Rafael A. Irizarry

111.0k total citations · 21 hit papers
191 papers, 57.2k citations indexed

About

Rafael A. Irizarry is a scholar working on Molecular Biology, Genetics and Cancer Research. According to data from OpenAlex, Rafael A. Irizarry has authored 191 papers receiving a total of 57.2k indexed citations (citations by other indexed papers that have themselves been cited), including 145 papers in Molecular Biology, 38 papers in Genetics and 19 papers in Cancer Research. Recurrent topics in Rafael A. Irizarry's work include Gene expression and cancer classification (63 papers), Epigenetics and DNA Methylation (37 papers) and Molecular Biology Techniques and Applications (34 papers). Rafael A. Irizarry is often cited by papers focused on Gene expression and cancer classification (63 papers), Epigenetics and DNA Methylation (37 papers) and Molecular Biology Techniques and Applications (34 papers). Rafael A. Irizarry collaborates with scholars based in United States, United Kingdom and Australia. Rafael A. Irizarry's co-authors include Benjamin M. Bolstad, Terence P. Speed, Magnus Åstrand, Michael I. Love, Carl Kingsford, Rob Patro, Geet Duggal, Andrew P. Feinberg, Leslie Cope and Laurent Gautier and has published in prestigious journals such as Nature, New England Journal of Medicine and Cell.

