Jennifer Listgarten

Jennifer Listgarten

Microsoft Research

About me

I am a Senior Researcher at Microsoft Research New England , located in Cambridge, MA on the Charles, a five minute walk from MIT . Previously I was with Microsoft Research in Los Angeles and before that in Redmond, WA where I joined after completing my Ph.D. in the machine learning group of the department of Computer Science at the University of Toronto.

My area of expertise is in machine learning and applied statistics for computational biology. I'm interested in both methods development as well as application of methods to enable new insight into basic biology and medicine.

If you're interested in how machine learning and biology go together, I was recently interviewed by Talking Machines on this topic.

If you're interested in my FaST-LMM or EWASher work, please go to this landing page.

News

Upcoming Research Assistant (RA) Opportunity

We have an open RA position in Computational Biology and Machine Learning with a start date of July 1st, 2016 and duration of 1-2 years. Microsoft Research is in Kendall Square in Cambridge, MA. The position is ideal for a recent undergraduate wishing to gain research experience prior to pursuing a Ph.D. For more information and instructions on how to apply, go here.

Our CRISPR predictive modeling paper is now out

Genome editing is about deleting or changing parts of the genetic code. It has long been a goal of molecular biology because it would help us to understand mechanisms of disease and enable precision medicine and drug development, to name just a few important applications. In the past few years a revolutionary new molecular biology technique called CRISPR emerged, which dramatically changed the field of gene editing. In collaboration with the Broad Institute, we have used machine learning to develop a state-of-the-art predictive model to enable substantially more efficient CRISPR gene editing.

  • The paper in Nature Biotechnology can be found here.
  • A Broad blog post on our project is here.
  • A Microsoft blog post on our project is here.
  • Our project page including links to the data and code is available from here.

Post-doc positions in computational biology

A computational biology postdoc position starting July 1st, 2017 is currently open. Although interviews may not be scheduled until January 2017, please apply as soon as you are ready to do so as we may fill the position on a rolling basis. Most post-docs stay for 2 years but because many already have faculty positions lined up which they defer for a year, the position can also be for only one year. MSR New England, located in Cambridge, MA and adjacent to MIT is a multi-displinary lab which includes areas in addition to computational biology, of machine learning, theoretical computer science, economics and social media. For instructions on how to apply, see here, but ignore the deadline written there.

Computational Biology Talks at MSR NE

From time to time we host computational biology talks at MSR New England. To subscribe to the talk announcement list, send a message to listserv@lists.research.microsoft.com and enter "subscribe msrne-cb-announce" in the body of the message, or simply click here to generate that email automatically.

Internship opportunities

We hire exceptional Ph.D. students with expertise in computational biology, genetics, applied statistics and/or machine learning for 3-month internships. Relocation, including work visa, housing and transportation are taken care of; internships are well-paid. If you are interested please send me a cover letter and CV with the subject "intern applicant: FirstName LastName". Also note that the best window of opportunity to secure an internship is early in the year and so it's best to send your materials in December, although most interns choose to start in early summer. N.B. We have filled all our positions for the year 2016.

Selected
Publications

Optimized sgRNA design to maximize activity and minimize off-target effects for genetic screens with CRISPR-Cas9

JG Doench*, N Fusi*, M Sullender*, M Hegde*, EW Vaimberg*, KF Donovan, I Smith, Z Tothova, C Wilen , R Orchard , HW Virgin, J Listgarten*, DE Root
Nature Biotechnology   2016 doi:10.1038/nbt.3437
(*equal contributions, corresponding)
A pre-print of just the computational aspects of this paper is available on bioRxiv
Source code and prediction server available from here: here.
[Microsoft Research blog post]
[Broad Institute blog post]

Epigenome-wide association studies without the need for cell-type composition

James Zou, C. Lippert, D. Heckerman, Martin Aryee, Jennifer Listgarten
Nature Methods   2014 (journal link)
Python software available from here, and R software available from here.

