RAFAEL ANGEL IRIZARRY

Summary

Affiliation: Johns Hopkins University
Country: USA

Publications

  1. pmc Increased methylation variation in epigenetic domains across cancer types
    Kasper Daniel Hansen
    Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
    Nat Genet 43:768-75. 2011
  2. pmc The Gene Expression Barcode: leveraging public data repositories to begin cataloging the human and murine transcriptomes
    Matthew N McCall
    Department of Biostatistics, Johns Hopkins University Bloomberg School of Public Health, 615 N Wolfe Street, Baltimore, MD 21205, USA
    Nucleic Acids Res 39:D1011-5. 2011
  3. pmc The human colon cancer methylome shows similar hypo- and hypermethylation at conserved tissue-specific CpG island shores
    Rafael A Irizarry
    Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland 21205, USA
    Nat Genet 41:178-86. 2009
  4. pmc Gene expression anti-profiles as a basis for accurate universal cancer signatures
    Héctor Corrada Bravo
    Department of Computer Science, Center for Bioinformatics and Computational Biology, University of Maryland, College Park, MD, USA
    BMC Bioinformatics 13:272. 2012
  5. pmc Feature-level exploration of a published Affymetrix GeneChip control dataset
    Rafael A Irizarry
    Genome Biol 7:404. 2006
  6. pmc Validation and extension of an empirical Bayes method for SNP calling on Affymetrix microarrays
    Shin Lin
    McKusick Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, N Broadway, Baltimore, MD 21205, USA
    Genome Biol 9:R63. 2008
  7. pmc Chromosome-wide mapping of DNA methylation patterns in normal and malignant prostate cells reveals pervasive methylation of gene-associated and conserved intergenic sequences
    Srinivasan Yegnasubramanian
    Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
    BMC Genomics 12:313. 2011
  8. pmc Thawing Frozen Robust Multi-array Analysis (fRMA)
    Matthew N McCall
    Department of Biostatistics and Computational Biology, University of Rochester Medical Center, Rochester, NY, USA
    BMC Bioinformatics 12:369. 2011
  9. pmc Assessing affymetrix GeneChip microarray quality
    Matthew N McCall
    Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, 615 N, Wolfe St, Baltimore, MD, USA
    BMC Bioinformatics 12:137. 2011
  10. pmc A summarization approach for Affymetrix GeneChip data using a reference training set from a large, biologically diverse database
    Simon Katz
    Gene Logic Inc, 610 Professional Dr, Gaithersburg, MD, 20876, USA
    BMC Bioinformatics 7:464. 2006

