David Quigley - Balmain Lab - UCSF


I am a cancer researcher in Allan Balmain's lab at UCSF. My work centers on identifying genetic networks associated with susceptibility to skin, lung, or breast cancer. I'm particularly interested in how these networks are altered after a tumor develops. My training is in Computer Science and Biomedical Informatics; I also have worked as a professional software developer.

I am also a PhD candidate in Anne-Lise Børresen-Dale's group in the Deparment of Genetics, Institution for Cancer Research, Norwegian Radium Hospital. I split my time between Oslo and San Francisco, with most of my time spent in the US. I expect to defend my thesis work in 2014.

My CV in PDF format.


I have taken a systems genetics approach that combines phenotypic measurements, genotype data from SNP assays, and gene microarrays to identify Quantitative Trait Loci (QTL) associated with physical phenotypes such as blood or inflammation traits as well as gene expression traits. The goal of these investigations is to identify loci that are associated with networks of genes that are functionally interrelated either because they produce proteins that are part of a common structure or because they are steps in a gene pathway. Combining these genetic expression QTL networks with phenotype QTL can identify plausible candidate genes that are under common genetic control with matched phenotypes (e.g., hemoglobin pathway genes that share common genetic control with the Red Blood Cell count phenotype). Our recent papers in Nature and Genome Biology are examples of this approach. For more details, see our Perspective in Nature Reviews: Genetics.

Although I try to spend as much time working on biology as I can, I write a lot of software in R, Python, and C++. For statistical analysis, I have found Karl Broman's R/QTL software and the NetworkX library to be particularly useful. For software engineering with C++ I make heavy use of the Boost libraries and wxWidgets for cross-platform software development.

 Peer-reviewed publications: first author
  • Quigley DA, Fiorito E, Nord S, Van Loo P, Alnaes G, Fleischer T, Tost J, Vollan HK, Tramm T, Overgaard J, Bukholm IR, Hurtado A, Balmain A, Børresen-Dale A, & Kristensen V.
    The 5p12 breast cancer susceptibility locus affects MRPS30 expression in estrogen-receptor positive tumors.
    Molecular Oncology, December 9 2013. [Pubmed] [Code and data to reproduce]

  • Quigley DA, To MD, Kim IJ, Lin KK, Albertson DG, Sjolund J, Perez-Losada J, Balmain A.
    Network Analysis of Skin Tumor Progression Identifies a Rewired Genetic Architecture Affecting Inflammation and Tumor Susceptibility.
    Genome Biology, 2011 Jan 18;12(1):R5. [Pubmed] [PDF] [supplement]

  • Quigley DA & Balmain A.
    Systems genetics analysis of cancer susceptibility: from mouse models to humans.
    Nature Reviews: Genetics, 2009. Sep;10(9) 651-7. [Pubmed]

  • Quigley DA, To MD, Perez-Losada J, Pelorosso F, Mao J, Nagase H, Ginzinger D, & Balmain A.
    Genetic architecture of mouse skin inflammation and tumor susceptibility.
    Nature, 2009. Mar 26;458(7237):505-8. [Pubmed]

  • Quigley, DA
    RNA-seq Permits a Closer Look at Normal Skin and Psoriasis Gene Networks
    Journal of Investigative Dermatology, 2014. 134: 1789–1791 doi:10.1038/jid.2014.66 [JID link]
    Comments on Li et al. JID 2014
 Other peer-reviewed publications
  • Identification of Hipk2 as an essential regulator of white fat development
    Sjölund J, Pelorosso F, Quigley DA, DelRosario R, and Balmain A
    Proceedings of the National Academy of Sciences. [Pubmed]

  • Lung Tumorigenesis in a Conditional Cul4A Transgenic Mouse Model.
    Yang YL, Hung MS, Wang Y, Ni J, Mao JH, Hsieh D, Au A, Kumar A, Quigley D, Fang LT, Yeh CC, Xu Z, Jablons DM, You L.
    J Pathol. 2014 Mar 19 [Pubmed]

