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  2. Agricultural Education A1
  3. ICAR-Indian Agricultural Statistics Research Institute B7
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Please use this identifier to cite or link to this item: http://krishi.icar.gov.in/jspui/handle/123456789/68631
Title: A Comprehensive Survey of Differential Expression Analysis Approaches in Single Cell RNA-sequencing Studies
Other Titles: Not Available
Authors: Samarendra Das
Anil Rai
M. Merchant
Mathew Cave
S.N. Rai
ICAR Data Use Licennce: http://krishi.icar.gov.in/PDF/ICAR_Data_Use_Licence.pdf
Author's Affiliated institute: ICAR::Indian Agricultural Statistics Research Institute
University of Louisville, USA
James G Brown Cancer Center, University of Louisville, Louisville, KY 40202, USA
Published/ Complete Date: 2021-12-02
Project Code: Not Available
Keywords: scRNA-seq
differential expression
statistical models
multiple criteria decision making
combined data settings
TOPSIS
Publisher: MDPI Publisher
Citation: Das, S., Rai, A., Merchant, M., Cave, M., and Rai, S.N. (2021). A Comprehensive Survey of Differential Expression Analysis Approaches in Single Cell RNA-sequencing Studies. Genes, 12(12), 1947. doi.org/10.3390/genes12121947.
Series/Report no.: Not Available;
Abstract/Description: Single-cell RNA-sequencing (scRNA-seq) is a recent high-throughput sequencing technique for studying gene expressions at the cell level. Differential Expression (DE) analysis is a major downstream analysis of scRNA-seq data. DE analysis the in presence of noises from different sources remains a key challenge in scRNA-seq. Earlier practices for addressing this involved borrowing methods from bulk RNA-seq, which are based on non-zero differences in average expressions of genes across cell populations. Later, several methods specifically designed for scRNA-seq were developed. To provide guidance on choosing an appropriate tool or developing a new one, it is necessary to comprehensively study the performance of DE analysis methods. Here, we provide a review and classification of different DE approaches adapted from bulk RNA-seq practice as well as those specifically designed for scRNA-seq. We also evaluate the performance of 19 widely used methods in terms of 13 performance metrics on 11 real scRNA-seq datasets. Our findings suggest that some bulk RNA-seq methods are quite competitive with the single-cell methods and their performance depends on the underlying models, DE test statistic(s), and data characteristics. Further, it is difficult to obtain the method which will be best-performing globally through individual performance criterion. However, the multi-criteria and combined-data analysis indicates that DECENT and EBSeq are the best options for DE analysis. The results also reveal the similarities among the tested methods in terms of detecting common DE genes. Our evaluation provides proper guidelines for selecting the proper tool which performs best under particular experimental settings in the context of the scRNA-seq.
Description: Not Available
ISSN: Not Available
Type(s) of content: Research Paper
Sponsors: This study was fully supported by Netaji Subhas-ICAR International Fellowship, OM No. 18(02)/2016-EQR/Edn. (SD), of Indian Council of Agricultural Research (ICAR), New Delhi, India. It was supported in part by Wendell Cherry Chair in Clinical Trial Research Fund (SNR), multiple National Institutes of Health (NIH), USA grants (SNR) (5P20GM113226, PI: McClain; 1P42ES023716, PI: Srivastava; 5P30GM127607-02, PI: Jones; 1P20GM125504-01, PI: Lamont; 2U54HL120163, PI: Bhatnagar/Robertson; 1P20GM135004, PI: Yan; 1R35ES0238373-01, PI: Cave; 1R01ES029846, PI: Bhatnagar; 1R01ES027778-01A1, PI: States; P30ES030283, PI: States; R01AA028436, PI: Merchant), and Kentucky Council on Postsecondary Education grant (PON2 415 1900002934, PI: Chesney).
Language: English
Name of Journal: Genes
Journal Type: research paper
NAAS Rating: 10.06
Impact Factor: 4.06
Volume No.: 12(12)
Page Number: 1947
Name of the Division/Regional Station: Not Available
Source, DOI or any other URL: doi.org/10.3390/genes12121947
URI: http://krishi.icar.gov.in/jspui/handle/123456789/68631
Appears in Collections:AEdu-IASRI-Publication

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