Irizarry, Rafael A.

Salmon provides fast and bias-aware quantification of transcript expression

Patro, R., Duggal, G., Love, M. I., Irizarry, R. A., & Kingsford, C. (2017) · Nature Methods

Genomics and Phylogenetic StudiesSingle-cell and spatial transcriptomics

Cited by 12,700

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

Irizarry, R. A. (2003) · Biostatistics

Gene expression and cancer classificationGenomics and Phylogenetic Studies

Cited by 10,603

MAGeCK enables robust identification of essential genes from genome-scale CRISPR/Cas9 knockout screens

Li, W., Xu, H., Xiao, T., Cong, L., Love, M. I., Zhang, F., Irizarry, R. A., Liu, J. S., Brown, M., & Liu, X. S. (2014) · Genome Biology

CRISPR and Genetic EngineeringChromatin Remodeling and Cancer

Cited by 2,684

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

Leek, J. T., Scharpf, R. B., Bravo, H. C., Simcha, D., Langmead, B., Johnson, W. E., Geman, D., Baggerly, K., & Irizarry, R. A. (2010) · Nature Reviews Genetics

Gene expression and cancer classificationBioinformatics and Genomic Networks

Cited by 2,196

The human colon cancer methylome shows similar hypo- and hypermethylation at conserved tissue-specific CpG island shores

Irizarry, R. A., Ladd-Acosta, C., Wen, B., Wu, Z., Montano, C., Onyango, P., Cui, H., Gabo, K., Rongione, M., Webster, M., et al. (2009) · Nature Genetics

Epigenetics and DNA MethylationGenetic Syndromes and Imprinting

Cited by 2,177

Robust decomposition of cell type mixtures in spatial transcriptomics

Cable, D. M., Murray, E., Zou, L. S., Goeva, A., Macosko, E. Z., Chen, F., & Irizarry, R. A. (2022) · Nature Biotechnology

Single-cell and spatial transcriptomicsGene expression and cancer classification

Cited by 1,487

Accounting for cellular heterogeneity is critical in epigenome-wide association studies

Jaffe, A. E., & Irizarry, R. A. (2014) · Genome Biology

Epigenetics and DNA MethylationGenetic Associations and Epidemiology

Cited by 1,067

Multiple-laboratory comparison of microarray platforms

Irizarry, R. A., Warren, D., Spencer, F., Kim, I. F., Biswal, S., Frank, B. C., Gabrielson, E., Garcia, J. G. N., Geoghegan, J., Germino, G., et al. (2005) · Nature Methods

Gene expression and cancer classificationMolecular Biology Techniques and Applications

Cited by 862

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

Hicks, S. C., Townes, F. W., Teng, M., & Irizarry, R. A. (2018) · Biostatistics

Single-cell and spatial transcriptomicsGene expression and cancer classification

Cited by 635

Missing Data and Technical Variability in Single-Cell RNA-Sequencing Experiments

Hicks, S. C., Townes, F. W., Teng, M., & Irizarry, R. A. (2015) · Biostatistics

Single-cell and spatial transcriptomicsGene expression and cancer classification

Cited by 625

Removing technical variability in RNA-seq data using conditional quantile normalization

Hansen, K. D., Irizarry, R. A., & WU, Z. (2012) · Biostatistics

Gene expression and cancer classificationGenomics and Phylogenetic Studies

Cited by 607

Feature selection and dimension reduction for single-cell RNA-Seq based on a multinomial model

Townes, F. W., Hicks, S. C., Aryee, M. J., & Irizarry, R. A. (2019) · Genome Biology

Single-cell and spatial transcriptomicsGene expression and cancer classification

Cited by 471

Excess deaths associated with covid-19 pandemic in 2020: age and sex disaggregated time series analysis in 29 high income countries

Islam, N., Shkolnikov, V. M., Acosta, R. J., Klimkin, I., Kawachi, I., Irizarry, R. A., Alicandro, G., Khunti, K., Yates, T., Jdanov, D. A., et al. (2021) · BMJ

