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dc.contributor.authorBocher, Ozvan
dc.contributor.authorLudwig, Thomas E.
dc.contributor.authorOglobinsky, Marie-Sophie
dc.contributor.authorMarenne, Gaëlle
dc.contributor.authorDeleuze, Jean-François
dc.contributor.authorSuryakant, Suryakant
dc.contributor.authorOdeberg, Jacob
dc.contributor.authorMorange, Pierre-Emmanuel
dc.contributor.authorTrégouët, David-Alexandre
dc.contributor.authorPerdry, Hervé
dc.contributor.authorGénin, Emmanuelle
dc.date.accessioned2022-12-21T09:59:14Z
dc.date.available2022-12-21T09:59:14Z
dc.date.issued2022-09-16
dc.description.abstractRare variant association tests (RVAT) have been developed to study the contribution of rare variants widely accessible through high-throughput sequencing technologies. RVAT require to aggregate rare variants in testing units and to filter variants to retain only the most likely causal ones. In the exome, genes are natural testing units and variants are usually filtered based on their functional consequences. However, when dealing with whole-genome sequence (WGS) data, both steps are challenging. No natural biological unit is available for aggregating rare variants. Sliding windows procedures have been proposed to circumvent this difficulty, however they are blind to biological information and result in a large number of tests. We propose a new strategy to perform RVAT on WGS data: “RAVA-FIRST” (RAre Variant Association using Functionally-InfoRmed STeps) comprising three steps. (1) New testing units are defined genome-wide based on functionally-adjusted Combined Annotation Dependent Depletion (CADD) scores of variants observed in the gnomAD populations, which are referred to as “CADD regions”. (2) A region-dependent filtering of rare variants is applied in each CADD region. (3) A functionally-informed burden test is performed with sub-scores computed for each genomic category within each CADD region. Both on simulations and real data, RAVA-FIRST was found to outperform other WGS-based RVAT. Applied to a WGS dataset of venous thromboembolism patients, we identified an intergenic region on chromosome 18 enriched for rare variants in early-onset patients. This region that was missed by standard sliding windows procedures is included in a TAD region that contains a strong candidate gene. RAVA-FIRST enables new investigations of rare non-coding variants in complex diseases, facilitated by its implementation in the R package Ravages.en_US
dc.identifier.citationBocher, Ludwig, Oglobinsky, Marenne, Deleuze, Suryakant, Odeberg, Morange, Trégouët, Perdry, Génin. Testing for association with rare variants in the coding and non-coding genome: RAVA-FIRST, a new approach based on CADD deleteriousness score. PLoS Genetics. 2022;18(9)en_US
dc.identifier.cristinIDFRIDAID 2077518
dc.identifier.doi10.1371/journal.pgen.1009923
dc.identifier.issn1553-7390
dc.identifier.issn1553-7404
dc.identifier.urihttps://hdl.handle.net/10037/27907
dc.language.isoengen_US
dc.publisherPublic Library of Scienceen_US
dc.relation.journalPLoS Genetics
dc.rights.accessRightsopenAccessen_US
dc.rights.holderCopyright 2022 The Author(s)en_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0en_US
dc.rightsAttribution 4.0 International (CC BY 4.0)en_US
dc.titleTesting for association with rare variants in the coding and non-coding genome: RAVA-FIRST, a new approach based on CADD deleteriousness scoreen_US
dc.type.versionpublishedVersionen_US
dc.typeJournal articleen_US
dc.typeTidsskriftartikkelen_US
dc.typePeer revieweden_US


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Attribution 4.0 International (CC BY 4.0)
Med mindre det står noe annet, er denne innførselens lisens beskrevet som Attribution 4.0 International (CC BY 4.0)