scAVENGERS: a genotype-based deconvolution of individuals in multiplexed single-cell ATAC-seq data without reference genotypes

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dc.contributor.authorHan, Seungbeomko
dc.contributor.authorKim, Kyukwangko
dc.contributor.authorPark, Seongwanko
dc.contributor.authorLee, Andrew J.ko
dc.contributor.authorChun, Hyonhoko
dc.contributor.authorJung, Inkyungko
dc.date.accessioned2023-01-28T02:00:20Z-
dc.date.available2023-01-28T02:00:20Z-
dc.date.created2023-01-28-
dc.date.created2023-01-28-
dc.date.created2023-01-28-
dc.date.created2023-01-28-
dc.date.created2023-01-28-
dc.date.issued2022-10-
dc.identifier.citationNAR GENOMICS AND BIOINFORMATICS, v.4, no.4-
dc.identifier.issn2631-9268-
dc.identifier.urihttp://hdl.handle.net/10203/304733-
dc.description.abstractGenetic differences inferred from sequencing reads can be used for demultiplexing of pooled single-cell RNA-seq (scRNA-seq) data across multiple donors without WGS-based reference genotypes. However, such methods could not be directly applied to single-cell ATAC-seq (scATAC-seq) data owing to the lower read coverage for each variant compared to scRNA-seq. We propose a new software, scATAC-seq Variant-based EstimatioN for GEnotype ReSolving (scAVENGERS), which resolves this issue by calling more individual-specific germline variants and using an optimized mixture model for the scATAC-seq. The benchmark conducted with three synthetic multiplexed scATAC-seq datasets of peripheral blood mononuclear cells and prefrontal cortex tissues showed outstanding performance compared to existing methods in terms of accuracy, doublet detection, and a portion of donor-assigned cells. Furthermore, analyzing the effect of the improved sections provided insight into handling pooled single-cell data in the future.-
dc.languageEnglish-
dc.publisherOXFORD UNIV PRESS-
dc.titlescAVENGERS: a genotype-based deconvolution of individuals in multiplexed single-cell ATAC-seq data without reference genotypes-
dc.typeArticle-
dc.identifier.scopusid2-s2.0-85160418708-
dc.type.rimsART-
dc.citation.volume4-
dc.citation.issue4-
dc.citation.publicationnameNAR GENOMICS AND BIOINFORMATICS-
dc.identifier.doi10.1093/nargab/lqac095-
dc.contributor.localauthorChun, Hyonho-
dc.contributor.localauthorJung, Inkyung-
dc.contributor.nonIdAuthorHan, Seungbeom-
dc.description.isOpenAccessN-
dc.type.journalArticleArticle-
dc.subject.keywordPlusCHROMATIN ACCESSIBILITY-
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