Ravages: An R package for the simulation and analysis of rare variants in multicategory phenotypes DOI Creative Commons
Ozvan Bocher, Gaëlle Marenne, Emmanuelle Génin

и другие.

Genetic Epidemiology, Год журнала: 2023, Номер 47(6), С. 450 - 460

Опубликована: Май 9, 2023

Abstract Current software packages for the analysis and simulations of rare variants are only available binary continuous traits. Ravages provides solutions in a single R package to perform variant association tests multicategory, phenotypes, simulate datasets under different scenarios compute statistical power. Association can be run whole genome thanks C++ implementation most functions, using either RAVA‐FIRST, recently developed strategy filter analyse genome‐wide variants, or user‐defined candidate regions. also includes simulation module that generates genetic data cases who stratified into several subgroups controls. Through comparisons with existing programmes, we show complements tools will useful study architecture complex diseases. is on CRAN at https://cran.r-project.org/web/packages/Ravages/ maintained Github https://github.com/genostats/Ravages .

Язык: Английский

Unravelling the genetic architecture of human complex traits through whole genome sequencing DOI Creative Commons
Ozvan Bocher, Cristen J. Willer, Eleftheria Zeggini

и другие.

Nature Communications, Год журнала: 2023, Номер 14(1)

Опубликована: Июнь 14, 2023

Whole genome sequencing has enabled new insights into the genetic architecture of complex traits, especially through access to low-frequency and rare variation. This Comment highlights key contributions from this technology discusses considerations for its use future perspectives.

Язык: Английский

Процитировано

12
A power-based sliding window approach to evaluate the clinical impact of rare genetic variants in the nucleotide sequence or the spatial position of the folded protein DOI Creative Commons

Elizabeth T. Cirulli,

Kelly M. Schiabor Barrett, Alexandre Bolze

и другие.

Human Genetics and Genomics Advances, Год журнала: 2024, Номер 5(3), С. 100284 - 100284

Опубликована: Март 19, 2024

SummarySystematic determination of novel variant pathogenicity remains a major challenge, even when there is an established association between gene and phenotype. Here we present Power Window (PW), sliding window technique that identifies the impactful regions using population-scale clinico-genomic datasets. By sizing analysis windows on number carriers, rather than variants or nucleotides, statistical power held constant, enabling localization clinical phenotypes removal unassociated regions. The can be built by across either nucleotide sequence (through 1D space) positions amino acids in folded protein 3D space). Using training set 350k exomes from UK Biobank (UKB), developed PW models for well-established gene-disease associations tested their accuracy two independent cohorts (117k UKB 65k sequenced at Helix Healthy Nevada Project, myGenetics, In Our DNA SC studies). significant retained median 49% qualifying carriers each (range 2%–98%), with quantitative traits showing effect size improvement 66% compared aggregating entire gene, binary traits' odds ratios improving 2.2-fold. showcases electronic health record-based analyses accurately distinguish coding genes will have high phenotypic penetrance those not, unlocking new potential human genomics research, drug development, interpretation, precision medicine.

Язык: Английский

Процитировано

3
Non-coding rare variant associations with blood traits on 166 740 UK Biobank genomes DOI Creative Commons
Diogo M. Ribeiro, Olivier Delaneau

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2023, Номер unknown

Опубликована: Дек. 4, 2023

Abstract Large biobanks with whole-genome sequencing now enable the association of non-coding rare variants complex human traits. Given that >98% genome is available for exploration, selection remains a critical yet unresolved challenge in these analyses. Here, we leverage knowledge blood gene regulation and deleteriousness scores to select pertinent blood-related We whole 59 cell count biomarker measurements 166 740 UK Biobank samples perform variant collapsing tests. identified hundreds gene-trait associations involving across However, demonstrate majority (i) reproduce known from common studies (ii) are driven by linkage disequilibrium between nearby variants. This study underscores prevailing challenges analysis need caution when interpreting results.

Язык: Английский

Процитировано

6
Next-generation sequencing strategies in venous thromboembolism: in whom and for what purpose? DOI Creative Commons
David‐Alexandre Trégouët, Pierre‐Emmanuel Morange

Journal of Thrombosis and Haemostasis, Год журнала: 2024, Номер 22(7), С. 1826 - 1834

Опубликована: Апрель 18, 2024

This invited review follows the oral presentation "To Sequence or Not to Sequence, That Is Question; But 'When, Who, Which and What For?' Is" given during State of Art session "Translational Genomics in Thrombosis: From OMICs Clinics" International Society on Thrombosis Haemostasis 2023 Congress. Emphasizing power next-generation sequencing technologies diverse strategies associated with DNA variant analysis, this highlights unresolved questions challenges their implementation both for clinical diagnosis venous thromboembolism translational research.

Язык: Английский

Процитировано

1
PSAP‐Genomic‐Regions: A Method Leveraging Population Data to Prioritize Coding and Non‐Coding Variants in Whole Genome Sequencing for Rare Disease Diagnosis DOI
Marie‐Sophie C. Ogloblinsky, Ozvan Bocher, Chaker Aloui

и другие.

