Document Type

Article

Publication Date

9-1-2021

Publication Title

Genome biology

Keywords

JGM

JAX Source

Genome Biol 2021 Sep 1; 22(1):252

Volume

22

Issue

1

First Page

252

Last Page

252

ISSN

1474-760X

PMID

34465366

DOI

https://doi.org/10.1186/s13059-021-02469-x

Grant

GM124922, AG052608, Department of Defense award number W81XWH-18-0401, American Diabetes Association Pathway to Stop Diabetes Accelerator Award

Abstract

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.

Comments

We thank the Beck and Lee labs for their feedback and suggestions on how to handle repetitive element sequences within our software. We thank Jane Cha for her help with enhancing schematic figures for this project. We thank Ucar/Stitzel lab members for their constructive feedback. We thank Dr. Motakis for help with naming our software. Finally,we thank the Jackson Laboratory Single Cell and Genome Technologies cores for generating snATAC-seq data.

This article is licensed under a Creative Commons Attribution 4.0 International License.

Download

Share

COinS