COVID-19 epidemiological studiesCOVID-19 and healthcare impacts

Cited by 468

Nucleocytosolic acetyl-coenzyme a synthetase is required for histone acetylation and global transcription

Takahashi, H., McCaffery, J. M., Irizarry, R. A., & Boeke, J. D. (2006) · Molecular Cell

Genomics and Chromatin DynamicsHistone Deacetylase Inhibitors Research

Cited by 438

Recommendations for the design and analysis of epigenome-wide association studies

Michels, K. B., Binder, A. M., Dedeurwaerder, S., Epstein, C. B., Greally, J. M., Gut, I., Houseman, E. A., Izzi, B., Kelsey, K. T., Meissner, A., et al. (2013) · Nature Methods

Epigenetics and DNA MethylationGenetic Associations and Epidemiology

Cited by 378

Stem-like intestinal Th17 cells give rise to pathogenic effector T cells during autoimmunity

Schnell, A., Huang, L., Singer, M., Singaraju, A., Barilla, R. M., Regan, B. M. L., Bollhagen, A., Thakore, P. I., Dionne, D., Delorey, T. M., et al. (2021) · Cell

Psoriasis: Treatment and PathogenesisT-cell and B-cell Immunology

Cited by 268

Sequencing technology does not eliminate biological variability

Hansen, K. D., Wu, Z., Irizarry, R. A., & Leek, J. T. (2011) · Nature Biotechnology

Genomics and Phylogenetic StudiesSingle-cell and spatial transcriptomics

Cited by 226

Modeling of RNA-seq fragment sequence bias reduces systematic errors in transcript abundance estimation

Love, M. I., Hogenesch, J. B., & Irizarry, R. A. (2016) · Nature Biotechnology

Genomics and Phylogenetic StudiesGene expression and cancer classification

Cited by 186

IVT-seq reveals extreme bias in RNA sequencing

Lahens, N. F., Kavakli, I. H., Zhang, R., Hayer, K., Black, M. B., Dueck, H., Pizarro, A., Kim, J., Irizarry, R., Thomas, R. S., et al. (2014) · Genome Biology

Genomics and Phylogenetic StudiesSingle-cell and spatial transcriptomics

Cited by 158

Every Body Counts: Measuring Mortality From the COVID-19 Pandemic

Kiang, M. V., Irizarry, R. A., Buckee, C. O., & Balsari, S. (2020) · Annals of Internal Medicine

COVID-19 epidemiological studiesInsurance, Mortality, Demography, Risk Management

Cited by 96

UBR5 forms ligand-dependent complexes on chromatin to regulate nuclear hormone receptor stability

Tsai, J. M., Aguirre, J. D., Li, Y.-D., Brown, J., Focht, V., Kater, L., Kempf, G., Sandoval, B., Schmitt, S., Rutter, J. C., et al. (2023) · Molecular Cell

Estrogen and related hormone effectsUbiquitin and proteasome pathways

Cited by 68

SNP-specific array-based allele-specific expression analysis

Bjornsson, H. T., Albert, T. J., Ladd-Acosta, C. M., Green, R. D., Rongione, M. A., Middle, C. M., Irizarry, R. A., Broman, K. W., & Feinberg, A. P. (2008) · Genome Research

Genetic Syndromes and ImprintingGene expression and cancer classification

Cited by 68

Using the R Package crlmm for Genotyping and Copy Number Estimation

Scharpf, R. B., Irizarry, R. A., Ritchie, M. E., Carvalho, B., & Ruczinski, I. (2011) · Journal of Statistical Software

Genomic variations and chromosomal abnormalitiesGene expression and cancer classification

Cited by 52

A Flexible Statistical Framework for Estimating Excess Mortality

Acosta, R. J., & Irizarry, R. A. (2020) · Epidemiology

Data-Driven Disease SurveillanceClimate Change and Health Impacts

Cited by 52