GeneTonic: an R/Bioconductor package for streamlining the interpretation of RNA-seq data

Abstract

Background The interpretation of results from transcriptome profiling experiments via RNA sequencing (RNA-seq) can be a complex task, where the essential information is distributed among different tabular and list formats—normalized expression values, results from differential expression analysis, and results from functional enrichment analyses. A number of tools and databases are widely used for the purpose of identification of relevant functional patterns, yet often their contextualization within the data and results at hand is not straightforward, especially if these analytic components are not combined together efficiently. Results We developed the software package, which serves as a comprehensive toolkit for streamlining the interpretation of functional enrichment analyses, by fully leveraging the information of expression values in a differential expression context. is implemented in R and Shiny, leveraging packages that enable HTML-based interactive visualizations for executing drilldown tasks seamlessly, viewing the data at a level of increased detail. is integrated with the core classes of existing Bioconductor workflows, and can accept the output of many widely used tools for pathway analysis, making this approach applicable to a wide range of use cases. Users can effectively navigate interlinked components (otherwise available as flat text or spreadsheet tables), bookmark features of interest during the exploration sessions, and obtain at the end a tailored HTML report, thus combining the benefits of both interactivity and reproducibility. Conclusion is distributed as an R package in the Bioconductor project (https://bioconductor.org/packages/GeneTonic/) under the MIT license. Offering both bird’s-eye views of the components of transcriptome data analysis and the detailed inspection of single genes, individual signatures, and their relationships, aims at simplifying the process of interpretation of complex and compelling RNA-seq datasets for many researchers with different expertise profiles.

Genomic insights into metabolic flux in ruby-throated hummingbirds

“…Thus, the one hour fasting targets targeted a relatively small set of genes in the muscle and liver that likely play a role in the hummingbird’s rapid switch from fed to fasted metabolism. To categorize these genes according to their gene ontology we used the Genetonic pipeline and generated functional gene-set enrichments for both the A. Colubris liver and muscle (Marini et al 2021) (Figure 4B,D) . This analysis yielded 200 statistically significant pathways (FDR < .05) in the liver and 106 in the muscle ( Table S6-7) .…”

“…Isoform level expression was quantified with Ballgown (Frazee et al 2015) and isoform level FPKM values were compared across the muscle and liver tissues. Significantly upregulated pathways were determined with the GeneTonic R package (Marini et al 2021) for both liver and muscle.…”

IRF4 deficiency vulnerates B cell progeny for leukemogenesis via somatically acquiredJak3mutations conferring IL-7 hypersensitivity

“…71 Differential expression analysis was performed with DESeq2 package, 72 setting the false discovery rate (FDR) cutoff to 0.1. DESeq2 datasets were analyzed using the GeneTonic 73 and pcaExplorer packages. To assess the possible occurrence of gene fusions, we applied two different methods, Star-Fusion (version 1.10.1) and Arriba (version 2.1.0).…”

backbone: An R package to extract network backbones

“…This is useful because data on childrens' social relations are difficult to collect directly, but they can often be inferred from bipartite projections. In the biological sciences, the backbone package has been used to examine organism co-occurrences in both plants [45] and animals [46], and is used by the genetonic package [47] to extract the backbone of gene-geneset graphs. Beyond these scientific applications, the backbone package has also been used to examine the collaboration relations among the writers, pencilers, and editors responsible for the X-men comic book series [48].…”