Genome Biol 2021 Sep 1; 22(1):252
GM124922, AG052608, Department of Defense award number W81XWH-18-0401, American Diabetes Association Pathway to Stop Diabetes Accelerator Award
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.
Thibodeau, Asa; Eroglu, Alper; McGinnis, Christopher S; Lawlor, Nathan; Nehar-Belaid, Djamel; Kursawe, Romy; Marches, Radu; Conrad, Daniel N; Kuchel, George A; Gartner, Zev J; Banchereau, Jacques; Stitzel, Michael L.; Cicek, A Ercument; and Ucar, Duygu, "AMULET: a novel read count-based method for effective multiplet detection from single nucleus ATAC-seq data." (2021). Faculty Research 2021. 186.