User Tools

Site Tools


This is an old revision of the document!

Pierre Neuvial

img_01.jpg CNRS researcher (CR1)
Université d'Évry Val d'Essonne
Laboratoire de Mathématiques et Modélisation d'Évry (UMR 8071)
I.B.G.B.I., 23 Bd. de France, 91037 Évry Cedex
☎ +33 1 64 85 35 44
CV as of 2016-06
Google Scholar Citations profile

Conference Statistical analysis of massive genomic data (Evry, Nov 19-20 2015):
the videos and posters are online. See also the SAMGD web page.


Toggle publication list by year

Multiple testing

Introduction to testing and to multiple testing (by xkcd) Another introduction (in French)

  1. Asymptotic Results on Adaptive False Discovery Rate Controlling Procedures Based on Kernel Estimators (2013). Neuvial, P. Journal of Machine Learning Research Vol. 14, pp 1423−1459 [url] [pdf]
  2. On False Discovery Rate thresholding for classification under sparsity (2012). Neuvial, P. and Roquain, E. Annals of Statistics Vol. 40, No. 5, pp. 2572-2600 [url] [pdf]
  3. Asymptotic properties of false discovery rate controlling procedures under independence (2008). Neuvial, P. Electronic Journal of Statistics Vol. 2 pp. 1065–1110 [url] [pdf] [corrigendum]

Statistical methods for DNA copy number analyses

Introductory slides (12/2011, Centrale ParisTech)

  1. A performance evaluation framework of DNA copy number analysis methods in cancer studies; application to SNP array data segmentation methods (2015). Pierre-Jean, M. and Rigaill, G. and Neuvial, P. Briefings in Bioinformatics. Vol. 16 No. 4 pp. 600-615 [arxiv preprint]
  2. Stability-based comparison of class discovery methods for array-CGH profiles (2013). Brito, I. and Hupé, P. and Neuvial, P. and Barillot, E. PLoS One Vol. 8 No. 12 pp. e81458 [paper]
  3. CalMaTe: A Method and Software to Improve Allele-Specific Copy Number of SNP Arrays for Downstream Segmentation (2012). Ortiz-Estevez, M. and Aramburu, A. and Bengtsson, H. and Neuvial, P. and Rubio, A. Bioinformatics Vol. 28 No. 13 pp. 1793-1794 [paper] [R package: calmate] [R vignette]
  4. Parent-specific copy number in paired tumor-normal studies using circular binary segmentation (2011). Olshen, A.B. et al. Bioinformatics Vol. 27 No. 15 pp. 2038-2046 [paper] [R package: PSCBS] [R vignette]
  5. Statistical analysis of genotyping microarrays in cancer studies (2011). Neuvial, P. and Bengtsson, H. and Speed, T.P. Book chapter in Handbook of Statistical Bioinformatics. pp. 225-255. Springer. [paper]
  6. TumorBoost: Normalization of allele-specific tumor copy numbers from a single pair of tumor-normal genotyping microarrays (2010). Bengtsson, H. and Neuvial, P. and Speed, T.P. BMC Bioinformatics Vol. 11 No. 1 pp. 245 [paper] [R vignette (high-level)] [R vignette (low-level)] Slides: [short version],[longer version]
  7. CAPweb: a bioinformatics CGH array Analysis Platform (2006). Liva, S. et al. Nucleic Acids Res Vol. 34(Web Server issue) No. - pp. 477–481 [paper]
  8. Spatial normalization of array-CGH data (2006). Neuvial, P. and Hupé, P. et al. BMC Bioinformatics Vol. 7 No. 1 pp. 264 [paper]
  9. VAMP: visualization and analysis of array-CGH, transcriptome and other molecular profiles (2006). La Rosa, P. et al (2006). Bioinformatics Vol. 22 No. 17 pp. 2066–2073 [paper]

