Experimental Design and Statistical Analysis for traditional and high-throughput studies / Data


Developing statistical methods for biotechnology data and advocating good study design and statistical analysis practices. To date, his lab has developed biostatistical methods for analysis of microarray gene expression, high-throughput screening (HTS) of small molecules and RNAi data, image-based high content screening (HCS), metabolomics and genome-wide polysomal profiling.

Exemples de plateformes
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

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

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

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Statistics and dIagnostic Graphs for HTS (SIGHTS) R Package for analysis of High-throughput Screening data

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Nous Joindre

Dr. Robert Nadon
Associate Professor, Dept Human Genetics
McGill University