南方科技大学知识苑(SUSTech KC): DPre: Computational identification of differentiation bias and genes underlying cell type conversions

题名	DPre: Computational identification of differentiation bias and genes underlying cell type conversions
作者	Steffens，Simon; Fu，Xiuling; He，Fangfang; Li，Yuhao; Babarinde，Isaac A.; Hutchins，Andrew P.
通讯作者	Hutchins，Andrew P.
发表日期	2020-03-01
DOI	10.1093/bioinformatics/btz789
发表期刊	BIOINFORMATICS 影响因子和分区
ISSN	1367-4803
EISSN	1460-2059
卷号	36 期号:5页码:1637-1639
摘要	Summary: Cells are generally resistant to cell type conversions, but can be converted by the application of growth factors, chemical inhibitors and ectopic expression of genes. However, it remains difficult to accurately identify the destination cell type or differentiation bias when these techniques are used to alter cell type. Consequently, there is demand for computational techniques that can help researchers understand both the cell type and differentiation bias. While advanced tools identifying cell types exist for single cell data and the deconvolution of mixed cell populations, the problem of exploring partially differentiated cells of indeterminate transcriptional identity has not been addressed. To fill this gap, we developed driver-predictor, which relies on scoring per gene transcriptional similarity between RNA-Seq datasets to reveal directional bias of differentiation. By comparing against large cell type transcriptome libraries or a desired target expression profile, the tool enables the user to visualize both the changes in transcriptional identity as well as the genes accounting for the cell type changes. This software will be a powerful tool for researchers to explore in vitro experiments that involve cell type conversions. Availability and implementation: Source code is open source under the MIT license and is freely available on https://github.com/LoaloaF/DPre.
相关链接	[Scopus记录]
收录类别	SCI
语种	英语
学校署名	第一 ; 通讯
资助项目	National Natural Science Foundation of China[31970589][31850410463][31850410486] ; Shenzhen Peacock plan[20170109068B]
WOS研究方向	Biochemistry & Molecular Biology ; Biotechnology & Applied Microbiology ; Computer Science ; Mathematical & Computational Biology ; Mathematics
WOS类目	Biochemical Research Methods ; Biotechnology & Applied Microbiology ; Computer Science, Interdisciplinary Applications ; Mathematical & Computational Biology ; Statistics & Probability
WOS记录号	WOS:000535656600045
出版者	OXFORD UNIV PRESS
ESI学科分类	BIOLOGY & BIOCHEMISTRY
Scopus记录号	2-s2.0-85081731957
来源库	Scopus
引用统计	被引频次[WOS]：1
成果类型	期刊论文
条目标识符	http://sustech.caswiz.com/handle/2SGJ60CL/106369
专题	生命科学学院_生物系生命科学学院
作者单位	Department of Biology,Southern University of Science and Technology,Shenzhen, Guangdong,518055,China
第一作者单位	生物系; 生命科学学院
通讯作者单位	生物系; 生命科学学院
第一作者的第一单位	生物系; 生命科学学院
推荐引用方式 GB/T 7714	Steffens，Simon,Fu，Xiuling,He，Fangfang,et al. DPre: Computational identification of differentiation bias and genes underlying cell type conversions[J]. BIOINFORMATICS,2020,36(5):1637-1639.
APA	Steffens，Simon,Fu，Xiuling,He，Fangfang,Li，Yuhao,Babarinde，Isaac A.,&Hutchins，Andrew P..(2020).DPre: Computational identification of differentiation bias and genes underlying cell type conversions.BIOINFORMATICS,36(5),1637-1639.
MLA	Steffens，Simon,et al."DPre: Computational identification of differentiation bias and genes underlying cell type conversions".BIOINFORMATICS 36.5(2020):1637-1639.