特征(语言学)
计算机科学
估计员
染色质
模式识别(心理学)
错误发现率
计算生物学
人工智能
生物
数学
统计
遗传学
基因
语言学
哲学
作者
Zhen Miao,Junhyong Kim
标识
DOI:10.1038/s41592-023-02103-7
摘要
Abstract Existing approaches to scoring single-nucleus assay for transposase-accessible chromatin with sequencing (snATAC-seq) feature matrices from sequencing reads are inconsistent, affecting downstream analyses and displaying artifacts. We show that, even with sparse single-cell data, quantitative counts are informative for estimating the regulatory state of a cell, which calls for a consistent treatment. We propose Paired-Insertion Counting as a uniform method for snATAC-seq feature characterization and provide a probability model for inferring latent insertion dynamics from snATAC-seq count matrices.
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