BCCHR Researchers Find a Researcher

Keegan Korthauer

PhD

Investigator, BC Children's Hospital

Innovative technologies now allow us to probe the genome in more dimensions and at higher resolution than ever before, providing a wealth of information for studying the genomic basis of complex traits. However, meaningful biological insights are often masked by technical artifacts, systematic biases, or low signal-to-noise ratio (“needle in a haystack”). These challenges demand tailored statistical methodology in order to unlock the full potential of emerging assays.

My research group focuses on developing novel frameworks and rigorous inferential procedures that exploit the increased scope and scale of high-throughput sequencing data, with the ultimate goal of uncovering new molecular signals in cancer, child health, and development.

Academic Affiliations

Assistant Professor, , Department of Statistics, Faculty of Science, University of British Columbia
Research Theme: Healthy Starts
Research Group(s): Origins of Child Health and Disease

Contact Information

Location

950 West 28th Avenue, Vancouver, British Columbia, Canada, V5Z 4H4

Keegan.Korthauer@bcchr.ca

Korthauer Lab

Clinical Utility of Multicancer Detection in Symptomatic Patients: A Decision-Making Perspective

JCO Precision Oncology

Giuliano Netto Flores Cruz and Keegan Korthauer

DOI: 10.1200/PO-25-00279

12 / 2025

RAMEN: Dissecting individual, additive and interactive gene-environment contributions to DNA methylome variability in cord blood

Genome Biology

Erick I. Navarro-Delgado and Darina Czamara and Karlie Edwards and Maggie P. Fu and Sarah M. Merrill and Chaini Konwar and Julie L. MacIsaac and David T.S. Lin and Piush Mandhane and Elinor Simons and Padmaja Subbarao and Theo J. Moraes and Jari Lahti and Gregory E. Miller and Elisabeth B. Binder and Katri Rikknen and Stuart E. Turvey and Keegan Korthauer and Michael S. Kobor

DOI: 10.1186/s13059-025-03864-4

12 / 2025

Distinct Co-methylation Patterns in African and European Populations and Their Genetic Associations

Genomics, Proteomics & Bioinformatics

Zheng Dong and Nicole Gladish and Maggie P Y Fu and Samantha L Schaffner and Keegan Korthauer and Michael S Kobor

DOI: 10.1093/gpbjnl/qzaf096

11 / 2025

Low oxygen promotes extravillous trophoblast progenitor expansion but restrains maturation

Gina L. McNeill and Giada Guntri and Ida Calvi and Alastair H. Kyle and Hans-Rudolf Hotz and Victoria M. Leonard and Willie Wu and Matthew J. Shannon and Andrew I. Minchinton and Keegan Korthauer and Margherita Y. Turco and Alexander G. Beristain

DOI: 10.1101/2025.10.29.685387

10 / 2025

decemedip: hierarchical Bayesian modeling for cell type deconvolution of immunoprecipitation-based DNA methylomes

Biorxiv

Shen, N. and Zhang, Z. and Baca, S. and Korthauer, K.

DOI: 10.1101/2025.05.09.653152

Complete reference genome and pangenome improve genome-wide detection and interpretation of DNA methylation using sequencing and array data

Cell Reports

Dong, Z. and Whitehead, J. and Fu, M. and MacIsaac, J.L. and Rehkopf, D.H. and Rosero-Bixby, L. and Kobor, M.S. and Korthauer, K.

DOI: 10.1016/j.celrep.2025.115755

Accounting for differences between Infinium MethylationEPIC v2 and v1 in DNA methylation"based tools

Life Science Alliance

Zhuang, B.C. and Jude, M.S. and Konwar, C. and Yusupov, N. and Ryan, C.P. and Engelbrecht, H.-R. and Whitehead, J. and Halberstam, A.A. and Macisaac, J.L. and Dever, K. and Tran, T.K. and Korinek, K. and Zimmer, Z. and Lee, N.R. and McDade, T.W. and Kuzawa, C.W. and Huffman, K.M. and Belsky, D.W. and Binder, E.B. and Czamara, D. and Korthauer, K. and Kobor, M.S.

DOI: 10.26508/lsa.202403155

Examining cellular heterogeneity in human DNA methylation studies: Overview and recommendations

STAR Protocols

Fu, M.P.-Y. and Merrill, S.M. and Korthauer, K. and Kobor, M.S.

