaneous_2700313939

Other Identifiers

ISSN

1548-7091

E-ISSN

1548-7105

DOI

10.1038/s41592-022-01562-8

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