  • Kim IJ, Quigley D, To M, Jen, Pham P, Lin K, Jo B, Jen K, Raz D, Kim J, Mao JH, Jablons D & Balmain A
    Rewiring of human lung cell lineage and mitotic networks in lung adenocarcinomas.
    Nature Communications, 2013 Apr 16 [Nature Website]

  • Wong C, Yu J, Quigley DA, To M, Jen Kuang-Yu, Huang P, Del Rosario R & Allan Balmain
    Inflammation and Hras Signaling Control Epithelial-mesenchymal Transition during Skin Tumor Progression
    Genes and Development, 2013 Mar 15;27(6):670-82 [Pubmed]

  • Kang HC, Quigley D, Kim IJ, Wakabayashi Y, Ferguson-Smith MA, D'Alessandro M, Lane EB, Akhurst RJ, Goudie DR, Balmain A.
    Multiple Self-Healing Squamous Epithelioma (MSSE): Rare Variants in an Adjacent Region of Chromosome 9q22.3 to known TGFBR1 Mutations Suggest a Digenic or Multilocus Etiology.
    Journal of Investigative Dermatology, 2013 January 28. [Pubmed]

  • Benzinou M, Clermont FF, Letteboer TG, Kim JH, Espejel S, Harradine KA, Arbelaez J, Luu MT, Roy R, Quigley D, Higgins MN, Zaid M, Aouizerat BE, van Amstel JK, Giraud S, Dupuis-Girod S, Lesca G, Plauchu H, Hughes CC, Westermann CJ & Akhurst RJ
    Mouse and human strategies identify PTPN14 as a modifier of angiogenesis and hereditary haemorrhagic telangiectasia.
    Nature Communications, 2012 January 10. [Pubmed]

  • To MD, Quigley D, Mao J, Rosario R, Hsu J, Hodgson G, Jacks T, & Balmain A.
    Progressive genomic instability in the FVB/KrasLA2 mouse model of lung cancer.
    Molecular Cancer Research, 2011 August 1. [Pubmed] [PDF] [raw data]

  • Chan MF, Sack R, Quigley DA, Sathe S, Vijmasi T, Li S, Holsclaw D, Strauss EC, McNamara NA.
    Membrane Array Analysis of Tear Proteins in Ocular Cicatricial Pemphigoid.
    Optometry & Visual Science, 2011 May 5. [Pubmed]

  • Lalitha P, Shapiro BL, Loh AR, Fothergill AW, Prajna NV, Srinivasan M, Oldenburg CE, Quigley DA, Chidambaram JD, McLeod SD, Acharya NR, Lietman TM.
    Amphotericin B and natamycin are not synergistic in vitro against Fusarium and Aspergillus spp. isolated from keratitis.
    British Journal of Ophthalmology, 2011 May;95(5):744-5. [Pubmed]

  • Connolly EC, Saunier EF, Quigley D, Luu MT, De Sapio A, Hann B, Yingling JM, Akhurst RJ.
    Outgrowth of drug-resistant carcinomas expressing markers of tumor aggression after long-term TGFBRI/II kinase inhibition with LY2109761.
    Cancer Research, 2011 Mar 15;71(6):2339-49. [Pubmed]

  • Climent J, Perez-Losada J, Quigley DA, Kim IJ, Delrosario R, Jen KY, Bosch A, Lluch A, Mao JH, Balmain A.
    Deletion of the PER3 gene on chromosome 1p36 in recurrent ER-positive breast cancer.
    Journal of Clinical Oncology, 2010. Aug 10;28(23):3770-8. [Pubmed] [PDF] [supplement]

  • Li S, Sack R, Vijmasi T, Sathe S, Beaton A, Quigley D, Gallup M & McNamara N.
    Antibody Protein Array Analysis of the Tear Film Cytokines.
    Optometry & Vision Science, 2008. Aug;85(8):653-60. [Pubmed]

  • Kundaje A, Lianoglou S, Li X, Quigley D, Arias M, Wiggins CH, Zhang L, Leslie C.
    Learning regulatory programs that accurately predict differential expression with MEDUSA.
    Ann N Y Acad Sci. 2007 Dec;1115:178-202. [Pubmed]

2012 San Antonio Breast Cancer Symposium poster; presents work that became Quigley et al. Mol. Onc. 2013


An introduction to Quantitative Biology and R. Very high-level overview for first-year PhD students, introducing R.

