Dataset Information

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

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), an 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.

Contact

Brittany Lasseigne ( bnp0001@uab.edu ).

Supplementary information

See Supplementary Files.

SUBMITTER: Haldar A

PROVIDER: S-EPMC10168259 | biostudies-literature | 2023 Jul

REPOSITORIES: biostudies-literature

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Publications

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

Haldar Anisha A Oza Vishal H VH DeVoss Nathaniel S NS Clark Amanda D AD Lasseigne Brittany N BN

bioRxiv : the preprint server for biology 20230720

PMID: 37163017

Similar Datasets

Project description:BACKGROUND: The variety of DNA microarray formats and datasets presently available offers an unprecedented opportunity to perform insightful comparisons of heterogeneous data. Cross-species studies, in particular, have the power of identifying conserved, functionally important molecular processes. Validation of discoveries can now often be performed in readily available public data which frequently requires cross-platform studies.Cross-platform and cross-species analyses require matching probes on different microarray formats. This can be achieved using the information in microarray annotations and additional molecular biology databases, such as orthology databases. Although annotations and other biological information are stored using modern database models (e.g. relational), they are very often distributed and shared as tables in text files, i.e. flat file databases. This common flat database format thus provides a simple and robust solution to flexibly integrate various sources of information and a basis for the combined analysis of heterogeneous gene expression profiles. RESULTS: We provide annotationTools, a Bioconductor-compliant R package to annotate microarray experiments and integrate heterogeneous gene expression profiles using annotation and other molecular biology information available as flat file databases. First, annotationTools contains a specialized set of functions for mining this widely used database format in a systematic manner. It thus offers a straightforward solution for annotating microarray experiments. Second, building on these basic functions and relying on the combination of information from several databases, it provides tools to easily perform cross-species analyses of gene expression data.Here, we present two example applications of annotationTools that are of direct relevance for the analysis of heterogeneous gene expression profiles, namely a cross-platform mapping of probes and a cross-species mapping of orthologous probes using different orthology databases. We also show how to perform an explorative comparison of disease-related transcriptional changes in human patients and in a genetic mouse model. CONCLUSION: The R package annotationTools provides a simple solution to handle microarray annotation and orthology tables, as well as other flat molecular biology databases. Thereby, it allows easy integration and analysis of heterogeneous microarray experiments across different technological platforms or species.

Dataset Information

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

Summary

Availability and implementation

Contact

Supplementary information

Publications

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

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