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. 2023 Dec 1;39(12):btad759.
doi: 10.1093/bioinformatics/btad759.

CoSIA: an R Bioconductor package for CrOss Species Investigation and Analysis

Anisha Haldar  1 , Vishal H Oza  1 , Nathaniel S DeVoss  1 , Amanda D Clark  1 , Brittany N Lasseigne  1
Affiliations

CoSIA: an R Bioconductor package for CrOss Species Investigation and Analysis

Anisha Haldar et al. Bioinformatics. .

Abstract

Summary: High-throughput sequencing technologies have enabled cross-species comparative transcriptomic studies; however, there are numerous challenges for these studies due to biological and technical factors. We developed CoSIA (Cross-Species Investigation and Analysis), a Bioconductor R package and Shiny app that provides an alternative framework for cross-species transcriptomic comparison of non-diseased wild-type RNA sequencing gene expression data from Bgee across tissues and species (human, mouse, rat, zebrafish, fly, and nematode) through visualization of variability, diversity, and specificity metrics.

Availability and implementation: https://github.com/lasseignelab/CoSIA.

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Conflict of interest statement

None declared.

Figures

Figure 1.
Figure 1.
(A) The CoSIA R package workflow. (B) The coefficient of variation cross-species comparison analysis depicts a lollipop plot of example data used to show median-based CV gene comparison across species. This example highlights genes with high variability (gene5), low variability (gene4, gene3, and gene1), and species-specific variability (gene2) in expression across tissues. (C) The diversity and specificity cross-species comparison analysis depicts scatter plots of example data (Supplementary Table S2) showing diversity and specificity metric for tissues and genes. This example highlights the differences in diversity and specificity across tissues (tissue1 and tissue3 in species2), and the similarities in diversity and specificity across species (gene1, gene2, gene3, and gene4 in species2). Figure was created with BioRender.com
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References

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