Collaborators

Detail Information

Publications17

  1. pmc Increased methylation variation in epigenetic domains across cancer types
    Kasper Daniel Hansen
    Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
    Nat Genet 43:768-75. 2011
    ..We suggest a model for cancer involving loss of epigenetic stability of well-defined genomic domains that underlies increased methylation variability in cancer that may contribute to tumor heterogeneity...
  2. pmc The Gene Expression Barcode: leveraging public data repositories to begin cataloging the human and murine transcriptomes
    Matthew N McCall
    Department of Biostatistics, Johns Hopkins University Bloomberg School of Public Health, 615 N Wolfe Street, Baltimore, MD 21205, USA
    Nucleic Acids Res 39:D1011-5. 2011
    ..For selected platforms, users may upload data and obtain results in a matter of seconds. The raw data, curated annotation, and code used to create our resource are also available at http://rafalab.jhsph.edu/barcode...
  3. pmc The human colon cancer methylome shows similar hypo- and hypermethylation at conserved tissue-specific CpG island shores
    Rafael A Irizarry
    Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland 21205, USA
    Nat Genet 41:178-86. 2009
    ....
  4. pmc Gene expression anti-profiles as a basis for accurate universal cancer signatures
    Héctor Corrada Bravo
    Department of Computer Science, Center for Bioinformatics and Computational Biology, University of Maryland, College Park, MD, USA
    BMC Bioinformatics 13:272. 2012
    ..However, progress has been slowed by heterogeneity in cancer profiles and the lack of effective computational prediction tools for this type of data...
  5. pmc Feature-level exploration of a published Affymetrix GeneChip control dataset
    Rafael A Irizarry
    Genome Biol 7:404. 2006
    ..A comment on Preferred analysis methods for Affymetrix GeneChips revealed by a wholly defined control dataset by SE Choe, M Boutros, AM Michelson, GM Church and MS Halfon. Genome Biology 2005, 6:R16...
  6. pmc Validation and extension of an empirical Bayes method for SNP calling on Affymetrix microarrays
    Shin Lin
    McKusick Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, N Broadway, Baltimore, MD 21205, USA
    Genome Biol 9:R63. 2008
    ..Also, we tie our call confidence metric to percent accuracy. We intend that our validation datasets and methods, refered to as SNPaffycomp, serve as standard benchmarks for future SNP calling algorithms...
  7. pmc Chromosome-wide mapping of DNA methylation patterns in normal and malignant prostate cells reveals pervasive methylation of gene-associated and conserved intergenic sequences
    Srinivasan Yegnasubramanian
    Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
    BMC Genomics 12:313. 2011
    ..This MBD-chip approach was used to characterize DNA methylation patterns across all non-repetitive sequences of human chromosomes 21 and 22 at high-resolution in normal and malignant prostate cells...
  8. pmc Thawing Frozen Robust Multi-array Analysis (fRMA)
    Matthew N McCall
    Department of Biostatistics and Computational Biology, University of Rochester Medical Center, Rochester, NY, USA
    BMC Bioinformatics 12:369. 2011
    ..Curation of such a database and creation of the frozen parameter estimates is time-consuming; therefore, fRMA has only been implemented on the most widely used Affymetrix platforms...
  9. pmc Assessing affymetrix GeneChip microarray quality
    Matthew N McCall
    Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, 615 N, Wolfe St, Baltimore, MD, USA
    BMC Bioinformatics 12:137. 2011
    ....
  10. pmc A summarization approach for Affymetrix GeneChip data using a reference training set from a large, biologically diverse database
    Simon Katz
    Gene Logic Inc, 610 Professional Dr, Gaithersburg, MD, 20876, USA
    BMC Bioinformatics 7:464. 2006
    ..All subsequent pre-processing tasks can be done on an individual array basis. We demonstrate the utility of this approach by defining a new version of the Robust Multi-chip Averaging (RMA) algorithm which we refer to as refRMA...
  11. pmc Summaries of Affymetrix GeneChip probe level data
    Rafael A Irizarry
    Department of Biostatistics, Johns Hopkins University, Baltimore, MD 21205, USA
    Nucleic Acids Res 31:e15. 2003
    ..In particular, improvements in the ability to detect differentially expressed genes are demonstrated...
  12. ncbi request reprint Exploration, normalization, and summaries of high density oligonucleotide array probe level data
    Rafael A Irizarry
    Department of Biostatistics, Johns Hopkins University, Baltimore, MD 21205, USA
    Biostatistics 4:249-64. 2003
    ..We conclude that there is no obvious downside to using RMA and attaching a standard error (SE) to this quantity using a linear model which removes probe-specific affinities...
  13. pmc Comprehensive high-throughput arrays for relative methylation (CHARM)
    Rafael A Irizarry
    Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland 21205, USA
    Genome Res 18:780-90. 2008
    ..Furthermore, unlike the other approaches, CHARM is highly quantitative, a substantial advantage in application to the study of human disease...
  14. ncbi request reprint Multiple-laboratory comparison of microarray platforms
    Rafael A Irizarry
    Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland 21205, USA
    Nat Methods 2:345-50. 2005
    ..We used appropriate statistical analysis to demonstrate that there are relatively large differences in data obtained in labs using the same platform, but that the results from the best-performing labs agree rather well...
  15. ncbi request reprint Comparison of Affymetrix GeneChip expression measures
    Rafael A Irizarry
    Department of Biostatistics, Johns Hopkins University, 615 N Wolfe Street, Baltimore, MD 21205, USA
    Bioinformatics 22:789-94. 2006
    ..A webtool was made available for developers to benchmark their procedures. At the time of writing over 50 methods had been submitted...
  16. ncbi request reprint Assessing homeostasis through circadian patterns
    R A Irizarry
    Department of Biostatistics, Johns Hopkins University, Baltimore, Maryland 21205, USA
    Biometrics 57:1228-37. 2001
    ..We then assess homeostasis using these estimates and their statistical properties...

Research Grants8

  1. Analysis Tools and Software for Second Generation Sequencing Data
    RAFAEL ANGEL IRIZARRY; Fiscal Year: 2010
    ..We will develop data analysis tools for widely used applications using statistical methods that account for this uncertainty. ..
  2. Software for the Statistical Analysis of Microarray Probe Level Data
    Rafael Irizarry; Fiscal Year: 2007
    ..Our proposed goal is to continue the support of our software and further develop our tools to increase their usefulness to the research community. ..
  3. Preprocessing and Analysis Tools for Contemporary Microarray Applications
    Rafael Irizarry; Fiscal Year: 2007
    ....
  4. Software for the Statistical Analysis of Microarray Probe Level Data
    Rafael Irizarry; Fiscal Year: 2009
    ..Our proposed goal is to continue the support of our software and further develop our tools to increase their usefulness to the research community. ..
  5. Preprocessing and Analysis Tools for Contemporary Microarray Applications
    Rafael Irizarry; Fiscal Year: 2009
    ..abstract_text> ..
  6. Preprocessing and Analysis Tools for Contemporary Microarray Applications
    RAFAEL ANGEL IRIZARRY; Fiscal Year: 2010
    ..abstract_text> ..