 Reproducible Results

I am in the process of uploading code required which will reproduce all of the results for papers where I made important statistical contributions.

Quigley et al. Nature 2009

The raw expression data for this paper (Affymetrix CEL files) are available at GEO, GSE12248.

R code to reproduce the differential expression analysis of tail expression data is available here. The "gene attributes" file (a version of the na31 edition of the Affymetrix probeset annotations) used by this code can be obtained here.

You can download the Cytoscape CYS file used to create Figure One of Quigley Nature 2009: Q_et_al_figure_one.cys. You will need an up-to-date version of the Java runtime to load the file; I recommend the latest version of Cytoscape as well.

Quigley et al. Genome Biology 2011

The raw expression data for this paper (Affymetrix CEL files) and array-CGH data are available in GEO in SuperSeries GSE21264. Note that this SuperSeries includes the data from the Nature paper.

Genotypes used for this analysis can be downloaded here.
aCGH data used for this analysis can be downloaded here.

eQTL Results
eQTL results for Tails, Papillomas, and Carcinomas can be downloaded here. eQTL results were calculated by linear regression using code that can be downloaded from my GitHub repository. Please see this README file for a general overview of the analysis.

To et al. Molecular Cancer Research 2011

The array-CGH data used in this paper can be downloaded from GEO at GSE29230. The data as used in the reproducible analysis can be downloaded directly as a zip archive.

Quigley et al. Molecular Oncology 2013

Code and data to reproduce. Note that I cannot post the genotype data used for this study online; please contact the corresponding author (Vessela Kristensen) to inquire about access to these genotypes.

A large collection of R functions I have written.

Source code for the software I have written to perform these analyses (C++) is also available on GitHub.

 Collaborations (past and present)

Dr. William Weiss, MD, PhD, Genetic models of neuroblastoma
Dr. Rosemary Akhurst, PhD, the role of TGF-Beta in squamous cell carcinomas
Dr. David Jablons, MD, lung adenocarcinoma genetic network analysis
Dr. Nancy Mcnamera, OD PhD, Inflammatory diseases in the eye
Dr. Tom Lietman, MD, stochastic modeling of trachoma


I received a Masters degree awarded with honors from the Department of Biomedical Informatics at Columbia University in 2006. My research topic at Columbia was building models of transcriptional regulation using large-margin machine learning tools. I was a research assistant to Dr. Christina Leslie (now at MSK) in the Center for Computational Learning Systems at Columbia. We applied boosting to microarray data and sequence data from yeast and Drosophila to build models of conditional gene regulation. Before he departed Columbia for Vancouver, I did a rotation with professor Paul Pavlidis in the Gene Expression Informatics Group in the Columbia Genome Center. Our work involved designing and building a system to integrate many genomic data sources, including public databases and experimental Microarray data.

My professional experience before 2004 was in building high-volume web-based financial data and publishing systems. I have have been a software developer at Marketwatch.com in Minneapolis and at Orrick, Herrington & Sutcliffe in San Francisco. I received my bachelor's degree magna cum laude in Computer Science from Carleton College in 1998.

My extra-curricular interests include cooking Thai food, walking in San Francisco's neighborhoods, and raising my daughters Charlotte and Katherine. My wife Sarah is a novelist; her first novel for young adults is called TMI; you can (and should) get it at your local bookstore or online.


Emaildquigley at cc.ucsf.edu.
Work Address UCSF Comprehensive Cancer Center
Box 0875
San Francisco, CA 94143-0875