SansSouci

Post hoc inference via multiple testing. Project ANR-16-CE40-0019 (2016-2021).

Rationale of the project

The number and size of available data sets of different types has increased dramatically over the past twenty years. This “data deluge” has been accompanied by a shift from hypothesis-driven research to data-driven research in many scientific fields including astronomy, biology, genetics, or medicine. Analyzing and interpreting such data require innovative approaches for the simultaneous testing of a large number of biological hypotheses.

This project gathers specialists of multiple testing theory, high-dimensional data analysis, and genomics. It aims at filling a gap between the statistical guarantees provided by state-of-the-art multiple testing procedures and the actual needs of practitioners.

We propose to develop “post hoc” procedures (in the sense of Goeman and Solari, Statistical Science, 2011), which provide confidence statements on the number or proportion of false positives among any subset of hypotheses chosen by the user after analyzing the data. Both theoretical and applied aspects of post hoc multiple testing will be covered.

Main events

  • Mar 3-4, 2022: Workshop “Post-selection inference for genomic and neuroimaging data”, Toulouse. With A. Blain, G. Blanchard, S. Davenport, G. Durand, N. Enjalbert-Courrech, J. Gonzales-Delgado, A. Marandon, C. Maugis-Rabusseau, I. Meah, P. Neuvial, L. Risser, E. Roquain, M. Perrot-Dockès, B. Thirion.

  • Jun 15-19, 2020: Participation to the scientific committee of the Mathematical Methods of Modern Statistics 2 conference at CIRM (Luminy, France). This conference has been virtualized.

  • Mar 10-12, 2020: ANR meeting, Paris. With G. Blanchard, M. Perrot-Dockès, P. Neuvial, E. Roquain.

  • Dec 12-15, 2019: Participation of M. Perrot-Dockès, P. Neuvial, E. Roquain and F. Villers at MCP 2019 in Taiwan. Organization of a session on post-selection inference and multiple testing.

  • Apr 8, 2019: ANR meeting, Paris. With G. Blanchard, G. Durand, M. Perrot-Dockès, P. Neuvial, G. Rigaill, E. Roquain, B. Sadacca.

  • Feb 7-9, 2018: Workshop “Post-selection inference and multiple testing” in Toulouse. This event is part of a thematic semester Mathematics and Computer Science for biology organized by CIMI, the International Centre for Mathematics and Computer Science in Toulouse.

  • January 6, 2017: Kick-off meeting, Evry.

Preprints

  1. Notip: Non-parametric True Discovery Proportion estimation for brain imaging
    Alexandre BlainBertrand Thirion, and Pierre Neuvial
    Apr 2022
  2. Powerful and interpretable control of false discoveries in differential expression studies
    Nicolas Enjalbert-Courrech, and Pierre Neuvial
    Mar 2022
  3. False clustering rate control in mixture models
    Ariane Marandon, Tabea Rebafka, Etienne Roquain, and Nataliya Sokolovska
    Mar 2022
  4. Online multiple testing with super-uniformity reward
    Sebastian Döhler, Iqraa Meah, and Etienne Roquain
    Mar 2021
  5. Sharp multiple testing boundary for sparse sequences
    Kweku Abraham, Ismael Castillo, and Etienne Roquain
    Mar 2021
  6. Selective inference for the false discovery proportion in a Hidden Markov Model.
    Mar 2021
  7. DiscreteFDR: An R package for controlling the false discovery rate for discrete test statistics
    Guillermo Durand, Florian Junge, Sebastian Döhler, and Etienne Roquain
    Mar 2019

Papers

  1. Semi-supervised multiple testing
    David Mary, and Etienne Roquain
    arXiv preprint arXiv:2106.13501, 2021
  2. Graph inference with clustering and false discovery rate control
    Tabea Rebafka, Etienne Roquain, and Fanny Villers
    Electronic Journal of Statistics, 2022
  3. Empirical Bayes cumulative l-value multiple testing procedure for sparse sequences
    Kweku Abraham, Ismael Castillo, and Etienne Roquain
    Electronic Journal of Statistics, 2022
  4. False discovery rate control with unknown null distribution: is it possible to mimic the oracle?
    Etienne Roquain, and Nicolas Verzelen
    Annals of Statistics, to appear
  5. Error rate control for classification rules in multiclass mixture models
    Tristan Mary-Huard, Vittorio Perduca, Marie Laure Martin-Magniette, and Gilles Blanchard
    International Journal of Biostatistics, 2021
  6. Controlling the false discovery exceedance for heterogeneous tests
    Sebastian Döhler, and Etienne Roquain
    Electronic Journal of Statistics, 2020
  7. Estimating minimum effect with outlier selection
    Alexandra Carpentier, Sylvain Delattre, Etienne Roquain, and Nicolas Verzelen
    The Annals of Statistics, 2021
  8. On spike and slab empirical Bayes multiple testing
    Ismael Castillo, and Etienne Roquain
    Annals of Statistics, 2020
  9. Adaptive p-value weighting with power optimality
    Electronic Journal of Statistics, 2019
  10. Post hoc false positive control for structured hypotheses
    Scandinavian Journal of Statistics, 2020
  11. Post Hoc Confidence Bounds on False Positives Using Reference Families
    Gilles BlanchardPierre Neuvial, and Etienne Roquain
    Annals of Statistics, 2020
  12. On the post selection inference constant under restricted isometry properties
    François BachocGilles Blanchard, and Pierre Neuvial
    Electron. J. Statist., Nov 2018
  13. Continuous testing for Poisson process intensities: a new perspective on scanning statistics
    Franck Picard, Patricia Reynaud-Bouret, and Etienne Roquain
    Biometrika, Nov 2018
  14. New FDR bounds for discrete and heterogeneous tests
    Sebastian Döhler, Guillermo Durand, and Etienne Roquain
    Electron. J. Statist., Nov 2018

Participants

Toulouse  
François Bachoc Université Paul Sabatier, Institut de Mathématiques de Toulouse
Alexandre Blain Institut de Mathématiques de Toulouse and Inria Parietal
Nicolas Enjalbert-Courrech Institut de Mathématiques de Toulouse
Maria Martinez INSERM UMR 1043
Pierre Neuvial CNRS, Institut de Mathématiques de Toulouse


Evry  
Cyril Dalmasso Université d’Evry, Laboratoire de Mathématiques et Modélisation d’Evry
Jean-François Deleuze Centre National de Recherche en Génomique Humaine
Edith Le Floch Centre National de Recherche en Génomique Humaine
Guillem Rigaill INRAE, Laboratoire de Mathématiques et Modélisation d’Evry
Franck Samson INRAE, Laboratoire de Mathématiques et Modélisation d’Evry


Paris  
Sylvain Delattre Sorbonne Université, Laboratoire de Probabilités, Statistique et Modélisation
Etienne Roquain Sorbonne Université, Laboratoire de Probabilités, Statistique et Modélisation
Marie Perrot-Dockès Université de Paris, MAP5
Benjamin Sadacca Institut Curie, Immune responses to cancer


Orsay  
Gilles Blanchard Université Paris-Saclay, Institut de Mathématiques d’Orsay
Guillermo Durand Université Paris-Saclay, Institut de Mathématiques d’Orsay


Open source software

Funding

Funded by ANR CNRS Labex CIMI