Computational Cell Cycle Analysis of Single Cell RNA-Seq Data

被引：0

作者：

Moussa, Marmar ^{[1
]}

Mandoiu, Ion I. ^{[2
]}

机构：

[1] Univ Connecticut, Sch Med, Farmington, CT 06030 USA

[2] Univ Connecticut, Storrs, CT USA

来源：

COMPUTATIONAL ADVANCES IN BIO AND MEDICAL SCIENCES | 2021年 / 12686卷

基金：

美国国家科学基金会;

关键词：

scRNA-Seq; Cell cycle; Cell order; Gene smoothness score; REVEALS; GENES;

D O I：

10.1007/978-3-030-79290-9_7

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

The variation in gene expression profiles of cells captured in different phases of the cell cycle can interfere with cell type identification and functional analysis of single cell RNA-Seq (scRNA-Seq) data. In this paper, we introduce SC1CC (SC1 Cell Cycle analysis tool), a computational approach for clustering and ordering single cell transcriptional profiles according to their progression along cell cycle phases. We also introduce a new robust metric, Gene Smoothness Score (GSS) for assessing the cell cycle based order of the cells. SC1CC is available as part of the SC1 web-based scRNA-Seq analysis pipeline, publicly accessible at https://sc1.engr.uconn.edu/.

引用

页码：71 / 87

页数：17

共 50 条

[31] ascend: R package for analysis of single-cell RNA-seq data
Senabouth, Anne
Lukowski, Samuel W.
Hernandez, Jose Alquicira
Andersen, Stacey B.
Mei, Xin
Nguyen, Quan H.
Powell, Joseph E.
[J]. GIGASCIENCE, 2019, 8 (08):
[32] SAIC: an iterative clustering approach for analysis of single cell RNA-seq data
Yang, Lu
Liu, Jiancheng
Lu, Qiang
Riggs, Arthur D.
Wu, Xiwei
[J]. BMC GENOMICS, 2017, 18
[33] Tumor genetic analysis from single-cell RNA-seq data
Tal Nawy
[J]. Nature Methods, 2018, 15 : 571 - 571
[34] scDIOR: single cell RNA-seq data IO software
Huijian Feng
Lihui Lin
Jiekai Chen
[J]. BMC Bioinformatics, 23
[35] scDIOR: single cell RNA-seq data IO software
Feng, Huijian
Lin, Lihui
Chen, Jiekai
[J]. BMC BIOINFORMATICS, 2022, 23 (01)
[36] Locality Sensitive Imputation for Single Cell RNA-Seq Data
Moussa, Marmar
Mandoiu, Ion I.
[J]. JOURNAL OF COMPUTATIONAL BIOLOGY, 2019, 26 (08) : 822 - 835
[37] Comparison of transformations for single-cell RNA-seq data
Constantin Ahlmann-Eltze
Wolfgang Huber
[J]. Nature Methods, 2023, 20 : 665 - 672
[38] Comparison of transformations for single-cell RNA-seq data
Ahlmann-Eltze, Constantin
Huber, Wolfgang
[J]. NATURE METHODS, 2023, 20 (05) : 665 - +
[39] Transmorph: a unifying computational framework for modular single-cell RNA-seq data integration
Fouche, Aziz
Chadoutaud, Loic
Delattre, Olivier
Zinovyev, Andrei
[J]. NAR GENOMICS AND BIOINFORMATICS, 2023, 5 (03)
[40] A Cell Cycle-Aware Network for Data Integration and Label Transferring of Single-Cell RNA-Seq and ATAC-Seq
Liu, Jiajia
Ma, Jian
Wen, Jianguo
Zhou, Xiaobo
[J]. ADVANCED SCIENCE, 2024,

← 1 2 3 4 5 →