S
Sandrine Dudoit
Researcher at University of California, Berkeley
Publications - 152
Citations - 43339
Sandrine Dudoit is an academic researcher from University of California, Berkeley. The author has contributed to research in topics: Multiple comparisons problem & Estimator. The author has an hindex of 60, co-authored 147 publications receiving 38789 citations. Previous affiliations of Sandrine Dudoit include Stanford University & California Institute for Quantitative Biosciences.
Papers
More filters
Journal ArticleDOI
Bioconductor: open software development for computational biology and bioinformatics
Robert Gentleman,Vincent J. Carey,Douglas M. Bates,Benjamin M. Bolstad,Marcel Dettling,Sandrine Dudoit,Byron Ellis,Laurent Gautier,Yongchao Ge,Jeff Gentry,Kurt Hornik,Torsten Hothorn,Wolfgang Huber,Stefano Maria Iacus,Rafael A. Irizarry,Friedrich Leisch,Cheng Li,Martin Maechler,A. J. Rossini,Günther Sawitzki,Colin A. Smith,Gordon K. Smyth,Luke Tierney,Jean Yang,Jianhua Zhang +24 more
TL;DR: Details of the aims and methods of Bioconductor, the collaborative creation of extensible software for computational biology and bioinformatics, and current challenges are described.
Journal ArticleDOI
Normalization for cDNA microarray data: a robust composite method addressing single and multiple slide systematic variation
TL;DR: This article proposes normalization methods that are based on robust local regression and account for intensity and spatial dependence in dye biases for different types of cDNA microarray experiments.
Journal ArticleDOI
Comparison of discrimination methods for the classification of tumors using gene expression data
TL;DR: Different discrimination methods for the classification of tumors based on gene expression data include nearest-neighbor classifiers, linear discriminant analysis, and classification trees, which are applied to datasets from three recently published cancer gene expression studies.
Journal ArticleDOI
Evaluation of statistical methods for normalization and differential expression in mRNA-Seq experiments
TL;DR: This work provides a detailed evaluation of statistical methods for normalization and differential expression analysis of Illumina transcriptome sequencing (mRNA-Seq) data and investigates the impact of the read count normalization method on DE results, and proposes more general quantile-based normalization procedures.
Journal Article
STATISTICAL METHODS FOR IDENTIFYING DIFFERENTIALLY EXPRESSED GENES IN REPLICATED cDNA MICROARRAY EXPERIMENTS
TL;DR: Differentially expressed genes are identified based on adjusted p-values for a multiple testing procedure which strongly controls the family-wise Type I error rate and takes into account the dependence structure between the gene expression levels.