In The Last Decade

Rafael A. Irizarry

186 papers receiving 56.4k citations

Hit Papers

Exploration, normalization, and summaries of high density... 2003 2026 2010 2018 2003 2017 2003 2004 2003 2.5k 5.0k 7.5k
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Exploration, normalization, and summaries of high density oligonucleotide array probe level data
    2003 8.5k citations Rafael A. Irizarry Biostatistics profile →
  2. Salmon provides fast and bias-aware quantification of transcript expression
    2017 6.7k citations Rafael A. Irizarry et al. profile →
  3. A comparison of normalization methods for high densityoligonucleotide array data based on variance and bias
    2003 6.5k citations Rafael A. Irizarry et al. profile →
  4. affy—analysis of Affymetrix GeneChip data at the probe level
    2004 4.0k citations Rafael A. Irizarry et al. profile →
  5. Summaries of Affymetrix GeneChip probe level data
    2003 4.0k citations Rafael A. Irizarry profile →
  6. Minfi: a flexible and comprehensive Bioconductor package for the analysis of Infinium DNA methylation microarrays
    2014 2.5k citations Martin J. Aryee, Andrew E. Jaffe et al. profile →
  7. The human colon cancer methylome shows similar hypo- and hypermethylation at conserved tissue-specific CpG island shores
    2009 1.6k citations Rafael A. Irizarry, Christine Ladd‐Acosta et al. profile →
  8. MAGeCK enables robust identification of essential genes from genome-scale CRISPR/Cas9 knockout screens
    2014 1.4k citations Rafael A. Irizarry et al. Genome biology profile →
  9. A Model-Based Background Adjustment for Oligonucleotide Expression Arrays
    2004 1.4k citations Zhijin Wu, Rafael A. Irizarry et al. Journal of the American Statistical Association profile →
  10. Tackling the widespread and critical impact of batch effects in high-throughput data
    2010 1.4k citations Jeffrey T. Leek, Rafael A. Irizarry et al. profile →
  11. A framework for oligonucleotide microarray preprocessing
    2010 1.1k citations Rafael A. Irizarry et al. profile →
  12. Differential methylation of tissue- and cancer-specific CpG island shores distinguishes human induced pluripotent stem cells, embryonic stem cells and fibroblasts
    2009 867 citations Peter Murakami, Martin J. Aryee et al. profile →
  13. Increased methylation variation in epigenetic domains across cancer types
    2011 752 citations Rafael A. Irizarry, Andrew P. Feinberg et al. profile →
  14. Accounting for cellular heterogeneity is critical in epigenome-wide association studies
    2014 683 citations Andrew E. Jaffe, Rafael A. Irizarry Genome biology profile →
  15. Meta-analysis of gut microbiome studies identifies disease-specific and shared responses
    2017 675 citations Rafael A. Irizarry et al. profile →
  16. Robust decomposition of cell type mixtures in spatial transcriptomics
    2021 565 citations Rafael A. Irizarry et al. profile →
  17. Comprehensive methylome map of lineage commitment from haematopoietic progenitors
    2010 467 citations Peter Murakami, Hwa-Jin Lee et al. profile →
  18. Bump hunting to identify differentially methylated regions in epigenetic epidemiology studies
    2012 457 citations Andrew E. Jaffe, Peter Murakami et al. International Journal of Epidemiology profile →
  19. Mortality in Puerto Rico after Hurricane Maria
    2018 402 citations Nishant Kishore, Ayesha S. Mahmud et al. New England Journal of Medicine profile →
  20. Excess deaths associated with covid-19 pandemic in 2020: age and sex disaggregated time series analysis in 29 high income countries
    2021 285 citations Rolando J. Acosta, Rafael A. Irizarry et al. profile →
  21. Feature selection and dimension reduction for single-cell RNA-Seq based on a multinomial model
    2019 257 citations F. William Townes, Martin J. Aryee et al. Genome biology profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Rafael A. Irizarry United States 74 38.9k 8.1k 8.1k 5.2k 4.7k 191 57.2k
Trey Ideker United States 81 46.8k 1.2× 6.4k 0.8× 8.2k 1.0× 4.9k 0.9× 3.6k 0.8× 246 66.9k
Christian von Mering Switzerland 68 45.6k 1.2× 6.3k 0.8× 7.5k 0.9× 5.6k 1.1× 4.3k 0.9× 134 69.7k
Lars Juhl Jensen Denmark 87 49.7k 1.3× 6.5k 0.8× 8.2k 1.0× 6.2k 1.2× 5.5k 1.2× 240 75.4k
Brad T. Sherman United States 23 37.7k 1.0× 7.7k 0.9× 11.4k 1.4× 7.0k 1.3× 5.1k 1.1× 43 59.6k
Da Wei Huang United States 27 28.2k 0.7× 5.7k 0.7× 8.6k 1.1× 5.4k 1.0× 4.2k 0.9× 69 45.1k
Damian Szklarczyk Switzerland 32 31.9k 0.8× 4.5k 0.6× 6.7k 0.8× 4.8k 0.9× 3.8k 0.8× 43 51.0k
Andrew P. Feinberg United States 92 45.0k 1.2× 15.5k 1.9× 6.8k 0.8× 4.4k 0.8× 5.9k 1.3× 235 62.2k
Richard A. Lempicki United States 46 36.6k 0.9× 7.5k 0.9× 11.0k 1.4× 8.5k 1.6× 5.1k 1.1× 130 60.5k
Steve Horvath United States 106 44.2k 1.1× 11.1k 1.4× 8.3k 1.0× 5.0k 1.0× 4.3k 0.9× 447 70.9k
M Snyder United States 141 58.7k 1.5× 11.0k 1.3× 9.0k 1.1× 4.6k 0.9× 3.6k 0.8× 913 82.4k

Countries citing papers authored by Rafael A. Irizarry

Since Specialization
Citations

This map shows the geographic impact of Rafael A. Irizarry's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Rafael A. Irizarry with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rafael A. Irizarry more than expected).

Fields of papers citing papers by Rafael A. Irizarry

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Rafael A. Irizarry. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Rafael A. Irizarry. The network helps show where Rafael A. Irizarry may publish in the future.