DOI: 10.1016/j.xpro.2025.103638

Genetic Basis, Quantitative Nature, and Functional Relevance of Evolutionarily Conserved DNA Methylation

Zheng Dong and Samantha Schaffner and Maggie Fu and Joanne Whitehead and Julia L. MacIsaac and David H. Rehkopf and W. Thomas Boyce and Luis Rosero-Bixby and Lluis Quintana-Murci and Etienne Patin and Gregory E. Miller and Keegan Korthauer and Michael S. Kobor

DOI: 10.1101/2024.11.07.622474

11 / 2024

Complete Reference Genome and Pangenome Expand Biologically Relevant Information for Genome-Wide DNA Methylation Analysis Using Short-Read Sequencing and Array Data

Biorxiv

Dong, Z.J. and Whitehead, J. and Fu, M. and MacIsaac, J.L. and Rehkopf, D.H. and Rosero-Bixby, L. and Kobor, M.S. and Korthauer, K.

DOI: 10.1101/2024.10.07.617116

Accounting for differences between Infinium MethylationEPIC v2 and v1 in DNA methylation-based tools

Biorxiv

Zhuang, B.C. and Jude, M.S. and Konwar, C. and Yusupov, N. and Ryan, C.P. and Engelbrecht, H.-R. and Whitehead, J. and Halberstam, A.A. and MacIsaac, J.L. and Dever, K. and Tran, T.K. and Korinek, K. and Zimmer, Z. and Lee, N.R. and McDade, T.W. and Kuzawa, C.W. and Huffman, K.M. and Belsky, D.W. and Binder, E.B. and Czamara, D. and Korthauer, K. and Kobor, M.S.

DOI: 10.1101/2024.07.02.600461

Bayesian Decision Curve Analysis With Bayesdca

Statistics in Medicine

Netto Flores Cruz, G. and Korthauer, K.

DOI: 10.1002/sim.10277

Pterostilbene Targets Hallmarks of Aging in the Gene Expression Landscape in Blood of Healthy Rats

Molecular Nutrition and Food Research

Tello-Palencia, M.A. and Yang, T. and Sularz, O. and Demers, L.E. and Ma, Y. and Boycott, C. and Zhang, H.A. and Lubecka-Gajewska, K. and Kumar, S. and Ramsey, B.S. and Torregrosa-Allen, S. and Elzey, B.D. and Lanman, N.A. and Korthauer, K. and Stefanska, B.

DOI: 10.1002/mnfr.202400662

vmrseq: probabilistic modeling of single-cell methylation heterogeneity

Biorxiv

Shen, N. and Korthauer, K.

DOI: 10.1101/2023.11.20.567911

FTD-associated behavioural and transcriptomic abnormalities in 'humanized' progranulin-deficient mice: A novel model for progranulin-associated FTD

Neurobiology of Disease

DOI: 10.1016/J.NBD.2023.106138

Conservation and divergence of canonical and non-canonical imprinting in murids

Genome Biology

DOI: 10.1186/S13059-023-02869-1

Reversal of viral and epigenetic HLA class I repression in Merkel cell carcinoma

Journal of Clinical Investigation

DOI: 10.1172/JCI151666

Detecting Neuroendocrine Prostate Cancer Through Tissue-Informed Cell-Free DNA Methylation Analysis

Clinical Cancer Research

DOI: 10.1158/1078-0432.CCR-21-3762

Differential substrate use in EGF- and oncogenic KRAS-stimulated human mammary epithelial cells.

The FEBS journal

Keibler MA and Dong W and Korthauer KD and Hosios AM and Moon SJ and Sullivan LB and Liu N and Abbott KL and Arevalo OD and Ho K and Lee J and Phanse AS and Kelleher JK and Iliopoulos O and Stephanopoulos G

DOI: 10.1111/febs.15858 PubMed: 33811729

04 / 2021

A compositional model to assess expression changes from single-cell rna-seq data

Annals of Applied Statistics

Ma, X. and Korthauer, K. and Kendziorski, C. and Newton, M.A.

