Florian Privé
Florian Privé
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Cited by
Cited by
LDpred2: better, faster, stronger
F Privé, J Arbel, BJ Vilhjálmsson
Bioinformatics 36 (22-23), 5424-5431, 2020
Efficient analysis of large-scale genome-wide data with two R packages: bigstatsr and bigsnpr
F Privé, H Aschard, A Ziyatdinov, MGB Blum
Bioinformatics 34 (16), 2781-2787, 2018
Portability of 245 polygenic scores when derived from the UK Biobank and applied to 9 ancestry groups from the same cohort
F Privé, H Aschard, S Carmi, L Folkersen, C Hoggart, PF O’Reilly, ...
The American Journal of Human Genetics 109 (1), 12-23, 2022
Performing highly efficient genome scans for local adaptation with R package pcadapt version 4
F Privé, K Luu, BJ Vilhjálmsson, MGB Blum
Molecular Biology and Evolution 37 (7), 2153-2154, 2020
Making the most of clumping and thresholding for polygenic scores
F Privé, BJ Vilhjálmsson, H Aschard, MGB Blum
The American journal of human genetics 105 (6), 1213-1221, 2019
Improved genetic prediction of complex traits from individual-level data or summary statistics
Q Zhang, F Privé, B Vilhjálmsson, D Speed
Nature communications 12 (1), 4192, 2021
Efficient toolkit implementing best practices for principal component analysis of population genetic data
F Privé, K Luu, MGB Blum, JJ McGrath, BJ Vilhjálmsson
Bioinformatics 36 (16), 4449-4457, 2020
Polygenic scoring accuracy varies across the genetic ancestry continuum
Y Ding, K Hou, Z Xu, A Pimplaskar, E Petter, K Boulier, F Privé, ...
Nature 618 (7966), 774-781, 2023
Large uncertainty in individual polygenic risk score estimation impacts PRS-based risk stratification
Y Ding, K Hou, KS Burch, S Lapinska, F Privé, B Vilhjálmsson, ...
Nature genetics 54 (1), 30-39, 2022
Efficient implementation of penalized regression for genetic risk prediction
F Privé, H Aschard, MGB Blum
Genetics 212 (1), 65-74, 2019
Identifying and correcting for misspecifications in GWAS summary statistics and polygenic scores
F Privé, J Arbel, H Aschard, BJ Vilhjálmsson
Human Genetics and Genomics Advances, 100136, 2022
Guidelines for cell-type heterogeneity quantification based on a comparative analysis of reference-free DNA methylation deconvolution software
C Decamps, F Privé, R Bacher, D Jost, A Waguet, EA Houseman, E Lurie, ...
BMC bioinformatics 21, 1-15, 2020
Pervasive downward bias in estimates of liability-scale heritability in genome-wide association study meta-analysis: a simple solution
AD Grotzinger, J de la Fuente, F Privé, MG Nivard, EM Tucker-Drob
Biological psychiatry 93 (1), 29-36, 2023
Leveraging both individual-level genetic data and GWAS summary statistics increases polygenic prediction
C Albiñana, J Grove, JJ McGrath, E Agerbo, NR Wray, CM Bulik, ...
The American Journal of Human Genetics 108 (6), 1001-1011, 2021
Polygenic risk score, psychosocial environment and the risk of attention-deficit/hyperactivity disorder
SD Østergaard, BB Trabjerg, TD Als, CA Climent, F Privé, BJ Vilhjálmsson, ...
Translational psychiatry 10 (1), 335, 2020
Using the UK Biobank as a global reference of worldwide populations: application to measuring ancestry diversity from GWAS summary statistics
F Privé
Bioinformatics 38 (13), 3477-3480, 2022
Accounting for age of onset and family history improves power in genome-wide association studies
EM Pedersen, E Agerbo, O Plana-Ripoll, J Grove, JW Dreier, KL Musliner, ...
The American Journal of Human Genetics 109 (3), 417-432, 2022
Multi-PGS enhances polygenic prediction by combining 937 polygenic scores
C Albiñana, Z Zhu, AJ Schork, A Ingason, H Aschard, I Brikell, CM Bulik, ...
Nature communications 14 (1), 4702, 2023
VarExp: estimating variance explained by genome-wide GxE summary statistics
V Laville, AR Bentley, F Privé, X Zhu, J Gauderman, TW Winkler, ...
Bioinformatics 34 (19), 3412-3414, 2018
Estimating the effective sample size in association studies of quantitative traits
A Ziyatdinov, J Kim, D Prokopenko, F Privé, F Laporte, PR Loh, P Kraft, ...
G3 11 (6), jkab057, 2021
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