Shuangge Steven Ma, PhD
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Affiliated Faculty, Yale Institute for Global Health; Director, Biostatistics and Bioinformatics Shared Resource
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About
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Department Chair and Professor of Biostatistics
Affiliated Faculty, Yale Institute for Global Health; Director, Biostatistics and Bioinformatics Shared ResourceBiography
Dr. Ma received his Ph.D. degree in statistics at University of Wisconsin in 2004. Prior to arriving at Yale, Dr. Ma was a Senior Fellow in Collaborative Health Studies Coordinating Center (CHSCC) and Department of Biostatistics at University of Washington. He has been involved in developing novel statistical and bioinformatics methodologies for analysis of cancer (NHL, breast cancer, melanoma, lung cancer), mental disorders, and cardiovascular diseases. He has also been involved in health economics research, with special interest in health insurance in developing countries.
Appointments
Biostatistics
ChairDualBiostatistics
ProfessorPrimary
Other Departments & Organizations
- Biostatistics
- Cancer Prevention and Control
- Center for Biomedical Data Science
- Center for Infection and Immunity
- Computational Biology and Biomedical Informatics
- Ma Lab
- SPORE in Lung Cancer
- SPORE in Skin Cancer
- Yale Cancer Center
- Yale Combined Program in the Biological and Biomedical Sciences (BBS)
- Yale Institute for Global Health
- Yale School of Public Health
- Yale Ventures
- YSPH Global Health Concentration
Education & Training
- Postdoctoral Associate
- University of Washington (2006)
- PhD
- University of Wisconsin (2004)
- MS
- University of California at Los Angeles (2000)
Research
Overview
Develop novel statistical methodologies for complex data;
Study epidemiology and pathogenesis of multiple cancers, including breast cancer, NHL, melanoma and lung cancer;
Conduct survey studies in mainland China and Taiwan, investigating health insurance utilization and impact;
Provide statistical support to multiple biomedical studies.
Medical Subject Headings (MeSH)
Biostatistics; Economics; Neoplasms
Research at a Glance
Yale Co-Authors
Frequent collaborators of Shuangge Steven Ma's published research.
Publications Timeline
A big-picture view of Shuangge Steven Ma's research output by year.
Research Interests
Research topics Shuangge Steven Ma is interested in exploring.
Tassos C. Kyriakides, PhD
Caroline Helen Johnson, PhD
Sajid A Khan, MD, FACS, FSSO
Xinyi Shen, MPH
Zhangsheng Yu
26Publications
46Citations
Publications
2024
HEARTSVG: a fast and accurate method for identifying spatially variable genes in large-scale spatial transcriptomics
Yuan X, Ma Y, Gao R, Cui S, Wang Y, Fa B, Ma S, Wei T, Ma S, Yu Z. HEARTSVG: a fast and accurate method for identifying spatially variable genes in large-scale spatial transcriptomics. Nature Communications 2024, 15: 5700. PMID: 38972896, PMCID: PMC11228050, DOI: 10.1038/s41467-024-49846-1.Peer-Reviewed Original ResearchAltmetricMeSH Keywords and ConceptsConceptsSpatially variable genesVariable genesSpatial expression patternsSpatial transcriptomics technologiesSpatial transcriptomics researchTranscriptome researchTranscriptomic technologiesBiological functionsExpression patternsSpatial transcriptomicsGenesState-of-the-art methodsColorectal cancer dataA penalized integrative deep neural network for variable selection among multiple omics datasets
Li Y, Ren X, Yu H, Sun T, Ma S. A penalized integrative deep neural network for variable selection among multiple omics datasets. Quantitative Biology 2024 DOI: 10.1002/qub2.51.Peer-Reviewed Original ResearchConceptsOmics data analysisAvailability of omics dataMultiple omics datasetsGene expression datasetsAggregate multiple datasetsDeep neural networksOmics dataIntegrated deep neural networkOmics datasetsExpression datasetsMultiple datasetsDeep learningDiverse originsNeural networkOmicsAbstract Deep learningVariable selection resultsSample sizeVariable selectionIntegrated analysis frameworkCognitive statusOvarian cancer patientsModel interpretationExtensive simulation studyDatasetPartial Hepatectomy and Ablation for Survival of Early-Stage Hepatocellular Carcinoma Patients: A Bayesian Emulation Analysis
Wang J, Im Y, Wang R, Ma S. Partial Hepatectomy and Ablation for Survival of Early-Stage Hepatocellular Carcinoma Patients: A Bayesian Emulation Analysis. Life 2024, 14: 661. PMID: 38929645, PMCID: PMC11204969, DOI: 10.3390/life14060661.Peer-Reviewed Original ResearchAltmetricConceptsOverall survivalHepatocellular carcinomaPartial hepatectomyTumor sizeAssociated with inferior overall survivalEarly-stage hepatocellular carcinomaEarly-stage HCC patientsInferior overall survivalHepatocellular carcinoma patientsAblation armCarcinoma patientsAblation therapyNo significant differenceTreatment regimensHCC patientsEmulated target trialSurgical proceduresEffect of ablationHepatectomyPatientsCompare treatment effectsClinical treatmentSignificant differencePropensity scoreLogistic regressionPrediction Consistency Regularization for Learning with Noise Labels Based on Contrastive Clustering
Sun X, Zhang S, Ma S. Prediction Consistency Regularization for Learning with Noise Labels Based on Contrastive Clustering. Entropy 2024, 26: 308. PMID: 38667864, PMCID: PMC11049179, DOI: 10.3390/e26040308.Peer-Reviewed Original ResearchCitationsConceptsLabel noiseContrastive clusteringConsistency regularizationRegularization termPrediction consistencyClassification accuracyImpact of label noiseEffects of label noiseClassification taskClustering problemComprehensive experimentsNoise labelsLabel informationNeural networkClustering resultsSample recognitionNoise rateMitigate noiseNoiseClassificationModel performanceRegularizationPrototypeAccuracyLabelingInformation‐incorporated sparse hierarchical cancer heterogeneity analysis
