Literature DB >> 35652733

scGAD: single-cell gene associating domain scores for exploratory analysis of scHi-C data.

Siqi Shen1, Ye Zheng2, Sündüz Keleş1,3.   

Abstract

SUMMARY: Quantitative tools are needed to leverage the unprecedented resolution of single-cell high-throughput chromatin conformation (scHi-C) data and integrate it with other single-cell data modalities. We present single-cell gene associating domain (scGAD) scores as a dimension reduction and exploratory analysis tool for scHi-C data. scGAD enables summarization at the gene unit while accounting for inherent gene-level genomic biases. Low-dimensional projections with scGAD capture clustering of cells based on their 3D structures. Significant chromatin interactions within and between cell types can be identified with scGAD. We further show that scGAD facilitates the integration of scHi-C data with other single-cell data modalities by enabling its projection onto reference low-dimensional embeddings. This multi-modal data integration provides an automated and refined cell-type annotation for scHi-C data. AVAILABILITY: scGAD is part of the BandNorm R package at https://sshen82.github.io/BandNorm/articles/scGAD-tutorial.html. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
© The Author(s) (2022). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Entities:  

Year:  2022        PMID: 35652733      PMCID: PMC9272792          DOI: 10.1093/bioinformatics/btac372

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.931


  17 in total

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Journal:  Nature       Date:  2021-10-06       Impact factor: 49.962

3.  Robust single-cell Hi-C clustering by convolution- and random-walk-based imputation.

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9.  Simultaneous profiling of 3D genome structure and DNA methylation in single human cells.

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10.  HeLa-CCL2 cell heterogeneity studied by single-cell DNA and RNA sequencing.

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  1 in total

1.  Normalization and de-noising of single-cell Hi-C data with BandNorm and scVI-3D.

Authors:  Ye Zheng; Siqi Shen; Sündüz Keleş
Journal:  Genome Biol       Date:  2022-10-17       Impact factor: 17.906

  1 in total

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