Robert Nadon, Ph.D


Associate Professor
Department of Human Genetics
McGill University and Genome Quebec Innovation Centre


 

Research Interest

microarray expression

high-throughput screening (HTS) of small molecule and RNAi data
image-based high content screening (HCS)
genome-wide mRNA translation
                                

             


Selected Publications (since 2006)

Caraus, I., Alsuwailem, A. A., Nadon, R., & Makarenkov, V. (2015). Detecting and overcoming systematic bias in high-throughput screening technologies: a comprehensive review of practical issues and methodological solutions. Briefings in Bioinformatics, 16(6), 974-986.

 

Murie, C., Barette, C., Button, J., Lafanechère, L., & Nadon, R. (2015). Improving detection of rare biological events in high-throughput screens. Journal of Biomolecular Screening, 20(2), 230-241.

 

Murie, C., Barette, C., Lafanechère, L., & Nadon, R. (2014). Control Plate Regression (CPR) normalization for high throughput screens with many active features. Journal of Biomolecular Screening19, 661-671. (Invited paper for “Knowledge from Small-Molecule Screening & Profiling Data” special issue)

 

Xu, G., Barrios-Rodiles, M., Jerkic, M., Turinsky, A., Nadon, R., Vera, S., Voulgarakis, D., Wrana, J.L., Toporsian, & M., Letarte, M.  (2014). Novel Protein Interactions with Endoglin and Activin Receptor-like Kinase 1: Potential Role in Vascular Networks, Molecular Cell Proteomics13, 489-502.

 

Murie, C., Barette, C., Lafanechère, L., & Nadon, R. (2013). Single assay-wide variance experimental (SAVE) design for high-throughput screening, Bioinformatics, 29, 3067-3072.

 

Boussouar, A., Barette, C., Nadon, R., Saint-Léger, A., Broucqsault, N., Ottaviani, A., Firozhoussen,

A., Lu, Y., Lafanechère, L., Gilson, E. (2013). Acacetin and Chrysin, Two Polyphenolic Compounds, Alleviate Telomeric Position Effect in Human Cells, Molecular Therapy—Nucleic Acids2, e116.

Larsson, O., Sonenberg, N., & Nadon, R. (2011). anota: analysis of differential translation in genome wide studies. Bioinformatics, 27,1440-1441.
 
Dragiev, P., Nadon, R., & Makarenkov, V. (2011). Systematic error detection in experimental high-throughput screening. BMC Bioinformatics, 12, 25.
 
Larsson, O., Sonenberg, N., & Nadon, R. (2010). Identification of differential translation in genome wide studies. Proceedings of the National Academy of Sciences, 107, 21487-21492.
 
Malo, N., Hanley, J. A., Carlile, G., Liu, J., Pelletier, J., Thomas,D., & Nadon, R. (2010). Experimental design and statistical methods for improved hit detection in high-throughput screening.  Journal of Biomolecular Screening, 15, 990-1000.
 
Carrillo, B., Yanofsky, C., Laboissiere, S., Nadon, R., & Kearney, R. E. (2010). Methods for combining peptide intensities to estimate relative protein abundance. Bioinformatics, 26, 98-103.
 
Soleilhac, E., Nadon, R., & Lafanechere, L. (2010). High-content screening for the discovery of pharmacological compounds: advantages, challenges and potential benefits of recent technological developments. Expert Opinion on Drug Discovery, 5, 135-144.
 
Murie, C., Woody, O., Lee, A.Y. & Nadon, R. (2009). Comparison of small n statistical tests of differential expression applied to microarrays. BMC Bioinformatics, 10, 45.
 
Larsson, O. & Nadon, R. (2008). Gene expression – Time to changepoint of view? Biotechnology and Genetic Engineering Review, 25, 77-92.
 
Murie, C. and Nadon, R. (2008) A correction for estimating error when using the Local Pooled Error Statistical Test. Bioinformatics, 24, 1735-1736.
 