DOI: 10.1214/20-AOAS1423

Reprogramming of the FOXA1 cistrome in treatment-emergent neuroendocrine prostate cancer

Nature Communications

Baca, S.C. and Takeda, D.Y. and Seo, J.-H. and Hwang, J. and Ku, S.Y. and Arafeh, R. and Arnoff, T. and Agarwal, S. and Bell, C. and O?Connor, E. and Qiu, X. and Alaiwi, S.A. and Corona, R.I. and Fonseca, M.A.S. and Giambartolomei, C. and Cejas, P. and Lim, K. and He, M. and Sheahan, A. and Nassar, A. and Berchuck, J.E. and Brown, L. and Nguyen, H.M. and Coleman, I.M. and Kaipainen, A. and De Sarkar, N. and Nelson, P.S. and Morrissey, C. and Korthauer, K. and Pomerantz, M.M. and Ellis, L. and Pasaniuc, B. and Lawrenson, K. and Kelly, K. and Zoubeidi, A. and Hahn, W.C. and Beltran, H. and Long, H.W. and Brown, M. and Corey, E. and Freedman, M.L.

DOI: 10.1038/s41467-021-22139-7

Androgen receptor and MYC equilibration centralizes on developmental super-enhancer

Nature Communications

DOI: 10.1038/S41467-021-27077-Y

CDK4/6 inhibition reprograms the breast cancer enhancer landscape by stimulating AP-1 transcriptional activity

Nature Cancer

April C. Watt and Paloma Cejas and Molly J. DeCristo and Otto Metzger-Filho and Enid Y. N. Lam and Xintao Qiu and Haley BrinJones and Nikolas Kesten and Rhiannon Coulson and Alba Font-Tello and Klothilda Lim and Raga Vadhi and Veerle W. Daniels and Joan Montero and Len Taing and Clifford A. Meyer and Omer Gilan and Charles C. Bell and Keegan D. Korthauer and Claudia Giambartolomei and Bogdan Pasaniuc and Ji-Heui Seo and Matthew L. Freedman and Cynthia Ma and Matthew J. Ellis and Ian Krop and Eric Winer and Anthony Letai and Myles Brown and Mark A. Dawson and Henry W. Long and Jean J. Zhao and Shom Goel

DOI: 10.1038/s43018-020-00135-y

11 / 2020

Transparency and reproducibility in artificial intelligence.

Nature

Haibe-Kains B and Adam GA and Hosny A and Khodakarami F and Massive Analysis Quality Control (MAQC) Society Board of Directors and Waldron L and Wang B and McIntosh C and Aerts HJWL

DOI: 10.1038/s41586-020-2766-y PubMed: 33057217

10 / 2020

Detection of urothelial carcinoma using plasma cell-free methylated DNA.

Journal of Clinical Oncology

DOI: 10.1200/jco.2020.38.15_suppl.5046

05 / 2020

Author Correction: Detection of renal cell carcinoma using plasma and urine cell-free DNA methylomes (Nature Medicine, (2020), 26, 7, (1041-1043), 10.1038/s41591-020-0933-1)

Nature Medicine

Nuzzo, P.V. and Berchuck, J.E. and Korthauer, K. and Spisak, S. and Nassar, A.H. and Alaiwi, S.A. and Chakravarthy, A. and Shen, S.Y. and Bakouny, Z. and Boccardo, F. and Steinharter, J. and Bouchard, G. and Curran, C.R. and Pan, W. and Baca, S.C. and Seo, J.-H. and Lee, G.-S.M. and Michaelson, M.D. and Chang, S.L. and Waikar, S.S. and Sonpavde, G. and Irizarry, R.A. and Pomerantz, M. and De Carvalho, D.D. and Choueiri, T.K. and Freedman, M.L.

DOI: 10.1038/s41591-020-1078-y

Prostate cancer reactivates developmental epigenomic programs during metastatic progression

Nature Genetics

Pomerantz, M.M. and Qiu, X. and Zhu, Y. and Takeda, D.Y. and Pan, W. and Baca, S.C. and Gusev, A. and Korthauer, K.D. and Severson, T.M. and Ha, G. and Viswanathan, S.R. and Seo, J.-H. and Nguyen, H.M. and Zhang, B. and Pasaniuc, B. and Giambartolomei, C. and Alaiwi, S.A. and Bell, C.A. and O?Connor, E.P. and Chabot, M.S. and Stillman, D.R. and Lis, R. and Font-Tello, A. and Li, L. and Cejas, P. and Bergman, A.M. and Sanders, J. and van der Poel, H.G. and Gayther, S.A. and Lawrenson, K. and Fonseca, M.A.S. and Reddy, J. and Corona, R.I. and Martovetsky, G. and Egan, B. and Choueiri, T. and Ellis, L. and Garraway, I.P. and Lee, G.-S.M. and Corey, E. and Long, H.W. and Zwart, W. and Freedman, M.L.

