Pierre Neuvial

CNRS researcher (CR2) CV as of 2013-06

tel : +33 1 64 85 35 44
fax : +33 1 64 85 36 01

Laboratoire Statistique et Génome
23 boulevard de France
91037 Évry, France


Google Scholar Citations profile

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Multiple testing

An introduction (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 (to appear). Pierre-Jean, M. and Rigaill, G. and Neuvial, P. Briefings in Bioinformatics. Arxiv preprint http://arxiv.org/abs/1402.7203
  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. 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)]
  2. 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)]
  3. 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]

Teaching 2013-2014 (in French)

Démarche Statistique I

Master 1 mention SGO, Université d'Evry
Page du cours

Analyse statistique des données génomiques (a.k.a. "ASBDE")

Master 2 BIBS, Université Paris Sud
Les transparents (provisoires) de l'ensemble du cours

Page du TP

Introduction aux méthodes statistiques en biologie moléculaire

Cours de troisième année à l'ENSAE, avec Catherine Matias.
Les transparents (provisoires) de l'ensemble du cours



install.packages("jointseg", repos="http://R-Forge.R-project.org")

Alternatively, sources may also be exported as:

svn export svn://r-forge.r-project.org/svnroot/jointseg

Some co-authors

  • Henrik Bengtsson, University of California at San Francisco, Epidemiology & Biostatistics
  • Antoine Chambaz, Université Paris Ouest Nanterre, Modal'X
  • Laurent Jacob, University of California at Berkeley, Statistics
  • Etienne Roquain, Université Pierre et Marie Curie, LPMA.

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