Co-authorship network of co-authors of Rafael A. Irizarry

This figure shows the co-authorship network connecting the top 25 collaborators of Rafael A. Irizarry. A scholar is included among the top collaborators of Rafael A. Irizarry based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Rafael A. Irizarry. Rafael A. Irizarry is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
2.
Irizarry, Rafael A., et al.. (2022). A probabilistic gene expression barcode for annotation of cell types from single-cell RNA-seq data. Biostatistics. 23(4). 1150–1164. 6 indexed citations
3.
Townes, F. William & Rafael A. Irizarry. (2020). Quantile normalization of single-cell RNA-seq read counts without unique molecular identifiers. Genome biology. 21(1). 16 indexed citations
4.
Acosta, Rolando J., Nishant Kishore, Rafael A. Irizarry, & Caroline O. Buckee. (2020). Quantifying the dynamics of migration after Hurricane Maria in Puerto Rico. Proceedings of the National Academy of Sciences. 117(51). 32772–32778. 42 indexed citations
5.
Wahle, Philipp, Irwin Jungreis, Peter Menzel, et al.. (2019). A gene expression atlas of embryonic neurogenesis in Drosophila reveals complex spatiotemporal regulation of lncRNAs. Development. 146(6). 19 indexed citations
6.
Shukla, Chinmay, Chiara Gerhardinger, Keegan Korthauer, et al.. (2018). High‐throughput identification of RNA nuclear enrichment sequences. The EMBO Journal. 37(6). 96 indexed citations
7.
Benjamini, Yuval, Jonathan Taylor, & Rafael A. Irizarry. (2018). Selection-Corrected Statistical Inference for Region Detection With High-Throughput Assays. Journal of the American Statistical Association. 114(527). 1351–1365. 4 indexed citations
8.
Kishore, Nishant, Ayesha S. Mahmud, Mathew V. Kiang, et al.. (2018). Mortality in Puerto Rico after Hurricane Maria. New England Journal of Medicine. 379(2). 162–170. 402 indexed citations breakdown →
9.
Lahens, Nicholas F., İbrahim Halil Kavaklı, Ray Zhang, et al.. (2014). IVT-seq reveals extreme bias in RNA sequencing. Genome biology. 15(6). R86–R86. 110 indexed citations
10.
Jaffe, Andrew E., Peter Murakami, Hwa-Jin Lee, et al.. (2012). Bump hunting to identify differentially methylated regions in epigenetic epidemiology studies. International Journal of Epidemiology. 41(1). 200–209. 457 indexed citations breakdown →
11.
Guerrero‐Preston, Rafael, Julio Acero, Luis Alberto Moreno López, et al.. (2011). NID2 and HOXA9 Promoter Hypermethylation as Biomarkers for Prevention and Early Detection in Oral Cavity Squamous Cell Carcinoma Tissues and Saliva. Cancer Prevention Research. 4(7). 1061–1072. 106 indexed citations
12.
Aryee, Martin J., Zhijin Wu, Christine Ladd‐Acosta, et al.. (2010). Accurate genome-scale percentage DNA methylation estimates from microarray data. Biostatistics. 12(2). 197–210. 58 indexed citations
13.
Yegnasubramanian, Srinivasan, Michael C. Haffner, Yonggang Zhang, et al.. (2008). DNA Hypomethylation Arises Later in Prostate Cancer Progression than CpG Island Hypermethylation and Contributes to Metastatic Tumor Heterogeneity. Cancer Research. 68(21). 8954–8967. 214 indexed citations
14.
Wu, Zhijin & Rafael A. Irizarry. (2007). A statistical framework for the analysis of microarray probe-level data. The Annals of Applied Statistics. 1(2). 25 indexed citations
15.
Wheelan, Sarah J., Lisa Z. Scheifele, Francisco Martínez-Murillo, Rafael A. Irizarry, & Jef D. Boeke. (2006). Transposon insertion site profiling chip (TIP-chip). Proceedings of the National Academy of Sciences. 103(47). 17632–17637. 36 indexed citations
16.
Kendziorski, Christina, et al.. (2005). On the utility of pooling biological samples in microarray experiments. Proceedings of the National Academy of Sciences. 102(12). 4252–4257. 413 indexed citations
17.
Gentleman, Robert, Vincent J. Carey, Wolfgang Huber, Rafael A. Irizarry, & Sandrine Dudoit. (2005). Bioinformatics and Computational Biology Solutions Using R and Bioconductor (Statistics for Biology and Health). Springer eBooks. 214 indexed citations
18.
Irizarry, Rafael A.. (2004). Multiple Lab Comparison of Microarray Platforms. 27(5). 734–8. 6 indexed citations
19.
Irizarry, Rafael A.. (2000). ASYMPTOTIC DISTRIBUTION OF ESTIMATES FOR A TIME- VARYING PARAMETER IN A HARMONIC MODEL WITH MULTIPLE FUNDAMENTALS. Statistica Sinica. 10(4). 1041–1067. 5 indexed citations
20.
Irizarry, Rafael A.. (1998). The Additive Sinusoidal Plus Residual Model: A Statistical Analysis. The Journal of the Abraham Lincoln Association. 1998. 3 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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