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Visualisation of FAANG data with VizFaDa

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Abstract

The FAANG (Functional Annotation of Animal Genomes) international consortium aims to produce high- quality functional annotation of the genomes of domesticated animals [1]. Members of the community can submit their epigenomics, transcriptomics or genomics data to the FAANG Data Portal (https://data.faang.org) coordinated by a Data Coordination Centre at the EMBL-EBI [2]. FAANG data conforms to principles of findability, accessibility, interoperability and reusability (FAIR). The FAANG Data Portal allows users to find, select and download datasets relevant to their research using extensive sample and experimental metadata standards. VizFaDa aims to produce interactive data visualization through web applications intended to be integrated to the FAANG Data Portal. In order to generate those visualizations, the raw data from the portal has to be processed. During this step, quality control reports are created, providing valuable and previously unavailable insight into the quality of the data. VizFaDa focuses on RNA-seq, ChIP-seq and DNA methylation data. Interactive clustered correlation heatmap are generated, allowing the user to compare experiments from a certain assay type within a species. Experiments with similar results are clustered together. The user can use FAANG metadata to annotate the heatmap or to filter experiments from the database for a more focused visualization. Stacked epigenetic profiles are created from gene expression and epigenetic data obtained either from the same sample or from two comparable samples, notably at transcription start sites. This allow the investigation of relationship between epigenetic marks and transcription levels. Data submitted to the portal will be automatically processed and added to VizFaDa, ensuring the long-term relevance and accuracy of the project. During VizFaDa demonstration, I will be presenting features and several use-cases of the VizFaDa web application, and discuss how the community can take advantage of our work.
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Dates and versions

hal-03740369 , version 1 (29-07-2022)

Identifiers

  • HAL Id : hal-03740369 , version 1

Cite

Laura Morel, Peter Harrison, Guillaume Devailly. Visualisation of FAANG data with VizFaDa. JOBIM 2022, Jul 2022, Rennes, France. ⟨hal-03740369⟩
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