Improving gene set enrichment analysis (GSEA) by using regulation directionality
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ABSTRACT:
PROVIDER: PRJNA860153 | ENA |
REPOSITORIES: ENA
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Project description:To infer the biological meaning from transcriptome data, it is useful to focus on genes that are regulated by the same regulator, i.e., regulons. Unfortunately, current gene set enrichment analysis (GSEA) tools do not consider whether a gene is activated or repressed by a regulator. This distinction is crucial when analyzing regulons since a regulator can work as an activator of certain genes and as a repressor of other genes, yet both sets of genes belong to the same regulon. Therefore, simply averaging expression differences of the genes of such a regulon will not properly reflect the activity of the regulator. What makes it more complicated is the fact that many genes are regulated by different transcription factors, and current transcriptome analysis tools are unable to indicate which regulator is most likely responsible for the observed expression difference of a gene. To address these challenges, we developed the gene set enrichment analysis program GINtool. Additional features of GINtool are novel graphical representations to facilitate the visualization of gene set analyses of transcriptome data, the possibility to include functional categories as gene sets for analysis, and the option to analyze expression differences within operons, which is useful when analyzing prokaryotic transcriptome and also proteome data.
2022-09-30 | GSE208571 | GEO
Project description:Directionality of developing skeletal muscles is set by mechanical forces
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Project description:Directionality Of Developing Skeletal Muscles Is Set By Mechanical Forces
| PRJNA818331 | ENA
Project description:Formation of oriented myofibrils is a key event in the development of a functional musculoskeletal system. However, the mechanisms that control orientation of myocytes, their fusion and the resulting directionality of adult muscles remain enigmatic. Here, we utilized in vivo and in vitro live imaging, CAS9/CRISPR-mediated mutagenesis in fish, genetic experiments in mice and single cell transcriptomics to demonstrate that individual myocyte polarization and subsequent orientation depend on cell stretch imposed by skeletal expansion. Our data revealed that upon migration, individual facial myocytes form unpolarized clusters corresponding to future muscle groups. These clusters undergo oriented stretch and alignment during embryonic growth. Experimental in vivo perturbations of cartilage shape, size and distribution caused disruptions in directionality and number of myofibrils. Controlled in vitro 2D and 3D experiments applying continuous tension via artificial attachment points demonstrated a sufficiency for mechanical forces to instruct coherent polarization of myocyte populations. Consistently, perturbations of cartilage extension revealed a role of the developing skeleton in the directional outgrowth of non-muscle soft tissues during limb and facial morphogenesis.
2020-10-27 | GSE160098 | GEO
Project description:Formation of oriented myofibrils is a key event in the development of a functional musculoskeletal system. However, the mechanisms that control orientation of myocytes, their fusion and the resulting directionality of adult muscles remain enigmatic. Here, we utilized in vivo and in vitro live imaging, CAS9/CRISPR-mediated mutagenesis in fish, genetic experiments in mice and single cell transcriptomics to demonstrate that individual myocyte polarization and subsequent orientation depend on cell stretch imposed by skeletal expansion. Our data revealed that upon migration, individual facial myocytes form unpolarized clusters corresponding to future muscle groups. These clusters undergo oriented stretch and alignment during embryonic growth. Experimental in vivo perturbations of cartilage shape, size and distribution caused disruptions in directionality and number of myofibrils. Controlled in vitro 2D and 3D experiments applying continuous tension via artificial attachment points demonstrated a sufficiency for mechanical forces to instruct coherent polarization of myocyte populations. Consistently, perturbations of cartilage extension revealed a role of the developing skeleton in the directional outgrowth of non-muscle soft tissues during limb and facial morphogenesis.
2022-03-24 | GSE199093 | GEO
Project description:Cardiovascular disease (CVD) is the leading cause of death worldwide. To this end, human cardiac organoids (hCOs) have been developed for improved organotypic CVD modeling over conventional in vivo animal models. Utilizing human cells, hCOs hold great promise to bridge key gaps in CVD research pertaining to human-specific conditions. hCOs are multicellular 3D models which resemble heart structure and function. Varying hCOs fabrication techniques leads to functional and phenotypic differences. To investigate heterogeneity across hCO platforms, we performed a transcriptomic analysis utilizing bulk RNA-sequencing from four previously published unique hCO studies. We further compared selected hCOs to 2D and 3D hiPSC-derived cardiomyocytes (hiPSC-CMs), as well as fetal and adult human myocardium bulk RNA-sequencing samples. Upon investigation utilizing Principal Component Analysis (PCA), K-means clustering analysis of key genes, and further downstream analyses such as Gene Set Enrichment (GSEA), Gene Set Variation (GSVA), and GO term enrichment, we found that hCO fabrication method influences maturity and cellular heterogeneity across models. Thus, we propose that adjustment of fabrication method will result in an hCO with a defined maturity and transcriptomic profile to facilitate its specified applications, in turn maximizing its modeling potential.
2024-06-01 | GSE262739 | GEO
Project description:Differential gene expression (DGE) studies often suffer from poor interpretability of their primary results, i.e., thousands of differentially expressed genes. This has led to the introduction of gene set analysis (GSA) methods that aim at identifying interpretable global effects by grouping genes into sets of common context, such as, molecular pathways, biological function or tissue localization. In practice, GSA often results in hundreds of differentially regulated gene sets. Similar to the genes they contain, gene sets are often regulated in a correlative fashion because they share many of their genes or they describe related processes. Using these kind of neighborhood information to construct networks of gene sets allows to identify highly connected sub-networks as well as poorly connected islands or singletons. We show here how topological information and other network features can be used to filter and prioritize gene sets in routine DGE studies. Community detection in combination with automatic labeling and the network representation of gene set clusters further constitute an appealing and intuitive visualization of GSA results. The RICHNET workflow described here does not require human intervention and can thus be conveniently incorporated in automated analysis pipelines.
| S-EPMC6446501 | biostudies-literature
Project description:Deregulated pathways identified from transcriptome data of two sample groups have played a key role in many genomic studies. Gene-set enrichment analysis (GSEA) has been commonly used for pathway or functional analysis of microarray data, and it is also being applied to RNA-seq data. However, most RNA-seq data so far have only small replicates. This enforces to apply the gene-permuting GSEA method (or preranked GSEA) which results in a great number of false positives due to the inter-gene correlation in each gene-set. We demonstrate that incorporating the absolute gene statistic in one-tailed GSEA considerably improves the false-positive control and the overall discriminatory ability of the gene-permuting GSEA methods for RNA-seq data. To test the performance, a simulation method to generate correlated read counts within a gene-set was newly developed, and a dozen of currently available RNA-seq enrichment analysis methods were compared, where the proposed methods outperformed others that do not account for the inter-gene correlation. Analysis of real RNA-seq data also supported the proposed methods in terms of false positive control, ranks of true positives and biological relevance. An efficient R package (AbsFilterGSEA) coded with C++ (Rcpp) is available from CRAN.
| S-EPMC5102490 | biostudies-literature
Project description:Experimental conditions improving in solution target enrichment for ancient DNA
| PRJEB13983 | ENA
Project description:DNA molecular combing-based replication fork directionality profiling
| PRJNA689720 | ENA