Batch Effect Correction in a Confounded Scenario: a Case Study on Gene Expression of Chornobyl Tree Frogs - IRSN - Institut de radioprotection et de sûreté nucléaire
Communication Dans Un Congrès Année : 2024

Batch Effect Correction in a Confounded Scenario: a Case Study on Gene Expression of Chornobyl Tree Frogs

Correction de l’effet par lots dans un scénario confus : une étude de cas sur l’expression génique des grenouilles arboricoles de Tchernobyl

Résumé

When large omics datasets present unwanted latent variability, a critical analysis step is to control these so-called batch effects properly. However, most batch effect-correction algorithms (BECAs) face limitations when the source of unwanted variation and the variable of interest are confounded. In this paper, we use RNA-seq data to study the effects of radiation contamination on tree frogs (Hyla orientalis) collected in the Chornobyl Exclusion Zone. We identify the site of collection of the frogs as a confounding factor in the transcriptomics analysis. We present our strategy to correct this confounding effect using the following BECAs: ComBat-seq, linear residualization, and Surrogate Variable Analysis. We show that the severe confounding between the site and radiocontamination level makes the correction step challenging. Instead, we investigate the site-to-site variability and successfully deconvolute the batch variable from the radiation level by adjusting for the population genetic structure. Our strategy allowed us to reveal the effects of low-dose radiation on the gene expression of Chornobyl tree frogs and appropriately preprocess the RNA-seq dataset for future multimodal integrative analyses.
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Dates et versions

irsn-04715789 , version 1 (01-10-2024)

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Citer

Elen Goujon, Olivier Armant, Clément Car, Jean-Marc Bonzom, Arthur Tenenhaus, et al.. Batch Effect Correction in a Confounded Scenario: a Case Study on Gene Expression of Chornobyl Tree Frogs. Computational Methods in Systems Biology, University of Pisa (Italy); IMT School for Advanced Studies Lucca (Italy), Sep 2024, Pisa (Italy), Italy. pp.89-107, ⟨10.1007/978-3-031-71671-3_8⟩. ⟨irsn-04715789⟩
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