Zhao Chengchen, Hu Sheng'en, Huo Xiao, Zhang Yong
Translational Medical Center for Stem Cell Therapy & Institute for Regenerative Medicine, Shanghai East Hospital, School of Life Science and Technology, Shanghai Key Laboratory of Signaling and Disease Research, Tongji University, Shanghai, China.
PLoS One. 2017 Jul 3;12(7):e0180583. doi: 10.1371/journal.pone.0180583. eCollection 2017.
An increasing number of single cell transcriptome and epigenome technologies, including single cell ATAC-seq (scATAC-seq), have been recently developed as powerful tools to analyze the features of many individual cells simultaneously. However, the methods and software were designed for one certain data type and only for single cell transcriptome data. A systematic approach for epigenome data and multiple types of transcriptome data is needed to control data quality and to perform cell-to-cell heterogeneity analysis on these ultra-high-dimensional transcriptome and epigenome datasets. Here we developed Dr.seq2, a Quality Control (QC) and analysis pipeline for multiple types of single cell transcriptome and epigenome data, including scATAC-seq and Drop-ChIP data. Application of this pipeline provides four groups of QC measurements and different analyses, including cell heterogeneity analysis. Dr.seq2 produced reliable results on published single cell transcriptome and epigenome datasets. Overall, Dr.seq2 is a systematic and comprehensive QC and analysis pipeline designed for parallel single cell transcriptome and epigenome data. Dr.seq2 is freely available at: http://www.tongji.edu.cn/~zhanglab/drseq2/ and https://github.com/ChengchenZhao/DrSeq2.
包括单细胞ATAC测序（scATAC-seq）在内，越来越多的单细胞转录组和表观基因组技术最近已被开发出来，作为同时分析许多单个细胞特征的强大工具。然而，这些方法和软件是为一种特定的数据类型设计的，且仅适用于单细胞转录组数据。需要一种用于表观基因组数据和多种类型转录组数据的系统方法，以控制数据质量，并对这些超高维转录组和表观基因组数据集进行细胞间异质性分析。在此，我们开发了Dr.seq2，这是一种用于多种类型单细胞转录组和表观基因组数据（包括scATAC-seq和Drop-ChIP数据）的质量控制（QC）和分析流程。该流程的应用提供了四组QC测量值和不同的分析，包括细胞异质性分析。Dr.seq2在已发表的单细胞转录组和表观基因组数据集上产生了可靠的结果。总体而言，Dr.seq2是一个为并行单细胞转录组和表观基因组数据设计的系统且全面的QC和分析流程。可在以下网址免费获取Dr.seq2：http://www.tongji.edu.cn/~zhanglab/drseq2/ 以及https://github.com/ChengchenZhao/DrSeq2 。
