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The Dana Pe'er Lab: Publications

Prabhakaran S, Azizi E, Carr A, Pe’er D Dirichlet Process Mixture Model for Correcting Technical Variation in Single-Cell Gene Expression DataICML 2016 
[URL] [PDF] [Supplementary Information]

Setty M, Tadmor MD, Reich-Zeliger S, Angel O, Salame TM, Kathail P, Choi K, Bendall S, Friedman N, Pe’er D Wishbone identifies bifurcating developmental trajectories from single-cell data Nat. Biotech. 2016 April 12 
 [URL] [PDF] [Supplementary Information] [Supplementary Table]

Marcotte R, Sayad A, Brown KR, Sanchez-Garcia F, Reimand J, Haider M, Virtanen C, Bradner JE, Bader GD, Mills GB, Pe’er D , Moffat J, Neel BGFunctional Genomic Landscape of Human Breast Cancer Drivers, Vulnerabilities, and Resistance Cell 2016 Jan 16 
 [URL] [PDF]

Gut G, Tadmor MD, Pe’er D, Pelkmans L, Liberali P. Trajectories of cell-cycle progression from fixed cell populations. Nat Methods. 2015 Aug 24 
[URL] [PDF] [Supplementary Material-PDF]

Chen BJ, Litvin O, Ungar L, Pe’er D . Context Sensitive Modeling of Cancer Drug Sensitivity. PLoS One 2015 Aug 14 

Alizadeh AA, Aranda V, Bardelli A, Blanpain C, Bock C, Borowski C, Caldas C, Califano A, Doherty M, Elsner M, Esteller M, Fitzgerald R, Korbel JO, Lichter P, Mason CE, Navin N, Pe’er D , Polyak K, Roberts CWM, Siu L, Snyder A, Stower H, Swanton C, Verhaak RGW, Zenklusen JC, Zuber J, Zucman-Rossi J. Toward understanding and exploiting tumor heterogeneity. Nature Methods 2015 Aug 8 

Levine JH, Simonds EF, Bendall SC, Davis KL, Amir ED, Tadmor MD, Litvin O, Fienberg HG, Jager A, Zunder ER, Finck R, Gedman AL, Radtke I, Downing JR, Pe’er D , Nolan GP. Data-Driven Phenotypic Dissection of AML Reveals Progenitor-like Cells that Correlate with Prognosis. Cell 2015 Jun 18 
 [URL] [PDF] [Supplementary Information-1] [Supplementary Information-2] [Supplementary Information-3] [Supplementary Information-4] [Supplementary Information-5] [Supplementary Table-1] [Supplementary Table-2] [Supplementary Table-3] [Main text with Supplementary Information]

Bose S, Wan Z, Carr A, Rizvi AH, Vieira G, Pe’er D , Sims PA. Scalable microfluidics for single cell RNA printing and sequencing. Genome Biol. 2015 Jun 6 

DiGiuseppe JA, Tadmor MD, Pe’er D . Detection of Minimal Residual Disease in B Lymphoblastic Leukemia Using viSNE. Cytometry B Clin Cytom. 2015 May 14 
[Web Version] [PDF]

Litvin O, Schwartz S, Wan Z, Schild T, Rocco M, Oh NL, Chen BJ, Goddard N, Pratilas C, Pe’er D . Interferon α/β enhances the cytotoxic response of MEK inhibition in Melanoma. Molecular Cell 2015 February 12 
[PDF] [Supplementary Information-1] [Supplementary Information-2] [DOI]

Lu Y, Xue Q, Eisele MR, Sulistijo, ES, Brower K, Han L, Amir el-AD, Pe’er D , Miller-Jensen K, Fan R. Highly multiplexed profiling of single-cell effector functions reveals deep functional heterogeneity in response to pathogenic ligands. PNAS 2015 February 17 

Zunder ER, Finck R, Behbehani GK, Amir el-AD, Krishnaswamy S, Gonzalez VD, Lorang CG, Bjornson Z, Spitzer MH, Bodenmiller B, Fantl WJ, Pe’er D , Nolan GP. Palladium-based mass tag cell barcoding with a doublet-filtering scheme and single-cell deconvolution algorithm. Nat. Protoc. 2015 February 10 
[Online Version] [PDF]

Sanchez-Garcia F, Villagrasa P, Matsui J, Kotliar D, Castro V, Akavia UD, Chen BJ, Saucedo-Cuevas L, Barrueco RR, Llobet-Navas D, Silva JM, Pe’er D . Integration of Genomic Data Enables Selective Discovery of Breast Cancer Drivers Cell 2014 December 4 
[PDF] [Supplementary Information-1] [Supplementary Information-2] [Supplementary Information-3] [DOI]

