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CTDquerier: a bioconductor R package for Comparative Toxicogenomics DatabaseTM data extraction, visualization and enrichment of environmental and toxicological studies.

ABSTRACT: Summary:Biomedical studies currently include a large volume of genomic and environmental factors for studying the etiology of human diseases. R/Bioconductor projects provide several tools for performing enrichment analysis at gene-pathway level, allowing researchers to develop novel hypotheses. However, there is a need to perform similar analyses at the chemicals-genes or chemicals-diseases levels to provide complementary knowledge of the causal path between chemicals and diseases. While the Comparative Toxicogenomics DatabaseTM (CTD) provides information about these relationships, there is no software for integrating it into R/Bioconductor analysis pipelines. CTDquerier helps users to easily download CTD data and integrate it in the R/Bioconductor framework. The package also contains functions for visualizing CTD data and performing enrichment analyses. We illustrate how to use the package with a real data analysis of asthma-related genes. CTDquerier is a flexible and easy-to-use Bioconductor package that provides novel hypothesis about the relationships between chemicals and diseases. Availability and implementation:CTDquerier R package is available through Bioconductor and its development version at https://github.com/isglobal-brge/CTDquerier. Supplementary information:Supplementary data are available at Bioinformatics online.

SUBMITTER: Hernandez-Ferrer C

PROVIDER: S-EPMC6137994 | biostudies-literature |

REPOSITORIES: biostudies-literature

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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.

Project description:BackgroundMiscarriage is a prevalent public health issue and many events occur before women are aware of their pregnancy, complicating research design. Thus, risk factors for miscarriage are critically understudied. Our goal was to identify environmental chemicals with a high number of interactions with miscarriage genes, based on known toxicogenomic responses.MethodsWe used miscarriage (MeSH: D000022) and chemical gene lists from the Comparative Toxicogenomics Database in human, mouse, and rat. We assessed enrichment for gene ontology biological processes among the miscarriage genes. We prioritized chemicals (n = 25) found at Superfund sites or in the blood or urine pregnant women. For chemical-disease gene sets of sufficient size (n = 13 chemicals, n = 20 comparisons), chi-squared enrichment tests and proportional reporting ratios (PRR) were calculated. We cross-validated enrichment results.ResultsMiscarriage was annotated with 121 genes and overrepresented in inflammatory response (q = 0.001), collagen metabolic process (q = 1 × 10-13), cell death (q = 0.02), and vasculature development (q = 0.005) pathways. The number of unique genes annotated to a chemical ranged from 2 (bromacil) to 5607 (atrazine). In humans, all chemicals tested were highly enriched for miscarriage gene overlap (all p < 0.001; parathion PRR = 7, cadmium PRR = 6.5, lead PRR = 3.9, arsenic PRR = 3.5, atrazine PRR = 2.8). In mice, highest enrichment (p < 0.001) was observed for naphthalene (PRR = 16.1), cadmium (PRR = 12.8), arsenic (PRR = 11.6), and carbon tetrachloride (PRR = 7.7). In rats, we observed highest enrichment (p < 0.001) for cadmium (PRR = 8.7), carbon tetrachloride (PRR = 8.3), and dieldrin (PRR = 5.3). Our findings were robust to 1000 permutations each of variable gene set sizes.ConclusionWe observed chemical gene sets (parathion, cadmium, naphthalene, carbon tetrachloride, arsenic, lead, dieldrin, and atrazine) were highly enriched for miscarriage genes. Exposures to chemicals linked to miscarriage, and thus linked to decreased probability of live birth, may limit the inclusion of fetuses susceptible to adverse birth outcomes in epidemiology studies. Our findings have critical public health implications for successful pregnancies and the interpretation of adverse impacts of environmental chemical exposures on pregnancy.

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CTDquerier: a bioconductor R package for Comparative Toxicogenomics DatabaseTM data extraction, visualization and enrichment of environmental and toxicological studies.

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