Makarenkov, V., Zentilli, P., Kevorkov, D., Gagarin, A., Malo, N., and Nadon, R. (2007). An efficient method for the detection and elimination of systematic error in high-throughput screening.  Bioinformatics, 23, 1648-1657.
 
Miron, M., Woody, O.Z., Marcil, A., Sladek, R., Murie C., Nadon, R. (2006). A methodology for global validation of microarray experiments. BMC Bioinformatics, 7, 333.
 
Makarenkov, V., Kevorkov, D., Zentilli, P., Gagarin, A., Malo, N. & Nadon, R. (2006) HTS-Corrector: Software for the statistical analysis and correction of experimental high-throughput screening data.  Bioinformatics, 22, 1408-1409.
 
Malo, N., Hanley, J., Cerquozzi, S., Pelletier, J., & Nadon, R. (2006) Statistical practice in high-throughput screening data analysis. Nature Biotechnology, 24, 167-175.
 
Miron, M. and Nadon, R. (2006). Inferential literacy for experimental high-throughput biology. Trends in Genetics, 22, 84-89.

  
  
  
  

  
  
  
  

 

 

Software

LPEadj:

R package for correction of the local pooled error (LPE) method to replace the asymptotic variance adjustment with an unbiased adjustment based on sample size

http://www.bioconductor.org/packages/2.12/bioc/html/LPEadj.html

citation: 

Murie, C. and Nadon, R. (2008) A correction for estimating error when using the Local Pooled Error Statistical Test.  Bioinformatics,24, 1735-1736.

 

FlexArray:

User-friendly Windows software for microarray analysis (now maintained by Genome Quebec)

http://www.gqinnovationcenter.com/services/bioinformatics/flexarray/index.aspx?l=e 

 

anota:

R package for analysis of differential translation in polysome microarray or ribosome-profiling datasets

http://www.bioconductor.org/packages/release/bioc/html/anota.html

citations :

Larsson, O., Sonenberg, N., & Nadon, R. (2011). anota: analysis of differential translation in genome wide studies.  Bioinformatics27, 1440-1441.

Larsson, O., Sonenberg, N., & Nadon, R. (2010). Identification of differential translation in genome wide studies.  Proceedings of the National Academy of Sciences107, 21487-21492.

 

HTS Corrector:

http://www.info2.uqam.ca/~makarenkov_v/HTS/home.php

User-friendly Windows software for the analysis of high-throughput screening (HTS) data (primary developer, Vladimir Makarenkov, Université du Québec à Montréal)

citation :

Makarenkov V; Kevorkov D; Zentilli P; Gagarin, A., Malo, N., Nadon, R. HTS-corrector: software for the statistical analysis and correction of experimental high-throughput screening data.Bioinformatics, 2006, 22, 1408-1409.

 

Intensity quantile estimation and mapping (IQEM):

MATLAB code for the correction of image non-uniformity bias in high-content screening (HCS) data

  
IQEM_STAGE1_STEP_1_AND_2.m

IQEM_STAGE1_STEP_3.m 

IQEM_STAGE2_STEP1.m

IQEM_STAGE2_STEP2.m 

citations :

Lo, E.Soleilhac, E., Martinez, A., Lafanechere, L., Nadon, R. (2012) Intensity quantile estimation and mapping-a novel algorithm for the correction of image non-uniformity bias in HCS data. Bioinformatics28, 2632-2639.

 

 

Statistics and dIagnostic Graphs for HTS (SIGHTS) Microsoft Excel Add-In

 

Murie, C., Barette, C., Button, J., Lafanechère, L., & Nadon, R. (in press). Improving detection of rare biological events in high-throughput screens. Journal of Biomolecular Screening. doi:10.1177/1087057114548853

 

Documentation, excel workbook, R command file

 


Contact info:

McGill University and Genome Quebec Innovation Centre, Room 6210

740 Avenue Dr. Penfield

H3A 1A5, Montreal, QC, Canada

Tel:      (514) 398-4400 ext 00284

e-mail: robert.nadon@mcgill.ca