DOI: 10.1038/s41588-020-0664-8

Plasma cell-free DNA variant analysis compared with methylated DNA analysis in renal cell carcinoma

Genetics in Medicine

Lasseter, K. and Nassar, A.H. and Hamieh, L. and Berchuck, J.E. and Nuzzo, P.V. and Korthauer, K. and Shinagare, A.B. and Ogorek, B. and McKay, R. and Thorner, A.R. and Lee, G.-S.M. and Braun, D.A. and Bhatt, R.S. and Freedman, M. and Choueiri, T.K. and Kwiatkowski, D.J.

DOI: 10.1038/s41436-020-0801-x

Detection of renal cell carcinoma using plasma and urine cell-free DNA methylomes

Nature Medicine

Nuzzo, P.V. and Berchuck, J.E. and Korthauer, K. and Spisak, S. and Nassar, A.H. and Abou Alaiwi, S. and Chakravarthy, A. and Shen, S.Y. and Bakouny, Z. and Boccardo, F. and Steinharter, J. and Bouchard, G. and Curran, C.R. and Pan, W. and Baca, S.C. and Seo, J.-H. and Lee, G.-S.M. and Michaelson, M.D. and Chang, S.L. and Waikar, S.S. and Sonpavde, G. and Irizarry, R.A. and Pomerantz, M. and De Carvalho, D.D. and Choueiri, T.K. and Freedman, M.L.

DOI: 10.1038/s41591-020-0933-1

Detection and accurate false discovery rate control of differentially methylated regions from whole genome bisulfite sequencing.

Biostatistics (Oxford, England)

Korthauer K and Chakraborty S and Benjamini Y and Irizarry RA

DOI: 10.1093/biostatistics/kxy007 PubMed: 29481604

07 / 2019

A practical guide to methods controlling false discoveries in computational biology

Genome Biology

Korthauer, K. and Kimes, P.K. and Duvallet, C. and Reyes, A. and Subramanian, A. and Teng, M. and Shukla, C. and Alm, E.J. and Hicks, S.C.

DOI: 10.1186/s13059-019-1716-1 PubMed: 31164141

Genome-wide repressive capacity of promoter DNA methylation is revealed through epigenomic manipulation

Keegan Korthauer and Rafael A. Irizarry

DOI: 10.1101/381145

08 / 2018

High-throughput identification of RNA nuclear enrichment sequences

The EMBO Journal

Chinmay J Shukla and Alexandra L McCorkindale and Chiara Gerhardinger and Keegan D Korthauer and Moran N Cabili and David M Shechner and Rafael A Irizarry and Philipp G Maass and John L Rinn

DOI: 10.15252/embj.201798452

03 / 2018

A Somatically Acquired Enhancer of the Androgen Receptor Is a Noncoding Driver in Advanced Prostate Cancer

Cell

Takeda, D.Y. and Spisk, S. and Seo, J.-H. and Bell, C. and O'Connor, E. and Korthauer, K. and Ribli, D. and Csabai, I. and Solymosi, N. and Szllsi, Z. and Stillman, D.R. and Cejas, P. and Qiu, X. and Long, H.W. and Tisza, V. and Nuzzo, P.V. and Rohanizadegan, M. and Pomerantz, M.M. and Hahn, W.C. and Freedman, M.L.

DOI: 10.1016/j.cell.2018.05.037

Detection and accurate False Discovery Rate control of differentially methylated regions from Whole Genome Bisulfite Sequencing

Keegan D. Korthauer and Sutirtha Chakraborty and Yuval Benjamini and Rafael A. Irizarry

DOI: 10.1101/183210

08 / 2017

IPI59: An Actionable Biomarker to Improve Treatment Response in Serous Ovarian Carcinoma Patients

Statistics in Biosciences

Choi, J. and Ye, S. and Eng, K.H. and Korthauer, K. and Bradley, W.H. and Rader, J.S. and Kendziorski, C.

DOI: 10.1007/s12561-016-9144-1

A statistical approach for identifying differential distributions in single-cell RNA-seq experiments

Genome Biology

Korthauer, K.D. and Chu, L.-F. and Newton, M.A. and Li, Y. and Thomson, J. and Stewart, R. and Kendziorski, C.

