Manu Setty

about me

I am a post-doctoral fellow in the Dana Pe'er lab in Computational & Systems Biology at Sloan Kettering Institute. I develop computational methods with a particular focus on trajectory detection to explain complex biological systems using single cell data. My post-doctoral work includes methods for detecting bifurcations in differentiation, modeling continuies in cell fate choices and harmonizing developmental datasets measured at discrete time points.

I received my PhD in Systems Biology under the supervision of Dr. Christina Leslie at Weill Cornell Graduate School. My doctoral research was focused on building methods to integrate diverse genomic datasets to infer regulatory changes in differentiation and disease. As part of my graduate work, I developed k-mer models for determining TF sequence preferences and used regression models to identify regulatory changes in disease.

I received a Masters degree in Computer Science from Columbia University specializing in Computational Biology and an undergraduate degree in Computer Science from National Institute of Technology Karnataka. I have also worked at Celsius Therapeutics as a Senior Scientist in Computational Biology.

Over the course of my training, I have developed a fascination for Understanding biology at a molecular level using high dimensional, high throughput data and I have worked on a variety of biological systems spanning embryonic development, differentiation, immunology and cancer biology.


  1. The emergent landscape of the mouse gut endoderm at single-cell resolution.
    Nowotschin S*, Setty M*, Kuo YY, Liu V, Garg V, Sharma R, Simon CS, Saiz N, Gardner R, Boutet SC, Church DM, Hoodless PA, Katerina-Hadjantonakis A, Pe'er D. Nature. April 2019.

  2. Negative Co-stimulation Constrains T Cell Differentiation by Imposing Boundaries on Possible Cell States.
    Wei SC, Sharma R, Anang NAS, Levine JH, Zhao Y, Setty M, Manusco JJ, Sharma P,Wang J, Pe'er D, Allison JP. Cell Immunity. March 2019.

  3. Characterization of cell fate probabilities in single-cell data with Palantir.
    Setty M, Kiseliovas V, Levine J, Gayoso A, Mazutis L, Pe'er D. Nature Biotechnology. March 2019.

  4. Single-cell Map of Diverse Immune Phenotypes Driven by the Tumor Microenvironment.
    Azizi E, Carr AJ, Plitas G, Cornish AE, Konopacki C, Prabhakaran S, Nainys J, Wu K, Kiseliovas V, Setty M, Choi K, Fromme RM, Dao P, McKenney PT, Wasti RC, Kadaveru K, Mazutis L, Rudensky AY, Pe'er D. Cell. June 2018.

  5. Epigenomic-guided mass cytometry profiling reveals disease-specific features of exhausted CD8 T cells.
    Bengsch B, Ohtani T, Khan O, Setty M, Manne1 M, O’Brien S, Gherardini PF, Herati RS, Huang AC, Chang KM, Newell EW, Bovenschen AN, Pe’er D, Albelda SM, Wherry EJ. Cell Immunity. May 2018.

  6. Wishbone identifies bifurcating developmental trajectories from single-cell data.
    Setty M*, Tadmor MD*, Reich-Zeliger S, Angel O, Salame TM, Kathail P, Choi K, Bendall S, Friedman N, Pe'er D. Nature Biotechnology. June 2016.

  7. Integrated genomic profiling identifies microRNA-92a regulation of IQGAP2 in locally advanced rectal cancer.
    Pelossof R, Chow OS, Fairchild L, Smith JJ, Setty M, Chen CT, Chen Z, Egawa F, Avila K, Leslie CS, Garcia-Aguilar J. Genes, Chromosomes & Cancer. Apr 2016.

  8. Enhancer poising and regulatory locus complexity shape gene expression changes in hematopoietic differentiation.
    Gonzalez JA*, Setty M*, Leslie CS. Nature Genetics. Aug 2015.

  9. SeqGL identifies binding profiles from genome-wide regulatory maps.
    Setty M, Leslie CS. PLoS Computational Biology. May 2015.

  10. MiR-28 controls cell proliferation and is down-regulated in B cell lymphomas.
    Schneider C, Setty M, Holmes A, Maute RL, Leslie CS, Mussolin L, Rosolen A, Dalla-Favera R, Basso K. Proceedings of the National Academy of Sciences. June 2014.

  11. A Novel Mutation in Bruton Tyrosine Kinase Confers Resistance to Ibrutinib (PCI-32765) in CLL.
    Furman RR, Cheng S, Lu P, Setty M, Perez A, Guo A, Racchumi J, Xu G, Ma J, Coleman M, Chen W, James D, Chang BY, Buggy J, Leslie CS, Wang YL.New England Journal of Medicine. May 2014.

  12. CSF-1R inhibition alters macrophage polarization and blocks gliomagenesis.
    Pyonteck S, Schumacher A, Bowman R, Akkari L, Sevenich L, Olson O, Teijeiro V, Setty M, Leslie CS, Huse J, Oei Y, Holland EC, Daniel D, Joyce J. Nature Medicine. Oct 2013.

  13. BCL6 positively regulates AID and germinal center gene expression via repression of miR-155.
    Basso K, Schneider C, Shen Q, Holmes A, Setty M, Leslie CS, Dalla-Favera R. Journal of Experimental Medicine. Dec 2012.

  14. Identification of global alterations of translational regulation in glioma in vivo.
    Helmy K, Halliday J, Fomchenko E, Setty M, Pitter K, Hafemeister C, Holland EC. PLoS One. Oct 2012.

  15. Inferring transcriptional and microRNA-mediated regulatory programs in glioblastoma.
    Setty M, Helmy K, Khan AA, Arvey A, Agius P, Holland EC, Leslie CS. Nature/EMBO Molecular Systems Biology. Aug 2012.

  16. A cooperative microRNA-tumor suppressor gene network in acute T-cell lymphoblastic leukemia (T-ALL)
    Mavrakis KJ, Van Der Meulen J, Wolfe AL, Liu X, Mets E, Taghon T, Khan AA, Setty M, Rondou P, Vandenberghe P, Delabesse E, Benoit Y, Socci NB, Leslie CS, Van Vlierberghe P, Speleman F, Wendel HG. Nature Genetics. Jul 2011.

  17. Genomic safe harbors permit high $\beta$-globin transgene expression in thalassemia induced pluripotent stem cells.
    Papapetrou E, Lee G, Malani N, Setty M, Riviere I, Tirunagari L, Kadota K, Roth S, Giardina P, Viale A, Leslie C, Bushman F, Studer L, Sadelain M. Nature Biotechnology. Jan 2011.

  18. HLA type inference via haplotypes identical by descent.
    Setty M, Gusev A, Pe'er I. Journal of Computational Biology. Aug 2010.

Computational Methods

Computational Methods
  1. Harmony. Harmonize single cell data measured at discrete developmental time points.
    Link. Reference.

  2. Palantir. Modeling continuities in cell fate choices.
    Link. Reference.

  3. Wishbone. Identifying bifurcations in single cell data.
    Link. Reference.

  4. SeqGL. k-mer models for TF sequence specificity.
    Link. Reference.

  5. RegulatorInference. Regression models for identify dysregulated regulators in disease.
    Link. Reference.


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