FaST-LMM-Select for addressing confounding from spatial structure and rare variants

Jennifer Listgarten, Christoph Lippert, David Heckerman (equal contributions)
Nature Genetics   2013 (journal link)

Patterns of methylation heritability in a genome-wide analysis of four brain regions

Gerald Quon, Christoph Lippert, David Heckerman, Jennifer Listgarten
Nucleic Acids Research   2013, doi: 10.1093/nar/gks1449

Improved linear mixed models for genome-wide association studies

Jennifer Listgarten, C. Lippert, C. Kadie, R. Davidson, E. Eskin and D. Heckerman
(equal contributions)
Nature Methods   2012, doi:10.1038/nmeth.2037
Source and executables available here.

Statistical resolution of ambiguous HLA typing data

Jennifer Listgarten, Z. Brumme, C. Kadie, G. Xiaojiang, B. Walker, M. Carrington, P. Goulder, D. Heckerman,
in PLoS Computational Biology   2008, 4(2):e1000016
(abstract, paper, coverage in the magazine BioInform, press release) For the public web server tool based on this work, go here ; for .exe and source code (training code not included), go here.

Bayesian detection of infrequent differences in sets of time series with shared structure.

Jennifer Listgarten, Radford M. Neal, Sam T. Roweis, Rachel Puckrin and Sean Cutler,
NIPS   2006
Best Student Paper, Honorable Mention. (abstract, paper)

Statistical and computational methods for comparative proteomic profiling using liquid chromatography-tandem mass spectrometry.

Jennifer Listgarten and Andrew Emili,
Molecular and Cellular Proteomics   2005 4:419-434. (abstract) (paper)

All Publications

Identifying gene expression modules that define human cell fates

I Germanguz, J Listgarten, A Solomon, X Gaeta, WE Lowry  (equal contributions)
Stem Cell Research  (2016, in press)

Leveraging Non-Linear Genetic Effects on Functional Traits for GWAS

Nicolo Fusi and Jennifer Listgarten
RECOMB Proceedings (in Lecture Notes in Computer Science)  2016 (pdf)

Optimized sgRNA design to maximize activity and minimize off-target effects for genetic screens with CRISPR-Cas9

JG Doench*, N Fusi*, M Sullender*, M Hegde*, EW Vaimberg*, KF Donovan, I Smith, Z Tothova, C Wilen , R Orchard , HW Virgin, J Listgarten*, DE Root
Nature Biotechnology Jan 2016 doi:10.1038/nbt.3437
(*equal contributions, corresponding)
A pre-print of just the computational aspects of this paper is available on bioRxiv
Source code and prediction server available from here: here.
[Microsoft Research blog post]
[Broad Institute blog post]

In Silico Predictive Modeling of CRISPR/Cas9 guide efficiency

Nicolo Fusi, Ian Smith, John Doench, Jennifer Listgarten
bioRxiv, dx.doi.org/10.1101/021568 2015 ( preprint )
This pre-print has been largely (though not entirely) absorbed into the Nature Biotechnology paper above.

Further Improvements to Linear Mixed Models for Genome-Wide Association Studies

Chris Widmer, Christoph. Lippert, Omer Weissbrod, Nicolo Fusi, Carl Kadie, Bob Davidson, Jennifer Listgarten and D. Heckerman
Scientific Reports, Nov. 2014 (open access)

let-7 miRNAs Can Act through Notch to Regulate Human Gliogenesis

Patterson M, Gaeta X, Loo K, Edwards M, Smale S, Cinkornpumin J, Xie Y, Listgarten J, Azghadi S, Douglass SM, Pellegrini M, Lowry WE.
Stem Cell Reports 2014, doi: 10.1016/j.stemcr.2014.08.015 (open access)

Personalized Medicine: From Genotypes, Molecular Phenotypes and the Quantified Self, Toward Improved Medicine

Joel Dudley, Jennifer Listgarten, Oliver Stegle, Steven Brenner, Leopold Parts
Proceedings of the Pacific Symposium on Biocomputing 2015 (pdf)

Greater power and computational efficiency for kernel-based association testing of sets of genetic variants

C. Lippert, J. Xiang, D. Horta, C. Widmer, C. Kadie, D. Heckerman, Jennifer Listgarten
Bioinformatics 2014, doi: 10.1093/bioinformatics/btu504 (open access)

Epigenome-wide association studies without the need for cell-type composition

James Zou, Christoph Lippert, David Heckerman, Martin Aryee, Jennifer Listgarten
Nature Methods, 309-311 (2014) (journal link)
Python software available from here, and R software available from here.

