MBCdeg4: A modified clustering-based method for identifying differentially expressed genes from RNA-seq data
RNA-seq is a commonly employed methodology for the measurement of transcriptomes, particularly for the identification of differentially expressed genes (DEGs) between different conditions or groups. In a previous report, we described a clustering-based method for identifying DEGs, designated MBCdeg1...
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Elsevier
2025-06-01
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2215016124006009 |
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| author | Chiharu Ichikawa Koji Kadota |
| author_facet | Chiharu Ichikawa Koji Kadota |
| author_sort | Chiharu Ichikawa |
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| description | RNA-seq is a commonly employed methodology for the measurement of transcriptomes, particularly for the identification of differentially expressed genes (DEGs) between different conditions or groups. In a previous report, we described a clustering-based method for identifying DEGs, designated MBCdeg1 and MBCdeg2. and a modified version, MBCdeg3. This study presents a further improved version, designated MBCdeg4. The four versions of MBCdeg employ an R package, designated MBCluster.Seq, internally. The sole distinction between them is the manner of data normalization. MBCdeg4 employs normalization factors derived from a robust normalization algorithm, designated as DEGES. Seven competing methods were compared: the four versions of MBCdeg and three conventional R packages (edgeR, DESeq2, and TCC). MBCdeg4 demonstrated superior performance in a multitude of simulation scenarios involving RNA-seq count data. Therefore, MBCdeg4 is recommended for use in preference to the earlier versions, MBCdeg1–3. • MBCdeg4 is a method for both identification and classification of DEGs from RNA-seq count data. • MBCdeg4 is available as an R function and performs well in a wide variety of simulation scenarios. |
| format | Article |
| id | doaj-art-be10fa3caa9741a6bd0294fda4c2e3f4 |
| institution | Kabale University |
| issn | 2215-0161 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | Elsevier |
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| spelling | doaj-art-be10fa3caa9741a6bd0294fda4c2e3f42025-01-08T04:53:00ZengElsevierMethodsX2215-01612025-06-0114103149MBCdeg4: A modified clustering-based method for identifying differentially expressed genes from RNA-seq dataChiharu Ichikawa0Koji Kadota1Graduate School of Agricultural and Life Sciences, The University of Tokyo, Yayoi 1-1-1, Bunkyo-ku, Tokyo 113-8657, JapanGraduate School of Agricultural and Life Sciences, The University of Tokyo, Yayoi 1-1-1, Bunkyo-ku, Tokyo 113-8657, Japan; Interfaculty Initiative in Information Studies, The University of Tokyo, Hongo 7-3-1, Bunkyo-ku, Tokyo 113-0033, Japan; Collaborative Research Institute for Innovative Microbiology, The University of Tokyo, Yayoi 1-1-1, Bunkyo-ku, Tokyo 113-8657, Japan; Corresponding author.RNA-seq is a commonly employed methodology for the measurement of transcriptomes, particularly for the identification of differentially expressed genes (DEGs) between different conditions or groups. In a previous report, we described a clustering-based method for identifying DEGs, designated MBCdeg1 and MBCdeg2. and a modified version, MBCdeg3. This study presents a further improved version, designated MBCdeg4. The four versions of MBCdeg employ an R package, designated MBCluster.Seq, internally. The sole distinction between them is the manner of data normalization. MBCdeg4 employs normalization factors derived from a robust normalization algorithm, designated as DEGES. Seven competing methods were compared: the four versions of MBCdeg and three conventional R packages (edgeR, DESeq2, and TCC). MBCdeg4 demonstrated superior performance in a multitude of simulation scenarios involving RNA-seq count data. Therefore, MBCdeg4 is recommended for use in preference to the earlier versions, MBCdeg1–3. • MBCdeg4 is a method for both identification and classification of DEGs from RNA-seq count data. • MBCdeg4 is available as an R function and performs well in a wide variety of simulation scenarios.http://www.sciencedirect.com/science/article/pii/S2215016124006009MBCdeg4 |
| spellingShingle | Chiharu Ichikawa Koji Kadota MBCdeg4: A modified clustering-based method for identifying differentially expressed genes from RNA-seq data MethodsX MBCdeg4 |
| title | MBCdeg4: A modified clustering-based method for identifying differentially expressed genes from RNA-seq data |
| title_full | MBCdeg4: A modified clustering-based method for identifying differentially expressed genes from RNA-seq data |
| title_fullStr | MBCdeg4: A modified clustering-based method for identifying differentially expressed genes from RNA-seq data |
| title_full_unstemmed | MBCdeg4: A modified clustering-based method for identifying differentially expressed genes from RNA-seq data |
| title_short | MBCdeg4: A modified clustering-based method for identifying differentially expressed genes from RNA-seq data |
| title_sort | mbcdeg4 a modified clustering based method for identifying differentially expressed genes from rna seq data |
| topic | MBCdeg4 |
| url | http://www.sciencedirect.com/science/article/pii/S2215016124006009 |
| work_keys_str_mv | AT chiharuichikawa mbcdeg4amodifiedclusteringbasedmethodforidentifyingdifferentiallyexpressedgenesfromrnaseqdata AT kojikadota mbcdeg4amodifiedclusteringbasedmethodforidentifyingdifferentiallyexpressedgenesfromrnaseqdata |