DOI: 10.1186/s13059-016-1077-y

scDD: A statistical approach for identifying differential distributions in single-cell RNA-seq experiments

Korthauer KD and Chu L and Newton MA and Li Y and Thomson J and Stewart R and Kendziorski C

DOI: 10.1101/035501

12 / 2015

MADGiC: A model-based approach for identifying driver genes in cancer

Bioinformatics

Korthauer, K.D. and Kendziorski, C.

DOI: 10.1093/bioinformatics/btu858

Chromosomal copy number alterations and HPV integration in cervical precancer and invasive cancer

Carcinogenesis

Bodelon, C. and Vinokurova, S. and Sampson, J.N. and den Boon, J.A. and Walker, J.L. and Horswill, M.A. and Korthauer, K. and Schiffman, M. and Sherman, M.E. and Zuna, R.E. and Mitchell, J. and Zhang, X. and Boland, J.F. and Chaturvedi, A.K. and Dunn, S.T. and Newton, M.A. and Ahlquist, P. and Wang, S.S. and Wentzensen, N.

DOI: 10.1093/carcin/bgv171

Methods for collapsing multiple rare variants in whole-genome sequence data

Genetic Epidemiology

Sung, Y.J. and Korthauer, K.D. and Swartz, M.D. and Engelman, C.D.

DOI: 10.1002/gepi.21820

Limited model antigen expression by transgenic fungi induces disparate fates during differentiation of adoptively transferred T cell receptor transgenic CD4 + T cells: Robust activation and proliferation with weak effector function during recall

Infection and Immunity

Wthrich, M. and Ersland, K. and Pick-Jacobs, J.C. and Gern, B.H. and Frye, C.A. and Sullivan, T.D. and Brennan, M.B. and Filutowicz, H.I. and O'brien, K. and Korthauer, K.D. and Schultz-Cherry, S. and Klein, B.S.

DOI: 10.1128/IAI.05326-11

The Genetic Network Controlling the Arabidopsis Transcriptional Response to Pseudomonas syringae pv. maculicola: Roles of Major Regulators and the Phytotoxin Coronatine

Molecular Plant-Microbe Interactions

DOI: 10.1094/MPMI-21-11-1408

Predicting Cancer Subtypes Using Survival-Supervised Latent Dirichlet Allocation Models

Advances in Statistical Bioinformatics

Keegan Korthauer and John Dawson and Christina Kendziorski

DOI: 10.1017/cbo9781139226448.019

Unraveling the spatial landscape of epigenomic signals

A common task in the interpretation of epigenomic data, which holds information about the genome not encoded in the DNA sequence itself, is the detection and inference of regions of interest. For example, it is of interest to detect segments of the genome that show significantly higher or lower DNA methylation levels with respect to disease state or developmental stage, as this particular modification to the DNA is known to influence gene regulation. However, the number of possible segments of all possible sizes is near infinite, leading to a massive multiple testing problem. Our group develops tailored statistical and computational approaches for powerful detection and inference of region-based epigenomic signals, while paying particular attention to spatial patterns. We are interested in designing and applying these techniques for the analysis of DNA methylation, histone modification, and chromatin accessibility assay data.

Predicting gene expression from epigenomic signals

It is widely known that epigenetic information, such as DNA methylation and histone modifications, plays a role in gene regulation. However, the prediction of gene expression from epigenomic signals is challenging due to interactions between different epigenomic marks as well as interactions between different regions of the genome. We are working on developing predictive models that account for these challenges and assess the predictive capacity for various epigenomic signals.

Understanding the genomic basis of complex traits

Our group develops computational approaches to study the genomic basis of a variety of complex traits. Our main focus areas currently include modeling the mutation spectrum of cancer genomes, revealing heterogeneity in single-cell gene expression during development, and characterizing the epigenomic landscape of prostate cancer. To maximize impact of our work, we also provide open source computational tools that enable other scientists to make meaningful biological insights.

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Our Research

At BC Children’s, we are making discoveries that save lives and transform health care for children in our province and around the world. Our research portfolio includes basic, clinical, population, and public health research.