Personalized Medicine: from genotypes and molecular phenotypes toward therapy

Jennifer Listgarten, Oliver Stegle, Quaid Morris, Steven Brenner, Leo Parts
Proceedings of the Pacific Symposium on Biocomputing 2014

A genome-to-genome analysis of associations between human genetic variation, HIV-1 sequence diversity, and viral control.

I. Bartha, J. Carlson, C. Brumme, P. McLaren, Z. Brumme, M. John, D. Haas, J. Martinez-Picado, J. Dalmau, C. López-Galíndez, C. Casado, A. Rauch, H. Günthard, E. Bernasconi, P. Vernazza, T. Klimkait, S. Yerly, S. O’Brien, Jennifer Listgarten, N. Pfeifer, C. Lippert, N. Fusi, Z. Kutalik, T. Allen, Viktor Müller, R. Harrigan, D. Heckerman, A. Telenti, J. Fellay
eLife (2013) 2:e01123 (journal link)

The benefits of selecting phenotype-specific variants for applications of mixed models in genomics.

C. Lippert, G. Quon, EY Kang, C. Kadie, Jennifer Listgarten, D. Heckerman
(equal contributions)
Scientific Reports (2013) doi:10.1038/srep01815 (journal link)

FaST-LMM-Select for addressing confounding from spatial structure and rare variants

Jennifer Listgarten, Christoph Lippert, David Heckerman (equal contributions)
Nature Genetics, 45, 470-471 (2013) doi:10.1038/ng.2620 (journal link)

A powerful and efficient set test for genetic markers that handles confounders

Jennifer Listgarten, C. Lippert, EY Kang, J. Xiang, C. Kadie, D. Heckerman
(equal contributions)
Bioinformatics 2013, doi: 10.1093/bioinformatics/btt177 (open access)
Source and executables available here.

An Exhaustive Epistatic SNP Association Analysis on Expanded Wellcome Trust Data

C. Lippert, Jennifer Listgarten, R. Davidson, S. Baxter, H. Poon, C. Kadie, D. Heckerman,
(equal contributions)
Scientific Reports, 2013, doi:10.1038/srep01099

Patterns of methylation heritability in a genome-wide analysis of four brain regions

Gerald Quon, Christoph Lippert, David Heckerman, Jennifer Listgarten
Nucleic Acids Research, 2013, doi: 10.1093/nar/gks1449

The future of genome-based medicine.

Quaid Morris, Steven Brenner, Jennifer Listgarten, Oliver Stegle
Proceedings of the Pacific Symposium on Biocomputing 2013, 16:456-458. doi:10.1142/9789814447973_0046

Correlates of Protective Cellular Immunity Revealed by Analysis of Population-Level Immune Escape Pathways in HIV-1

J. Carlson, C. Brumme, E. Martin, Jennifer Listgarten, M. Brockman, AQ. Le, C. Chui, L. Cotton, D. Knapp, SA. Riddler, R. Haubrich, G. Nelson, N. Pfeifer, C. DeZiel, D. Heckerman, R. Apps, M. Carrington, S. Mallal, R. Harrigan, M. John, Z. Brumme and the International HIV Adaptation Collaborative
Journal of Virology, Dec. 2012, 86(4)

Co-Operative Additive Effects between HLA Alleles in Control of HIV-1

P. Matthews, Jennifer Listgarten, J. Carlson, R. Payne, KH Huang, J Frater, D Goedhals, D Steyn, D van Vuuren, P Paioni, P Jooste, A Ogwu, R Shapiro, Z Mncube, T Ndung'u, B Walker, D Heckerman, P Goulder
(equal contributions)
PLoS One, 2012, 7(10): e47799. doi:10.1371/journal.pone.0047799

Improved linear mixed models for genome-wide association studies

Jennifer Listgarten, C Lippert, CM Kadie, RI Davidson, E Eskin and D Heckerman
(equal contributions)
Nature Methods, 2012, doi:10.1038/nmeth.2037
Source and executables available here.