Statistical methods for high-throughput genomic data analyses

  1. A model for gene deregulation detection using expression data BMC Systems Biology 9(Suppl 6):S6. Picchetti, T. and Chiquet, J. and Elati, M. and Neuvial, P. and Nicolle, R. and Birmelé, E. [Hal preprint]. Presented at the GIW/InCoB 2015 conference.
  2. tmle.npvi: targeted, integrative search of associations between DNA copy number and gene expression, accounting for DNA methylation Bioinformatics (Application Note) Vol. 31(18):3054-6. Chambaz, A. and Neuvial, P. [Hal preprint][R package: tmle.npvi]
  3. Performance of a Blockwise Approach in Variable Selection using Linkage Disequilibrium Information (2015), Dehman, A. and Ambroise, C. and Neuvial, P. BMC Bioinformatics [url][R package: BALD]
  4. Estimation of a non-parametric variable importance measure of a continuous exposure (2012). Chambaz, A. and Neuvial, P. and van der Laan, M.J. Electronic journal of Statistics Vol. 6 pp 1059-1099 [paper] [extended abstract (in French)][slides (08/2012)]
  5. More Power via Graph-Structured Tests for Differential Expression of Gene Networks (2012). Jacob, L. and Neuvial, P. and Dudoit, S. Annals of Applied Statistics Vol. 6 No. 2 pp 561–600 [url] [pdf] [Bioconductor package: DEGraph] [slides (01/2012)]
  6. LICORN: LearIng COoperative Regulation Networks (2008). Elati, M. and Neuvial, P. and Bolotin-Fukuhara, M. and Barillot, E. and Radvanyi, F. and Rouveirol, C. Bioinformatics Vol. 23 No. 18 pp. 2407–2414. [paper]

Applications to cancer research

  1. Subtype and pathway specific responses to anticancer compounds in breast cancer (2012). Heiser, L. M. et al. PNAS [paper]
  2. Integrated Genomic Analyses of Ovarian Carcinoma (2011). The Cancer Genome Atlas Network. Nature Vol. 474 No. 7353 pp. 609–615 [paper]
  3. Identification of a CpG Island Methylator Phenotype that Defines a Distinct Subgroup of Glioma (2010). Noushmehr, H. et al. Cancer cell Vol. 17 No. 5 pp. 510–522 [paper]
  4. High-resolution mapping of DNA breakpoints to define true recurrences among ipsilateral breast cancers (2008). Bollet, M. et al. J Natl Cancer Inst Vol. 100 No. 1 pp. 48–58 [paper]

General audience

  1. Vers une médecine personnalisée grâce à la recherche en génomique (2013). Neuvial, P. Variances Vol. 48 pp 31–33 [paper]
  2. Tests multiples en génomique (2011). Neuvial, P. La gazette des mathématiciens No. 130 pp. 71–76 [paper]
  3. Problématiques statistiques à l'heure de la post-génomique (2009). Neuvial, P. and Bourguignon, P.-Y. Variances Vol. 35 pp. 56–60 [paper]

PhD students

  • Guillermo Durand (2015-): “Multiple testing for structured biological data”. Co-supervised with Etienne Roquain. Funded by Université Paris 6.
  • Benjamin Sadacca (2013-): “Tumoral microenvironment and treatment response in breast cancers”. Co-supervised with Fabien Reyal. Funded by Institut Curie.
  • Morgane Pierre-Jean (2013-): “Statistical methods for the analysis of structured genomic data”. Funded by École doctorale GAO, University of Évry.
  • Alia Dehman (2012-2015/12/9): “Structured sparse regression for Genome-Wide Association Studies”. Co-supervised with Christophe Ambroise. Funded by École doctorale GAO, University of Évry.



(essentially driven by the contributions of Henrik Bengtsson)

Other software from LaMME

Some co-authors

my .screenrc

members/pneuvial/welcome.1466376156.txt.gz · Last modified: 2016/06/20 00:42 by Pierre Neuvial

Page Tools