Krishnaswamy S, Spitzer MH, Mingueneau M, Bendall SC, Litvin O, Stone E, Pe’er D, Nolan GP. Conditional density-based analysis of T cell signaling in single cell data. Science 2014 October 23 
[Link to PDF]

Mingueneau M, Krishnaswamy S, Spitzer MH, Bendall SC, Stone EL, Hedrick SM, Pe’er D , Mathis D, Nolan GP, and Benoist C. Single-cell mass cytometry of TCR signaling: Amplification of small initial differences results in low ERK activation in NOD mice. PNAS 2014 October 7 

Carr A, Pe’er D. Broadening horizons: holistic viewpoints from the Biology of Genomes. Genome Biol. 2014 July 25 

Bendall SC, Davis KL, Amir EA, Tadmor MD, Simonds EF, Chen TJ, Shenfeld DK, Nolan GP, Pe’er D. Single-Cell Trajectory Detection Uncovers Progression and Regulatory Coordination in Human B Cell Development.Cell 2014 April 24 
[PDF] [Supplementary Information] [DOI]

Llobet-Navas D, Rodriguez-Barrueco R, Castro V, Ugalde AP, Sumazin P, Jacob-Sendler D, Demircan B, Castillo-Martin M, Putcha P, Marshall N, Villagrasa P, Chan J, Sanchez-Garcia F, Pe’er D, Rabadan R, Iavarone A, Cordon-Cardo C, Califano A, Lopez-Otin C, Ezhkova E, Silva JM. The miR-424(322)/503 cluster orchestrates remodeling of the epithelium in the involuting mammary gland. Genes Dev. 2014 April 1 

Becker-Weimann S, Xiong G, Furuta S, Han J, Kuhn I, Akavia UD, Pe’er D, Bissell MJ, Xu R. NFkB disrupts tissue polarity in 3D by preventing integration of microenvironmental signals. Oncotarget 2013 November 4 
[PDF] [Supplementary Figures] [Supplementary Tables]

Gagneur J, Stegle O, Zhu C, Jakob P, Tekkedil MM, Aiyar RS, Schuon AK,Pe’er D, Steinmetz LM. Genotype-environment interactions reveal causal pathways that mediate genetic effects on phenotype. PLoS Genet. 2013 Sep 19. 

Romano GH, Harari Y, Yehuda T, Podhorzer A, Rubinstein L, Shamir R, Gottlieb A, Silberberg Y, Pe’er D , Ruppin E, Sharan R, Kupiec M.Environmental stresses disrupt telomere length homeostasis. PLoS Genet. 2013 Sep 5 

Danussi C, Akavia UD, Niola F, Jovic A, Lasorella A, Pe’er D, Iavarone A. RHPN2 Drives Mesenchymal Transformation in Malignant Glioma by Triggering RhoA Activation. Cancer Res. 2013 Aug 2. 

Antebi YE, Reich-Zeliger S, Hart Y, Mayo A, Eizenberg I, Rimer J, Putheti P, Pe’er D , Friedman N. Mapping differentiation under mixed culture conditions reveals a tunable continuum of T cell fates. PLoS Biol. 2013 July 1 

Amir EA, Davis KL, Tadmor MD, Simonds EF, Levine JH, Bendall SC, Shenfeld DK, Krishnaswamy S, Nolan GP, Pe’er D. viSNE enables visualization of high dimensional single-cell data and reveals phenotypic heterogeneity of leukemia. Nat Biotechnol. 2013 May 19 
[PDF] [Supplementary Material] [Software]

Finck R, Simonds EF, Jager A, Krishnaswamy S, Sachs K, Fantl W, Pe’er D, Nolan GP, Bendall SC. Normalization of mass cytometry data with bead standards. Cytometry A. 2013 May 

Kreimer A, Litvin O, Hao K, Molony C, Pe’er D, Pe’er I. Inference of modules associated to eQTLs. Nucleic Acids Res. 2012 Mar 24 

Floratos A, Honig B, Pe’er D , Califano A. Using systems and structure biology tools to dissect cellular phenotypes. J. Am. Med. Inform. Assoc. 2012 