Han W, Zhang S, Ma S, Ren M. Information‐incorporated sparse hierarchical cancer heterogeneity analysis. Statistics In Medicine 2024, 43: 2280-2297. PMID: 38553996, DOI: 10.1002/sim.10071.Peer-Reviewed Original ResearchMeSH Keywords and ConceptsOrganochlorine pesticides and risk of papillary thyroid cancer in U.S. military personnel: a nested case-control study
Rusiecki J, McAdam J, Denic-Roberts H, Sjodin A, Davis M, Jones R, Hoang T, Ward M, Ma S, Zhang Y. Organochlorine pesticides and risk of papillary thyroid cancer in U.S. military personnel: a nested case-control study. Environmental Health 2024, 23: 28. PMID: 38504322, PMCID: PMC10949709, DOI: 10.1186/s12940-024-01068-0.Peer-Reviewed Original ResearchCitationsAltmetricMeSH Keywords and ConceptsConceptsPapillary thyroid cancer riskNested case-control studyPapillary thyroid cancerCase-control studyOdds ratioBody mass index categoriesOrganochlorine pesticidesConfidence intervalsFindings of increased riskRisk of papillary thyroid cancerConditional logistic regressionPre-diagnostic serum samplesIndividually-matched controlsThyroid cancerFollicular variant papillary thyroid cancerSerum concentrationsVariant papillary thyroid cancerEffect modificationU.S. military personnelBirth cohortPapillary thyroid cancer casesBirth yearIndex categoriesDecreased riskEffects of organochlorine pesticidesEndocrine disrupting chemical mixture exposure and risk of papillary thyroid cancer in U.S. military personnel: A nested case-control study
Denic-Roberts H, McAdam J, Sjodin A, Davis M, Jones R, Ward M, Hoang T, Ma S, Zhang Y, Rusiecki J. Endocrine disrupting chemical mixture exposure and risk of papillary thyroid cancer in U.S. military personnel: A nested case-control study. The Science Of The Total Environment 2024, 922: 171342. PMID: 38428594, PMCID: PMC11034764, DOI: 10.1016/j.scitotenv.2024.171342.Peer-Reviewed Original ResearchAltmetricMeSH Keywords and ConceptsConceptsPapillary thyroid cancer riskEndocrine disrupting chemicalsRisk of papillary thyroid cancerNested case-control studyPolychlorinated biphenylsOne-quartile increaseCase-control studyPapillary thyroid cancerOdds ratioWhite raceEvaluate associationsThyroid cancer riskBrominated flame retardantsEDC mixturesHistological subtypesChemical mixture exposureNon-statistically significant increaseBody mass indexQuantile g-computationOrganochlorine pesticidesSerum sampling timesCancer riskThyroid cancerU.S. military personnelStandard errorEstimation of multiple networks with common structures in heterogeneous subgroups
Qin X, Hu J, Ma S, Wu M. Estimation of multiple networks with common structures in heterogeneous subgroups. Journal Of Multivariate Analysis 2024, 202: 105298. PMID: 38433779, PMCID: PMC10907012, DOI: 10.1016/j.jmva.2024.105298.Peer-Reviewed Original ResearchConceptsGaussian graphical modelsMultiple networksGraphical modelsSparse regression problemHigh-dimensional data analysisNetwork estimationMinimax concave penaltyLarge-scale dataRegularized likelihoodJoint estimation approachRegression problemSelection consistency propertyConcave penaltyComplex dependence structureNetworkBreast cancer dataConsistency propertiesConvexity propertiesTCGA breast cancer dataNetwork identificationReparameterization techniqueEstimation approachDistributional assumptionsDependence structureBiological networks
2023
Hierarchical false discovery rate control for high-dimensional survival analysis with interactions
Liang W, Zhang Q, Ma S. Hierarchical false discovery rate control for high-dimensional survival analysis with interactions. Computational Statistics & Data Analysis 2023, 192: 107906. PMID: 38098875, PMCID: PMC10718515, DOI: 10.1016/j.csda.2023.107906.Peer-Reviewed Original ResearchAltmetricFunctanSNP: an R package for functional analysis of dense SNP data (with interactions)
Ren R, Fang K, Zhang Q, Ma S. FunctanSNP: an R package for functional analysis of dense SNP data (with interactions). Bioinformatics 2023, 39: btad741. PMID: 38060266, PMCID: PMC10723032, DOI: 10.1093/bioinformatics/btad741.Peer-Reviewed Original ResearchAltmetricMeSH Keywords
Clinical Trials
Current Trials
Molecular Markers of UV Exposure and Cancer Risk in Skin
HIC ID2000024848RoleSub InvestigatorPrimary Completion Date03/31/2024Recruiting Participants
Academic Achievements and Community Involvement
honor Fellow
International AwardASADetails05/01/2013United Statesactivity Health insurance in mainland China and Taiwan: utilization, impact, and policy interventions
ResearchDetails01/01/2013 - PresentChinaAbstract/SynopsisThe goal of this study is to provide an updated, comprehensive description of health insurance coverage and utilization and their impacts on health and economic outcomes. Special attention has been paid to the less-advantaged groups.
honor Elected Member
International AwardISIDetails06/01/2007United States
Links & Media
News
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- June 05, 2024
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- May 14, 2024
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- April 08, 2024
Award-Winning Statistician Joins Yale School of Public Health Leadership
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