EXPLORE OUR RESEARCH

Keegan Korthauer

PhD

Investigator, BC Children's Hospital

Academic Affiliations

Contact Information

Location

Publications

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Clinical Utility of Multicancer Detection in Symptomatic Patients: A Decision-Making Perspective

RAMEN: Dissecting individual, additive and interactive gene-environment contributions to DNA methylome variability in cord blood

Distinct Co-methylation Patterns in African and European Populations and Their Genetic Associations

Low oxygen promotes extravillous trophoblast progenitor expansion but restrains maturation

decemedip: hierarchical Bayesian modeling for cell type deconvolution of immunoprecipitation-based DNA methylomes

Complete reference genome and pangenome improve genome-wide detection and interpretation of DNA methylation using sequencing and array data

Accounting for differences between Infinium MethylationEPIC v2 and v1 in DNA methylation"based tools

Examining cellular heterogeneity in human DNA methylation studies: Overview and recommendations

Genetic Basis, Quantitative Nature, and Functional Relevance of Evolutionarily Conserved DNA Methylation

Complete Reference Genome and Pangenome Expand Biologically Relevant Information for Genome-Wide DNA Methylation Analysis Using Short-Read Sequencing and Array Data

Accounting for differences between Infinium MethylationEPIC v2 and v1 in DNA methylation-based tools

Bayesian Decision Curve Analysis With Bayesdca

Pterostilbene Targets Hallmarks of Aging in the Gene Expression Landscape in Blood of Healthy Rats

vmrseq: probabilistic modeling of single-cell methylation heterogeneity

FTD-associated behavioural and transcriptomic abnormalities in 'humanized' progranulin-deficient mice: A novel model for progranulin-associated FTD

Conservation and divergence of canonical and non-canonical imprinting in murids

Reversal of viral and epigenetic HLA class I repression in Merkel cell carcinoma

Detecting Neuroendocrine Prostate Cancer Through Tissue-Informed Cell-Free DNA Methylation Analysis

Differential substrate use in EGF- and oncogenic KRAS-stimulated human mammary epithelial cells.

A compositional model to assess expression changes from single-cell rna-seq data

Reprogramming of the FOXA1 cistrome in treatment-emergent neuroendocrine prostate cancer

Androgen receptor and MYC equilibration centralizes on developmental super-enhancer

CDK4/6 inhibition reprograms the breast cancer enhancer landscape by stimulating AP-1 transcriptional activity

Transparency and reproducibility in artificial intelligence.

Detection of urothelial carcinoma using plasma cell-free methylated DNA.

Author Correction: Detection of renal cell carcinoma using plasma and urine cell-free DNA methylomes (Nature Medicine, (2020), 26, 7, (1041-1043), 10.1038/s41591-020-0933-1)

Prostate cancer reactivates developmental epigenomic programs during metastatic progression

Plasma cell-free DNA variant analysis compared with methylated DNA analysis in renal cell carcinoma

Detection of renal cell carcinoma using plasma and urine cell-free DNA methylomes

Detection and accurate false discovery rate control of differentially methylated regions from whole genome bisulfite sequencing.

A practical guide to methods controlling false discoveries in computational biology

Genome-wide repressive capacity of promoter DNA methylation is revealed through epigenomic manipulation

High-throughput identification of RNA nuclear enrichment sequences

A Somatically Acquired Enhancer of the Androgen Receptor Is a Noncoding Driver in Advanced Prostate Cancer

Detection and accurate False Discovery Rate control of differentially methylated regions from Whole Genome Bisulfite Sequencing

IPI59: An Actionable Biomarker to Improve Treatment Response in Serous Ovarian Carcinoma Patients

A statistical approach for identifying differential distributions in single-cell RNA-seq experiments

scDD: A statistical approach for identifying differential distributions in single-cell RNA-seq experiments

MADGiC: A model-based approach for identifying driver genes in cancer

Chromosomal copy number alterations and HPV integration in cervical precancer and invasive cancer

Methods for collapsing multiple rare variants in whole-genome sequence data

Limited model antigen expression by transgenic fungi induces disparate fates during differentiation of adoptively transferred T cell receptor transgenic CD4 + T cells: Robust activation and proliferation with weak effector function during recall

The Genetic Network Controlling the Arabidopsis Transcriptional Response to Pseudomonas syringae pv. maculicola: Roles of Major Regulators and the Phytotoxin Coronatine

Predicting Cancer Subtypes Using Survival-Supervised Latent Dirichlet Allocation Models

Research

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Expand

Unraveling the spatial landscape of epigenomic signals

Predicting gene expression from epigenomic signals

Understanding the genomic basis of complex traits

Related News

Congratulations 2021 CIHR Project Grant Recipients!

Separating the signal from the noise: Q&A with Keegan Korthauer

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