Learning Transcriptional Regulatory Relationships Using Sparse Graphical Models

X Zhang, W Cheng, Jennifer Listgarten, C Kadie, S Huang, W Wang, D Heckerman
PLoS One, 2012, doi:10.1371/journal.pone.0035762

Widespread Impact of HLA Restriction on Immune Control and Escape Pathways in HIV-1

J. Carlson, Jennifer Listgarten, N Pfeifer, V Tan, Carl Kadie, B Walker, T Ndung'u, R Shapiro, J Frater, Z Brumme, P Goulder and D Heckerman
Journal of Virology, February 2012, doi:10.1128/?JVI.06728-11 (abstract,paper)

Personalized Medicine: From Genotype and Molecular Phenotypes Towards Computed Therapy

Oliver Stegle, Frederick P. Roth, Quaid Morris, Jennifer Listgarten
Proceedings of the Pacific Symposium on Biocomputing 2012

HLA-A*7401-mediated control of HIV viremia is independent of its linkage disequilibrium with HLA-B*5703.

P. Matthews, E. Adland, J. Listgarten, A. Leslie, N. Mkhwanazi, J. Carlson, M. Harndahl, A. Stryhn, R. Payne, A. Ogwu, K. Huang, J. Frater, P. Paioni, H. Kloverpris, P.Jooste, D. Goedhals, C. van Vuuren, D. Steyn, L. Riddell, F. Chen, G. Luzzi, T. Balachandran, T. Ndung'u, S. Buus, M. Carrington, R. Shapiro, D. Heckerman, and P. Goulder
Journal of Immunology April 2011, doi: 10.4049

Additive contribution of HLA class I alleles in the immune control of HIV-1 infection

Leslie A, Matthews PC, Listgarten J, Carlson JM, Kadie C, Ndung'u T, Brander C, Coovadia H, Walker BD, Heckerman D, Goulder PJ
Journal of Virology , 2010

Rare HLA Drive Additional HIV Evolution Compared to More Frequent Alleles

CM Rousseau, DW Lockhart, Jennifer Listgarten, C Kadie, GH Learn, DC Nickle, D Heckerman, W Deng, C Brander, T Ndung'u, H Coovadia, P Goulder, B. Korber, B Walker, J Mullins
AIDS Research and Human Retroviruses , 2009; 25(3):297-303

In silico resolution of ambiguous HLA typing data

J Listgarten, Z Brumme, C Kadie, G Xiaojiang, B Walker, M Carrington, P Goulder, D Heckerman,
in ASHI Quarterly, Volume 32, Number 2, 2008
For the public web server tool based on this work, go here ; for .exe and source code (training code not included), go here. (pdf)

Statistical resolution of ambiguous HLA typing data.

Jennifer Listgarten, Z Brumme, C Kadie, G Xiaojiang, B Walker, M Carrington, P Goulder, D Heckerman,
in PLoS Computational Biology, 2008, 4(2):e1000016
For the public web server tool based on this work, go here ; for .exe and source code (training code not included), go here.
(abstract, paper, coverage in the magazine BioInform, press release)

A statistical framework for modeling HLA-dependent T-cell response data.

Jennifer Listgarten, Nicole Frahm, Carl Kadie, Christian Brander and David Heckerman,
PLoS Computational Biology, 2007, 3(10):e188
Web tool, executable and source code available here, under "HLA Assignment"
(abstract, paper, press release)

Extensive HLA class I allele promiscuity among viral CTL epitopes.

