---
OA_place: repository
OA_type: green
_id: '17147'
abstract:
- lang: eng
  text: Efficient utilization of large-scale biobank data is crucial for inferring
    the genetic basis of disease and predicting health outcomes from the DNA. Yet
    we lack efficient, accurate methods that scale to data where electronic health
    records are linked to whole genome sequence information. To address this issue,
    our paper develops a new algorithmic paradigm based on Approximate Message Passing
    (AMP), which is specifically tailored for genomic prediction and association testing.
    Our method yields comparable out-of-sample prediction accuracy to the state of
    the art on UK Biobank traits, whilst dramatically improving computational complexity,
    with a 8x-speed up in the run time. In addition, AMP theory provides a joint association
    testing framework, which outperforms the currently used REGENIE method, in roughly
    a third of the compute time. This first, truly large-scale application of the
    AMP framework lays the foundations for a far wider range of statistical analyses
    for hundreds of millions of variables measured on millions of people.
acknowledged_ssus:
- _id: ScienComp
acknowledgement: "This work was supported by a Lopez-Loreta Prize to MM, an SNSF Eccellenza
  Grant to MRR (PCEGP3-181181), and core funding from ISTA. The authors thank Philip
  Schniter, Matthew Stephens and Pragya Sur for valuable suggestions on an early version
  of the work. The authors acknowledge the participants and investigators of the UK
  Biobank study. High-performance\r\ncomputing was supported by the Scientific Service
  Units (SSU) of IST Austria through resources provided by Scientific Computing (SciComp)."
article_processing_charge: No
author:
- first_name: Al
  full_name: Depope, Al
  id: 0b77531d-dbcd-11ea-9d1d-a8eee0bf3830
  last_name: Depope
- first_name: Marco
  full_name: Mondelli, Marco
  id: 27EB676C-8706-11E9-9510-7717E6697425
  last_name: Mondelli
  orcid: 0000-0002-3242-7020
- first_name: Matthew Richard
  full_name: Robinson, Matthew Richard
  id: E5D42276-F5DA-11E9-8E24-6303E6697425
  last_name: Robinson
  orcid: 0000-0001-8982-8813
citation:
  ama: 'Depope A, Mondelli M, Robinson MR. Inference of genetic effects via approximate
    message passing. In: <i>2024 IEEE International Conference on Acoustics, Speech,
    and Signal Processing</i>. IEEE; 2024:13151-13155. doi:<a href="https://doi.org/10.1109/ICASSP48485.2024.10447198">10.1109/ICASSP48485.2024.10447198</a>'
  apa: 'Depope, A., Mondelli, M., &#38; Robinson, M. R. (2024). Inference of genetic
    effects via approximate message passing. In <i>2024 IEEE International Conference
    on Acoustics, Speech, and Signal Processing</i> (pp. 13151–13155). Seoul, Korea:
    IEEE. <a href="https://doi.org/10.1109/ICASSP48485.2024.10447198">https://doi.org/10.1109/ICASSP48485.2024.10447198</a>'
  chicago: Depope, Al, Marco Mondelli, and Matthew Richard Robinson. “Inference of
    Genetic Effects via Approximate Message Passing.” In <i>2024 IEEE International
    Conference on Acoustics, Speech, and Signal Processing</i>, 13151–55. IEEE, 2024.
    <a href="https://doi.org/10.1109/ICASSP48485.2024.10447198">https://doi.org/10.1109/ICASSP48485.2024.10447198</a>.
  ieee: A. Depope, M. Mondelli, and M. R. Robinson, “Inference of genetic effects
    via approximate message passing,” in <i>2024 IEEE International Conference on
    Acoustics, Speech, and Signal Processing</i>, Seoul, Korea, 2024, pp. 13151–13155.
  ista: 'Depope A, Mondelli M, Robinson MR. 2024. Inference of genetic effects via
    approximate message passing. 2024 IEEE International Conference on Acoustics,
    Speech, and Signal Processing. ICASSP: International Conference on Acoustics,
    Speech and Signal Processing, 13151–13155.'
  mla: Depope, Al, et al. “Inference of Genetic Effects via Approximate Message Passing.”
    <i>2024 IEEE International Conference on Acoustics, Speech, and Signal Processing</i>,
    IEEE, 2024, pp. 13151–55, doi:<a href="https://doi.org/10.1109/ICASSP48485.2024.10447198">10.1109/ICASSP48485.2024.10447198</a>.
  short: A. Depope, M. Mondelli, M.R. Robinson, in:, 2024 IEEE International Conference
    on Acoustics, Speech, and Signal Processing, IEEE, 2024, pp. 13151–13155.
conference:
  end_date: 2024-04-19
  location: Seoul, Korea
  name: 'ICASSP: International Conference on Acoustics, Speech and Signal Processing'
  start_date: 2024-04-14
corr_author: '1'
date_created: 2024-06-16T22:01:07Z
date_published: 2024-04-19T00:00:00Z
date_updated: 2025-11-05T07:21:31Z
day: '19'
department:
- _id: MaMo
- _id: MaRo
doi: 10.1109/ICASSP48485.2024.10447198
external_id:
  isi:
  - '001396233806078'
isi: 1
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://openreview.net/forum?id=aQYCDxfZV0
month: '04'
oa: 1
oa_version: Submitted Version
page: 13151-13155
project:
- _id: 059876FA-7A3F-11EA-A408-12923DDC885E
  name: Prix Lopez-Loretta 2019 - Marco Mondelli
- _id: 9B8D11D6-BA93-11EA-9121-9846C619BF3A
  grant_number: PCEGP3_181181
  name: Improving estimation and prediction of common complex disease risk
publication: 2024 IEEE International Conference on Acoustics, Speech, and Signal Processing
publication_identifier:
  isbn:
  - '9798350344851'
  issn:
  - 1520-6149
publication_status: published
publisher: IEEE
quality_controlled: '1'
scopus_import: '1'
status: public
title: Inference of genetic effects via approximate message passing
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2024'
...