Wolpaw AJ, Shimada K, Skouta R, Welsch ME, Akavia UD, Pe’er D, Shaik F, Bulinski JC, Stockwell BR. Modulatory profiling identifies mechanisms of small molecule-induced cell death. Proc Natl Acad Sci U S A. 2011 Sep 27 

Bendall SC, Simonds EF, Qiu P, Amir el-AD, Krutzik PO, Finck R, Bruggner RV, Melamed R, Trejo A, Ornatsky OI, Balderas RS, Plevritis SK, Sachs K, Pe’er D, Tanner SD, Nolan GP. Single-cell mass cytometry of differential immune and drug responses across a human hematopoietic continuum. Science. 2011 May 6 

Pe’er D., Hacohen N., Principles and Strategies for Developing Network Models in Cancer. Cell. 2011 Mar 18 

Akavia U.D., Litvin O., Kim J., Sanchez-Garcia F., Kotliar D., Causton H.C., Pochanard P., Mozes E., Garraway L.A., Pe’er D., An integrated approach to uncover drivers of cancer. Cell. 2010 Dec 10 
[PDF] [Software]

Sanchez-Garcia F., Akavia U.D., Mozes E., Pe’er D., JISTIC: identification of significant targets in cancer BMC Bioinformatics. 2010 Apr 14 
[PDF] [Software]

Patwardhan R.P., Lee C., Litvin O., Young D.L., Pe’er D., Shendure J.,High-resolution analysis of DNA regulatory elements by synthetic saturation mutagenesis Nat Biotechnol. 2009 Dec 27 

Chen BJ., Causton H.C., Mancenido D., Goddard N.L., Perlstein E.O., Pe’er D., Harnessing gene expression to identify the genetic basis of drug resistance Mol Syst Biol. 2009 Oct 13 
[PDF] [Supplementary Material]

Litvin O., Causton H., Chen BJ., Pe’er D., Modularity and interactions in the genetics of gene expression Proc Natl Acad Sci. 2009 Feb 17 
[PDF] [Supplementary Material]

Lee S., Dudley A., Drubin D., Silver P., Krogan N., Pe’er D. and Koller D., Learning a Prior on Regulatory Potential from eQTL Data, PLoS Genet 5 (1), e1000358, 2009. 

Sachs K., Itani S., Carlisle J., Nolan G., Pe’er D. and Lauffenburger D., Learning Signaling Network Structures with Sparsely Distributed Data, Journal of Computational Biology, 2009. 

Lee S.*, Pe’er D.*, Dudley A., Church G., and Koller, D. (*equal contribution), Identifying Regulatory Mechanisms and their Individual Variation Reveals Key Role of Chromatin Modification, Proc Natl Acad Sci.2006 Sep 19;103(38):14062-7. 
[PDF] [PNAS] [Supplementary Material]

Pe’er D., Regev A. and Tanay A. Minreg: A Scalable Algorithm for Learning Parsimonious Regulatory networks in Yeast and Mammals, Journal of Machine Learning Research, 7:167—189, Feb 2006. 

Pe’er D. Bayesian network analysis of signaling networks: a primer, Science STKE, 281:pl4, April 2005 
[PDF] [STKE] [Breakthrough of year]

Sachs, K*., Perez, O*., Pe’er D*., Lauffenburger, D., and Nolan, G., (*equal contribution), Causal protein-signaling networks derived from multiparameter single-cell data, Science 308:523-529, April 2005. 
[PDF] [Science] [Supporting Material and Data] [Perspective]

Segal, E., Pe’er D., Regev, A. Koller, D. and Friedman N., Learning Module Networks, Journal of Machine Learning , 6:557-588, April 2005.

Segal, E*., Shapira, M., Regev, A*., Pe’er, D.*, Botstein, D., Koller, D. and Friedman, N., (*equal contribution), Module networks: identifying regulatory modules and their condition specific regulators from gene expression data, Nature Genetics 34:166-176, June 2003. 
[PDF] [Nature Genetics] [Web Supplement]

Pe’er, D., Regev, A. and Tanay, A., Minreg: Inferring an active regulator set, Bioinformatics 18:S258-S267, 2002 
[PDF] [Web Supplement]

Pe’er,D. , Regev, A., Elidan, G., and Friedman N., Inferring Subnetworks from Preturbed Expression Profiles Bioinformatics 17:S215-S224, 2001 
[PDF] [Web Supplement]

Friedman, N., Linial, M., Nachman, I, and Pe’er D., Using Bayesian networks to analyze expression data, Journal of Computational Biology, 7:601-620, 2000. 
[PDF] [Web Supplement] [Technical Supplement]