Dr. Chen's overall research interests focus on developing statistical methods for analyzing 'big' integrative genomics data. Her lab has developed statistical methods for ‘omics’ studies that involve multiple types of large-scale high-dimensional data sets, for example, genetic data, gene transcriptional expression data, proteomic data and complex phenotypes. Besides methodology development, her lab has also developed many R packages.
Fred Hutchinson Cancer Research Center
Seattle
Postdoctoral Training - Statistical genomics
2010
University of Washington
Seattle
PhD - Biostatistics
2008
Peking University
Beijing
BS - Economics
2002
Integrated Proteogenomic Characterization of Clear Cell Renal Cell Carcinoma.
Integrated Proteogenomic Characterization of Clear Cell Renal Cell Carcinoma. Cell. 2020 Jan 09; 180(1):207.
PMID: 31923397
Using multivariate mixed-effects selection models for analyzing batch-processed proteomics data with non-ignorable missingness.
Using multivariate mixed-effects selection models for analyzing batch-processed proteomics data with non-ignorable missingness. Biostatistics. 2019 10 01; 20(4):648-665.
PMID: 29939200
Insights into Impact of DNA Copy Number Alteration and Methylation on the Proteogenomic Landscape of Human Ovarian Cancer via a Multi-omics Integrative Analysis.
Insights into Impact of DNA Copy Number Alteration and Methylation on the Proteogenomic Landscape of Human Ovarian Cancer via a Multi-omics Integrative Analysis. Mol Cell Proteomics. 2019 08 09; 18(8 suppl 1):S52-S65.
PMID: 31227599
Using multivariate mixed-effects selection models for analyzing batch-processed proteomics data with non-ignorable missingness.
Wang J, Wang P, Hedeker D, Chen LS. Using multivariate mixed-effects selection models for analyzing batch-processed proteomics data with non-ignorable missingness. Biostatistics. 2018 Jun 24.
PMID: 29939200
Co-occurring expression and methylation QTLs allow detection of common causal variants and shared biological mechanisms.
Co-occurring expression and methylation QTLs allow detection of common causal variants and shared biological mechanisms. Nat Commun. 2018 02 23; 9(1):804.
PMID: 29476079
A meta-analysis approach with filtering for identifying gene-level gene-environment interactions.
A meta-analysis approach with filtering for identifying gene-level gene-environment interactions. Genet Epidemiol. 2018 07; 42(5):434-446.
PMID: 29430690
Identifying cis-mediators for trans-eQTLs across many human tissues using genomic mediation analysis.
Identifying cis-mediators for trans-eQTLs across many human tissues using genomic mediation analysis. Genome Res. 2017 11; 27(11):1859-1871.
PMID: 29021290
Risk-based Breast Cancer Screening: Implications of Breast Density.
Risk-based Breast Cancer Screening: Implications of Breast Density. Med Clin North Am. 2017 Jul; 101(4):725-741.
PMID: 28577623
A MIXED-EFFECTS MODEL FOR INCOMPLETE DATA FROM LABELING-BASED QUANTITATIVE PROTEOMICS EXPERIMENTS.
A MIXED-EFFECTS MODEL FOR INCOMPLETE DATA FROM LABELING-BASED QUANTITATIVE PROTEOMICS EXPERIMENTS. Ann Appl Stat. 2017 Mar; 11(1):114-138.
PMID: 29743963
Imputing Gene Expression in Uncollected Tissues Within and Beyond GTEx.
Imputing Gene Expression in Uncollected Tissues Within and Beyond GTEx. Am J Hum Genet. 2016 Apr 07; 98(4):697-708.
PMID: 27040689
The Best Paper in Genetic Epidemiology Award for the Year 2021
International Genetic Epidemiology Society
2021 - 2022
Reviewer for BMRD study section
NIH
2020
Program Chair-Elect for the Section on Statistics in Genomics and Genetics
American Statistical Association
2020 - 2021
Associate Editor for Biometrics
2018
The Departmental Best Dissertation Award (for Dr. Chen's PhD student)
Department of Public Health Sciences
2017 - 2018