Genetic Epidemiology, Год журнала: 2024, Номер unknown

Опубликована: Сен. 24, 2024

ABSTRACT The introduction of Next‐Generation Sequencing technologies in the clinics has improved rare disease diagnosis. Nonetheless, for very heterogeneous or diseases, more than half cases still lack molecular Novel strategies are needed to prioritize variants within a single individual. Population Sampling Probability (PSAP) method was developed meet this aim but only coding exome data. Here, we propose an extension PSAP non‐coding genome called PSAP‐genomic‐regions. In extension, instead considering genes as testing units (PSAP‐genes strategy), use genomic regions defined over whole that pinpoint potential functional constraints. We conceived evaluation protocol our using artificially generated exomes and genomes, by inserting pathogenic ClinVar large data sets genomes from general population. PSAP‐genomic‐regions significantly improves ranking these compared pathogenicity score alone. Using PSAP‐genomic‐regions, 50% were among top 10 genome. On real sequencing six patients with Cerebral Small Vessel Disease nine male infertility, all causal ranked 100 By revisiting used include variants, have efficient whole‐genome prioritization tool which offers promising results diagnosis unresolved diseases.

Язык: Английский

Процитировано

1
Rare Variant Association Studies: Significance, Methods, and Applications in Chronic Pain Studies DOI Creative Commons

Sahel Jahangiri Esfahani,

Xiang Ao,

Anahita Oveisi

и другие.

Osteoarthritis and Cartilage, Год журнала: 2024, Номер unknown

Опубликована: Дек. 1, 2024

Rare genetic variants, characterized by their low frequency in a population, have emerged as essential components the study of complex disease genetics. The biology rare variants underscores significance, they can exert profound effects on phenotypic variation and susceptibility. Recent advancements sequencing technologies yielded availability large-scale data such UK Biobank whole-exome (WES) cohort empowered researchers to conduct variant association studies (RVASs). This review paper discusses significance available methodologies, applications. We provide an overview studies, emphasizing relevance unraveling architecture diseases with special focus chronic pain Arthritis. Additionally, we discuss strengths limitations various testing methods, outlining typical pipeline for conducting association. encompasses crucial steps quality control WES data, annotation, testing. It serves comprehensive guide field interested datasets like cohort. Lastly, how identified be further investigated through detailed experimental animal models elucidate functional impact underlying mechanisms.

Язык: Английский

Процитировано

0
PSAP-genomic-regions: a method leveraging population data to prioritize coding and non-coding variants in whole genome sequencing for rare disease diagnosis DOI Creative Commons
Marie‐Sophie C. Ogloblinsky, Ozvan Bocher, Chaker Aloui

и другие.

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2024, Номер unknown

Опубликована: Фев. 13, 2024

Abstract The introduction of next generation sequencing technologies in the clinics has improved rare disease diagnosis. Nonetheless, for very heterogeneous or diseases, more than half cases still lack molecular Novel strategies are needed to prioritize variants within a single individual. PSAP (Population Sampling Probability) method was developed meet this aim but only coding exome data. To address challenge analysis non-coding whole genome data, we propose an extension called PSAP-genomic-regions. In extension, instead considering genes as testing units (PSAP-genes strategy), use genomic regions defined over that pinpoint potential functional constraints. We conceived evaluation protocol our using artificially-generated exomes and genomes, by inserting pathogenic ClinVar large datasets genomes from general population. found PSAP-genomic-regions significantly improves ranking these compared pathogenicity score alone. Using PSAP-genomic-regions, fifty percent variants, especially those involved splicing, were among top 10 genome. addition, approach gave similar results PSAP-genes regarding scoring variants. On real data 6 patients with Cerebral Small Vessel Disease 9 male infertility, all causal ranked 100 By revisiting used include have efficient whole-genome prioritization tool which offers promising diagnosis unresolved diseases. is implemented user-friendly Snakemake workflow, accessible both researchers clinicians can easily integrate up-to-date annotation databases. Author summary recent years, improvement DNA allowed identification many unknown diseases cases. This part due heterogeneity causes also highlights need development new methods at scale not regions. With offer strategy individual combines information on predicted frequency context work, compare other variant simulated show better performance classical based scores provides straightforward ones, often missed could explain cause undiagnosed

Язык: Английский

Процитировано

0
Ravages: An R package for the simulation and analysis of rare variants in multicategory phenotypes DOI Creative Commons
Ozvan Bocher, Gaëlle Marenne, Emmanuelle Génin

и другие.

Genetic Epidemiology, Год журнала: 2023, Номер 47(6), С. 450 - 460

Опубликована: Май 9, 2023

Abstract Current software packages for the analysis and simulations of rare variants are only available binary continuous traits. Ravages provides solutions in a single R package to perform variant association tests multicategory, phenotypes, simulate datasets under different scenarios compute statistical power. Association can be run whole genome thanks C++ implementation most functions, using either RAVA‐FIRST, recently developed strategy filter analyse genome‐wide variants, or user‐defined candidate regions. also includes simulation module that generates genetic data cases who stratified into several subgroups controls. Through comparisons with existing programmes, we show complements tools will useful study architecture complex diseases. is on CRAN at https://cran.r-project.org/web/packages/Ravages/ maintained Github https://github.com/genostats/Ravages .

Язык: Английский

Процитировано

0