Literature DB >> 31697351

scGEAToolbox: a Matlab toolbox for single-cell RNA sequencing data analysis.

James J Cai1,2.   

Abstract

MOTIVATION: Single-cell RNA sequencing (scRNA-seq) technology has revolutionized the way research is done in biomedical sciences. It provides an unprecedented level of resolution across individual cells for studying cell heterogeneity and gene expression variability. Analyzing scRNA-seq data is challenging though, due to the sparsity and high dimensionality of the data.
RESULTS: I developed scGEAToolbox-a Matlab toolbox for scRNA-seq data analysis. It contains a comprehensive set of functions for data normalization, feature selection, batch correction, imputation, cell clustering, trajectory/pseudotime analysis, and network construction, which can be combined and integrated to building custom workflow. While most of the functions are implemented in native Matlab, wrapper functions are provided to allow users to call the "third-party" tools developed in Matlab or other languages. Furthermore, scGEAToolbox is equipped with sophisticated graphical user interfaces (GUIs) generated with App Designer, making it an easy-to-use application for quick data processing. AVAILABILITY: https://github.com/jamesjcai/scGEAToolbox. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
© The Author(s) (2019). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Year:  2019        PMID: 31697351     DOI: 10.1093/bioinformatics/btz830

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  8 in total

1.  Single-cell RNA Sequencing Reveals How the Aryl Hydrocarbon Receptor Shapes Cellular Differentiation Potency in the Mouse Colon.

Authors:  Yongjian Yang; Daniel Osorio; Laurie A Davidson; Huajun Han; Destiny A Mullens; Arul Jayaraman; Stephen Safe; Ivan Ivanov; James J Cai; Robert S Chapkin
Journal:  Cancer Prev Res (Phila)       Date:  2021-11-22

2.  RNA-combine: a toolkit for comprehensive analyses on transcriptome data from different sequencing platforms.

Authors:  Xuemin Dong; Shanshan Dong; Shengkai Pan; Xiangjiang Zhan
Journal:  BMC Bioinformatics       Date:  2022-01-06       Impact factor: 3.169

3.  Isolation of Murine Myeloid Progenitor Populations by CD34/CD150 Surface Markers.

Authors:  Leonid Olender; Roshina Thapa; Roi Gazit
Journal:  Cells       Date:  2022-01-20       Impact factor: 6.600

4.  Hyaline cartilage differentiation of fibroblasts in regeneration and regenerative medicine.

Authors:  Ling Yu; Yu-Lieh Lin; Mingquan Yan; Tao Li; Emily Y Wu; Katherine Zimmel; Osama Qureshi; Alyssa Falck; Kirby M Sherman; Shannon S Huggins; Daniel Osorio Hurtado; Larry J Suva; Dana Gaddy; James Cai; Regina Brunauer; Lindsay A Dawson; Ken Muneoka
Journal:  Development       Date:  2022-01-28       Impact factor: 6.862

5.  scTenifoldKnk: An efficient virtual knockout tool for gene function predictions via single-cell gene regulatory network perturbation.

Authors:  Daniel Osorio; Yan Zhong; Guanxun Li; Qian Xu; Yongjian Yang; Yanan Tian; Robert S Chapkin; Jianhua Z Huang; James J Cai
Journal:  Patterns (N Y)       Date:  2022-02-01

Review 6.  Selecting gene features for unsupervised analysis of single-cell gene expression data.

Authors:  Jie Sheng; Wei Vivian Li
Journal:  Brief Bioinform       Date:  2021-11-05       Impact factor: 13.994

7.  Single-Cell Expression Variability Implies Cell Function.

Authors:  Daniel Osorio; Xue Yu; Yan Zhong; Guanxun Li; Peng Yu; Erchin Serpedin; Jianhua Z Huang; James J Cai
Journal:  Cells       Date:  2019-12-19       Impact factor: 6.600

Review 8.  Prospects and challenges of cancer systems medicine: from genes to disease networks.

Authors:  Mohammad Reza Karimi; Amir Hossein Karimi; Shamsozoha Abolmaali; Mehdi Sadeghi; Ulf Schmitz
Journal:  Brief Bioinform       Date:  2022-01-17       Impact factor: 11.622

  8 in total

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