Rafael A. Irizarry

Bioconductor: open software development for computational biology and bioinformatics

Tackling the widespread and critical impact of batch effects in high-throughput data

High-throughput technologies are widely used, for example to assay genetic variants, gene and protein expression, and epigenetic modifications. One often overlooked complication...

Overcoming bias and systematic errors in next generation sequencing data

Considerable time and effort has been spent in developing analysis and quality assessment methods to allow the use of microarrays in a clinical setting. As is the case for micro...

Missing data and technical variability in single-cell RNA-sequencing experiments

Until recently, high-throughput gene expression technology, such as RNA-Sequencing (RNA-seq) required hundreds of thousands of cells to produce reliable measurements. Recent tec...

Exploration, normalization, and summaries of high density oligonucleotide array probe level data

In this paper we report exploratory analyses of high-density oligonucleotide array data from the Affymetrix GeneChip system with the objective of improving upon currently used m...

A comparison of normalization methods for high densityoligonucleotide array data based on variance and bias

Abstract Motivation: When running experiments that involve multiple high density oligonucleotide arrays, it is important to remove sources of variation between arrays of non-bio...