单细胞基因组学数据的通用预处理

Universal preprocessing of single-cell genomics data.

作者信息

Booeshaghi A Sina, Sullivan Delaney K, Pachter Lior

机构信息

Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA.

UCLA-Caltech Medical Scientist Training Program, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.

出版信息

bioRxiv. 2023 Sep 15:2023.09.14.543267. doi: 10.1101/2023.09.14.543267.

DOI:10.1101/2023.09.14.543267

PMID:37745572

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10515959/

Abstract

We describe a workflow for preprocessing a wide variety of single-cell genomics data types. The approach is based on parsing of machine-readable assay specifications to customize inputs for , which uses and to catalog reads, error correct barcodes, and count reads. The universal preprocessing method is implemented in the Python package that is available for download at: https://github.com/cellatlas/cellatlas/.

摘要

我们描述了一种用于预处理各种单细胞基因组学数据类型的工作流程。该方法基于对机器可读检测规范的解析，以为[具体工具名称]定制输入，[具体工具名称]使用[工具1名称]和[工具2名称]对 reads 进行编目、纠错条形码并计数 reads。通用预处理方法在 Python 包[包名称]中实现，可从以下网址下载：https://github.com/cellatlas/cellatlas/ 。