Rafael Irizarry

Professor
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Research

We develop quantitative methods and software for genomics and epigenetics. We focus on microarrays and next generation sequencing. We are interested in leveraging our expertise in handling these data to help translate scientific research into medical practice with a focus on cancer.Specific problems we are currently working on include:

 

  • Next Generation Sequencing: Developing analysis tools for various applications.
  • Quantitative Epigenetics: Analyzing high throughput DNA methylation data.
  • RMA, fRMA, GCRMA: Preprocessing algorithms for Affymetrix arrays.
  • CRLMM: Genotyping and copy number tools for Affymetrix and Illumina SNP chips.
  • minfi, CHARM: Microarray method for high-throughput measurement of DNA methylation.
  • Expression Barcode: Single array classification based on calling expressed genes

 

 

Biography

Dr. Irizarry received his bachelor's in mathematics in 1993 from the University of Puerto Rico and went on to receive a Ph.D. in statistics in 1998 from the University of California, Berkeley. His thesis work was on Statistical Models for Music Sound Signals. He joined the faculty of the Department of Biostatistics in the Bloomberg School of Public Health in 1998 and was promoted to Professor in 2007. He is now a Professor in the Biostatistics and Computational Biology at the Dana Farber Cancer Center and a Professor of Biostatistics at Harvard School of Public Health. For the past fourteen years, Dr. Irizarry's work has focused on Genomics and Computational Biology problems. In particular, he has worked on the analysis and pre-processing of microarray, next-generation sequencing, and genomic data. He is currently interested in leveraging his knowledge in translational work, e.g. developing diagnostic tools and discovering biomarkers.

 

 

Recent Publications

Yuan GC, Cai L, Elowitz M, Enver T, Fan G, Guo G, Irizarry R, Kharchenko P,
Kim J, Orkin S, Quackenbush J, Saadatpour A, Schroeder T, Shivdasani R, Tirosh I. Challenges and emerging directions in single-cell analysis. Genome Biol. 2017 May 8;18(1):84.

 

Patro R, Duggal G, Love MI, Irizarry RA, Kingsford C. Salmon provides fast and
bias-aware quantification of transcript expression. Nat Methods. 2017
Apr;14(4):417-419.

 

Zheng SC, Beck S, Jaffe AE, Koestler DC, Hansen KD, Houseman AE, Irizarry RA,
Teschendorff AE. Correcting for cell-type heterogeneity in epigenome-wide
association studies: revisiting previous analyses. Nat Methods. 2017 Feb
28;14(3):216-217.

 

Han L, Wu HJ, Zhu H, Kim KY, Marjani SL, Riester M, Euskirchen G, Zi X, Yang
J, Han J, Snyder M, Park IH, Irizarry R, Weissman SM, Michor F, Fan R, Pan X.
Bisulfite-independent analysis of CpG island methylation enables genome-scale
stratification of single cells. Nucleic Acids Res. 2017 Jun 2;45(10):e77.

 

Campbell PT, Rebbeck TR, Nishihara R, Beck AH, Begg CB, Bogdanov AA, Cao Y,
Coleman HG, Freeman GJ, Heng YJ, Huttenhower C, Irizarry RA, Kip NS, Michor F, Nevo D, Peters U, Phipps AI, Poole EM, Qian ZR, Quackenbush J, Robins H, Rogan PK, Slattery ML, Smith-Warner SA, Song M, VanderWeele TJ, Xia D, Zabor EC, Zhang X, Wang M, Ogino S. Proceedings of the third international molecular pathological epidemiology (MPE) meeting. Cancer Causes Control. 2017 Feb;28(2):167-176.

 

Love MI, Hogenesch JB, Irizarry RA. Modeling of RNA-seq fragment sequence bias reduces systematic errors in transcript abundance estimation. Nat Biotechnol. 2016 Dec;34(12):1287-1291.

 

Teng M, Love MI, Davis CA, Djebali S, Dobin A, Graveley BR, Li S, Mason CE,
Olson S, Pervouchine D, Sloan CA, Wei X, Zhan L, Irizarry RA. Erratum to: A
benchmark for RNA-seq quantification pipelines. Genome Biol. 2016 Sep
30;17(1):203.

 

Collado-Torres L, Nellore A, Frazee AC, Wilks C, Love MI, Langmead B, Irizarry
RA, Leek JT, Jaffe AE. Flexible expressed region analysis for RNA-seq with
derfinder. Nucleic Acids Res. 2017 Jan 25;45(2):e9.

 

Teng M, Love MI, Davis CA, Djebali S, Dobin A, Graveley BR, Li S, Mason CE,
Olson S, Pervouchine D, Sloan CA, Wei X, Zhan L, Irizarry RA. Erratum to: A
benchmark for RNA-seq quantification pipelines. Genome Biol. 2016 May
23;17(1):107.

 

Teng M, Love MI, Davis CA, Djebali S, Dobin A, Graveley BR, Li S, Mason CE,
Olson S, Pervouchine D, Sloan CA, Wei X, Zhan L, Irizarry RA. A benchmark for
RNA-seq quantification pipelines. Genome Biol. 2016 Apr 23;17:74. doi:
10.1186/s13059-016-0940-1. Erratum in: Genome Biol. 2016;17(1):107. Genome Biol. 2016 Sep 30;17 (1):203.

 

 

Related Links

 

Rafael Irizarry Lab