RNfuzzyApp: an R shiny RNA-seq data analysis app for visualisation, differential expression analysis, time-series clustering and enrichment analysis

Haering, Margaux; Habermann, Bianca

doi:10.12688/f1000research.54533.2

Cited by 5 publications

(5 citation statements)

References 30 publications

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“…The Mfuzz R package 15 comprises a clustering method. The core algorithm is based on Fuzzy C‐means clustering.…”

Section: Methodsmentioning

confidence: 99%

High throughput miRNA sequencing and bioinformatics analysis identify the mesenchymal cell proliferation and apoptosis related miRNAs during fetal mice palate development

Liao

et al. 2023

The Journal of Gene Medicine

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BackgroundPalatogenesis requires a precise spatiotemporal regulation of gene expression. Recent studies indicate that microRNAs (miRNAs) are key factors in normal palatogenesis. The present study aimed to explain the regulatory mechanisms of miRNAs during palate development.MethodsPregnant ICR mice were choose at embryonic day 10.5 (E10.5). Hemotoxylin and eosin (H&E) staining was used to observe the morphological changes during the development of palatal process at embryonic day (E)13.5, E14.0, E14.5, E15.0 and E15.5. The fetal palatal tissues were collected at E13.5, E14.0, E14.5 and E15.0 to explore miRNA expression and function by high throughput sequencing and bioinformatic analysis. Mfuzz cluster analysis was used to look for miRNAs related to the fetal mice palate formation. The target genes of miRNAs were predicted by miRWalk. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis was performed base on target genes. The mesenchymal cell proliferation and apoptosis related miRNAs‐genes networks were predicted and constructed using miRWalk and Cytoscape software. The expression of mesenchymal cell proliferation and apoptosis related miRNAs at the E13.5, E14.0, E14.5, and E15.0 was detected by a quantitative real‐time PCR (RT‐qPCR) assay.ResultsH&E staining found that the palatal process grows vertically along the sides of the tongue at E13.5, the position of the tongue begins to descend and the bilateral palatal processes rise above the tongue at E14.0, the palatal process grows horizontally at E14.5, there is palatal contact fusion at E15.0, and the palatal suture disappeared at E15.5. Nine clusters of miRNA expression changes were identified in the fetal mice palate formation progression, including two reducing trends, two rising trends and five disordered trends. Next, the heatmap showed the miRNA expression from Clusters 4, 6, 9, 12 in the E13.5, E14.0, E14.5 and E15.0 groups. GO functional and KEGG pathway enrichment analysis found target genes of miRNAs in clusters involved in regulation of mesenchymal phenotype and the mitogen‐activated protein kinase (MAPK) signaling pathway. Next, mesenchymal phenotype related miRNA‐genes networks were constructed. The heatmap showing that the mesenchymal phenotype related miRNA expression of Clusters 4, 6, 9 and 12 at E13.5, E14.0, E14.5 and E15.0. Furthermore, the mesenchymal cell proliferation and apoptosis related miRNA‐gene networks were identified in Clusters 6 and 12, including mmu‐miR‐504‐3p‐Hnf1b, etc. The expression level of mesenchymal cell proliferation and apoptosis related miRNAs at the E13.5, E14.0, E14.5, and E15.0 was verified by a RT‐qPCR assay.ConclusionsFor the first time, we identified that clear dynamic miRNA expression during palate development. Furthermore, we demonstrated that mesenchymal cell proliferation and apoptosis related miRNAs, genes and the MAPK signaling pathway are important during fetal mice palate development.

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“…The Mfuzz R package 15 comprises a clustering method. The core algorithm is based on Fuzzy C‐means clustering.…”

Section: Methodsmentioning

confidence: 99%

High throughput miRNA sequencing and bioinformatics analysis identify the mesenchymal cell proliferation and apoptosis related miRNAs during fetal mice palate development

Liao

et al. 2023

The Journal of Gene Medicine

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“…The optimal number of clusters was defined using the Elbow method. 65 Core cluster proteins were used for the top 10 REACTOME pathway enrichment analyses using the Database for Annotation, Visualization, and Integrated Discovery (DAVID, version 2022q4).…”

Section: Methodsmentioning

confidence: 99%

Understanding COVID-19 progression with longitudinal peripheral blood mononuclear cell proteomics: Changes in the cellular proteome over time

Figueirêdo Leite,

Colo Brunialti,

Peçanha-Pietrobom

et al. 2023

iScience

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“…FeatureCounts ( 21 ) was used to calculate read counts. Normalization and differential expression analysis were done using DESeq2 via RNfuzzyApp ( 22 ). We compared all conditions to each other: 5-week wild type (WT) versus ATXN1_82Q_Tg, 12-week WT versus ATXN1_82Q_Tg, 5- versus 12-week WT, and finally 5- versus 12-week ATXN1_82Q_Tg.…”

Section: Methodsmentioning

confidence: 99%

The mitoXplorer 2.0 update: integrating and interpreting mitochondrial expression dynamics within a cellular context

Marchianò

Haering

Habermann

2022

Nucleic Acids Research

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Mitochondria are subcellular organelles present in almost all eukaryotic cells, which play a central role in cellular metabolism. Different tissues, health and age conditions are characterized by a difference in mitochondrial structure and composition. The visual data mining platform mitoXplorer 1.0 was developed to explore the expression dynamics of genes associated with mitochondrial functions that could help explain these differences. It, however, lacked functions aimed at integrating mitochondria in the cellular context and thus identifying regulators that help mitochondria adapt to cellular needs. To fill this gap, we upgraded the mitoXplorer platform to version 2.0 (mitoXplorer 2.0). In this upgrade, we implemented two novel integrative functions, network analysis and transcription factor enrichment, to specifically help identify signalling or transcriptional regulators of mitochondrial processes. In addition, we implemented several other novel functions to allow the platform to go beyond simple data visualization, such as an enrichment function for mitochondrial processes, a function to explore time-series data, the possibility to compare datasets across species and an IDconverter to help facilitate data upload. We demonstrate the usefulness of these functions in three specific use cases. mitoXplorer 2.0 is freely available without login at http://mitoxplorer2.ibdm.univ-mrs.fr.

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RNfuzzyApp: an R shiny RNA-seq data analysis app for visualisation, differential expression analysis, time-series clustering and enrichment analysis

Cited by 5 publications

References 30 publications

High throughput miRNA sequencing and bioinformatics analysis identify the mesenchymal cell proliferation and apoptosis related miRNAs during fetal mice palate development

High throughput miRNA sequencing and bioinformatics analysis identify the mesenchymal cell proliferation and apoptosis related miRNAs during fetal mice palate development

Understanding COVID-19 progression with longitudinal peripheral blood mononuclear cell proteomics: Changes in the cellular proteome over time

The mitoXplorer 2.0 update: integrating and interpreting mitochondrial expression dynamics within a cellular context

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