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AMULET: a Novel Read Count-Based Method for Effective Multiplet Detection from Single Nucleus ATAC-seq Data

Thibodeau Asa,Eroglu Alper,McGinnis Christopher S.,Lawlor Nathan,Nehar-Belaid Djamel,Kursawe Romy,Marches Radu,Conrad Daniel N.,Kuchel George A., NSF Center for Cellular Construction,Banchereau Jacques, University of Connecticut Health Center, Carnegie Mellon University

Genome Biology(2021)

引用 27|浏览45
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摘要
Detecting multiplets in single nucleus (sn)ATAC-seq data is challenging due to data sparsity and limited dynamic range. AMULET (ATAC-seq MULtiplet Estimation Tool) enumerates regions with greater than two uniquely aligned reads across the genome to effectively detect multiplets. We evaluate the method by generating snATAC-seq data in the human blood and pancreatic islet samples. AMULET has high precision, estimated via donor-based multiplexing, and high recall, estimated via simulated multiplets, compared to alternatives and identifies multiplets most effectively when a certain read depth of 25K median valid reads per nucleus is achieved.
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关键词
Multiplets,Doublets,Single nucleus ATAC-seq,snATAC-seq
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