Volume 11 Number 3 (Jul. 2021)
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IJBBB 2021 Vol.11(3): 50-57 ISSN: 2010-3638
DOI: 10.17706/ijbbb.2021.11.3.50-57

Detecting Lineage-Specific Marker Genes for Tumor Evolution Based on Single Cell Transcriptome

Kosho Murayama, Hideo Matsuda
Abstract—Marker gene detection is important for understanding tumor progression; therefore, this paper proposes a novel approach to detect marker genes for each of several lineages as tumor cells progress. The approach clusters the tumor cells into groups that reflect the drug sensitivity, resistance, and other characteristics and infers lineages undergoing transitional processes along with tumor progression and potential branching. The approach estimates continuous gene expression during the progression of each lineage and identifies marker genes by analyzing within-lineage and between-lineage differential expression. Using this method, we successfully detected a potential marker gene related to tumor drug resistance, which was not detected by a conventional cluster-based method.

Index Terms—Marker genes, single-cell RNA-seq, trajectory inference, tumor progression.

Kosho Murayama and Hideo Matsuda are with Graduate School of Information Science and Technology, Osaka University, Suita, Osaka, Japan.

Cite:Kosho Murayama, Hideo Matsuda, "Detecting Lineage-Specific Marker Genes for Tumor Evolution Based on Single Cell Transcriptome," International Journal of Bioscience, Biochemistry and Bioinformatics vol. 11, no. 3, pp. 50-57, 2021.

Copyright © 2021 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

General Information

ISSN: 2010-3638 (Online)
Abbreviated Title: Int. J. Biosci. Biochem. Bioinform.
Frequency: Quarterly 
DOI: 10.17706/IJBBB
Editor-in-Chief: Prof. Ebtisam Heikal 
Abstracting/ Indexing:  Electronic Journals Library, Chemical Abstracts Services (CAS), Engineering & Technology Digital Library, Google Scholar, and ProQuest.
E-mail: ijbbb@iap.org
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