N. Frahm, K. Yusim, T. Suscovich, S. Adams, J. Sidney, P. Hraber, H. Hewitt, CH. Linde, D. Kavanagh, T. Woodberry, L. Henry, K. Faircloth, J. Listgarten, C. Kadie, N. Jojic, K. Sango, N. Brown, E. Pae, M. Zaman, F. Bihl, A. Khatri, M. John, S. Mallal, F. Marincola, B. Walker, A. Sette, D. Heckerman, B. Korber, C. Brander
European Journal of Immunology, 2007 37(9):2419-2433.
See paper above for code/tools used in this paper. (abstract)

Evidence that dysregulated DNA mismatch repair characterizes human non-melanoma skin cancer

Leah C. Young, Jennifer Listgarten, Martin J. Trotter, Susan E. Andrew, Victor A. Tron
British Journal of Dermatology, 2008 158(1):59-69. (abstract)

Determining the number of non-spurious arcs in a learned DAG model: Investigation of a Bayesian and a frequentist approach.

Jennifer Listgarten and David Heckerman
Proceedings of Twenty-Third Conference on Uncertainty in Artificial Intelligence, UAI Press, July 2007 ( paper)

Analysis of sibling time series data: alignment and difference detection

Jennifer Listgarten,
Ph.D. Thesis, Department of Computer Science, University of Toronto 2007.
(abstract, thesis and code)

Bayesian detection of infrequent differences in sets of time series with shared structure.

Jennifer Listgarten, Radford M. Neal, Sam T. Roweis, Rachel Puckrin and Sean Cutler,
Advances in Neural Information Processing Systems 19, MIT Press, Cambridge, MA, 2007 ( NIPS 2006).
Best Student Paper, Honorable Mention. (abstract, paper)

Leveraging information across HLA alleles/supertypes improves epitope prediction.

David Heckerman, Carl Kadie, Jennifer Listgarten,
Journal of Computational Biology, 2007 14: 736-746
(shorter version also appears Proceedings of Research in Computational Molecular Biology. Lecture Notes in Computer Science, Volume 3909, Mar 2006, 296-308.)
(abstract, paper)
Web tool, executable and source code available here, under "Epitope Prediction"

Practical proteomic biomarker discovery: taking a step back to leap forward.

Jennifer Listgarten and Andrew Emili,
Drug Discovery Today, 2005 10:1697-1702.
(abstract) (paper)

Statistical and computational methods for comparative proteomic profiling using liquid chromatography-tandem mass spectrometry.

Jennifer Listgarten and Andrew Emili,
Molecular and Cellular Proteomics, 2005 4:419-434.
(abstract) (paper)

Multiple alignment of continuous time series.

Jennifer Listgarten, Radford M. Neal, Sam T. Roweis and Andrew Emili,
Advances in Neural Information Processing Systems 17, MIT Press, Cambridge, MA, 2005 (NIPS 2004).
The Continuous Profile Models (CPM) Matlab Toolbox is available here.
(abstract, paper, slides, and audio demo)

Predictive models for breast cancer susceptibility from multiple, single nucleotide polymorphisms.

(abstract) (paper)
Jennifer Listgarten, S Damaraju, B Poulin, L Cook, J Dufour, A Driga, J Mackey, D Wishart, R Greiner and B Zanke,
Clinical Cancer Research 2004:10(8):2725-37.

Clinically validated benchmarking of normalization techniques for two-colour oligonucleotide spotted microarray slides.

(abstract) (paper)
Jennifer Listgarten, K Graham, S Damaraju, C Cass, J Mackey and B Zanke, Applied Bioinformatics 2003:2(4)219-228.

Lymphovascular invasion is associated with poor survival in gastric cancer: an application of gene-expression and tissue array techniques.

BJ Dicken, K Graham, SM Hamilton, S Andrews, R Lai, Jennifer Listgarten, GS Jhangri, LD Saunders, S Damaraju and CE Cass,
Annals of Surgery 2006: 243(1):64-73.

Exploring qualitative probabilities for image understanding

Jennifer Listgarten,
M.Sc. Thesis, Department of Computer Science, University of Toronto, October 2000.
(pdf 1.2MB) (ps.gz 0.6MB)