期刊
BIOINFORMATICS
卷 32, 期 14, 页码 2221-2223出版社
OXFORD UNIV PRESS
DOI: 10.1093/bioinformatics/btw174
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资金
- National Natural Science Foundation of China [31571365, 31322031, 31371288]
- Specialized Research Fund for the Doctoral Program of Higher Education [20130072110032]
Motivation: Drop-seq has recently emerged as a powerful technology to analyze gene expression from thousands of individual cells simultaneously. Currently, Drop-seq technology requires refinement and quality control (QC) steps are critical for such data analysis. There is a strong need for a convenient and comprehensive approach to obtain dedicated QC and to determine the relationships between cells for ultra-high-dimensional datasets. Results: We developed Dr. seq, a QC and analysis pipeline for Drop-seq data. By applying this pipeline, Dr. seq provides four groups of QC measurements for given Drop-seq data, including reads level, bulk-cell level, individual-cell level and cell-clustering level QC. We assessed Dr. seq on simulated and published Drop-seq data. Both assessments exhibit reliable results. Overall, Dr. seq is a comprehensive QC and analysis pipeline designed for Drop-seq data that is easily extended to other droplet-based data types. Availability and Implementation: Dr. seq is freely available at: http://www.tongji.edu.cn/similar to zhanglab/drseq and https://bitbucket.org/tarela/drseq
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