Wenyi Wang, Ph.D.
Department of Bioinformatics and Computational Biology, Division of Basic Sciences
About Dr. Wang
Professor Wenyi Wang is a big data scientist with an academic background in both statistics and biology. Her main interests lie in using data wrangling to understand big data generated by cancer multi-omics. Her lab’s statistical methodology and tool development is data-driven and motivated by solving important and novel biological questions.
Present Title & Affiliation
Primary Appointment
Associate (Tenured) Professor, Department of Bioinformatics and Computational Biology, Division of Basic Science Research, The University of Texas MD Anderson Cancer Center, Houston, TX
Dual/Joint/Adjunct Appointment
Adjunct Faculty, Department of Statistics, Texas A&M, College Station, TX
Research Interests
The lab’s current major research focuses are:
1) Tumor heterogeneity and evolution using computational deconvolution of both transcriptomic and genomic data (inter-gromics), from both bulk sample and single cell sequencing data. Our goal is to understand a) tumor microenvironment that may lead to different outcomes in prognosis or response to treatment, b) the molecular mechanism of cell-cell interactions in normal tissues.
2) Personalized cancer risk prediction models, using TP53 mutation-associated Li-Fraumeni syndrome as a disease model; and novel statistical modeling and study design to further our understanding of the pan-cancer impact of TP53 mutations.
The lab uses statistical/computational toolbox as needed, including deep learning approaches. Our current focus is on mixture modeling and machine learning in high dimensional data.
Education & Training
Degree-Granting Education
| 2007 | Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA, PHD, Biostatistics |
| 2003 | Columbia University College of Physicians and Surgeons, New York City, NY, USA, MA, Human Nutrition |
| 2001 | Fudan University, Shanghai, CHN, BS, Biology |
Experience & Service
Academic Appointments
Assistant Professor, Division of Quantitative Sciences, The University of Texas MD Anderson Cancer Center, Houston, TX, 2010 - 2015
Administrative Appointments/Responsibilities
Admission Committee member, GSBS, Houston, TX, 2018 - Present
Quantitative Sciences Program Co-director, The University of Texas Graduate School of Biomedical Sciences at Houston, Houston, TX, 2014 - 2018
Other Appointments/Responsibilities
Program Chair, American Statistical Association Section on Statistical Genetics and Genomics, Alexandria, VA, 2018 - 2018
Faculty member, Baylor College of Medicine Graduate Program in Quantitative Computational Biology, Houston, TX, 2017 - Present
Honors & Awards
| 2014 | Outstanding service to graduate education, The University of Texas Graduate School of Biomedical Sciences at Houston |
| 2011 | The Stellar Abstract Award, The 5th Annual Program in Quantitative Genomics, Harvard School of Public Health |
| 2008 | The Jane and Steve Dykacz Award, Johns Hopkins University, Baltimore, MD |
| 2008 | Phi Beta Kappa Inducted Member, Johns Hopkins University Chapter of Phi Beta Kappa |
| 2008 | Delta Omega Alpha Inducted Member, Johns Hopkins Bloomberg School of Public Health |
| 2007 | Travel Award, The 11th International Conference on Research in Computational and Molecular Biology |
| 2006 | Travel Award, The International Genetic Epidemiology Society 15th Annual Meeting |
| 2005 | The June B. Culley Award, Johns Hopkins University, Baltimore, MD |
| 1997 | People's Scholarship, Fudan Univeristy, Shanghai, China |
| 1994 | Honor Science Program, Fundan University, Shanghai, China |
Selected Publications
Peer-Reviewed Articles
- Tarabichi M, Martincorena I, Gerstung M, Leroi AM, Markowetz F, PCAWG Evolution and Heterogeneity Working Group, Spellman PT, Morris QD, Lingjærde OC, Wedge DC, Van Loo P. Neutral tumor evolution?. Nat Genet 50(12):1630-1633, 2018. e-Pub 2018. PMID: 30374075.
- Wang Z, Morris JS, Cao S, Ahn J, Liu R, Tyekucheva S, Li B, Lu W, Tang X, Wistuba II, Bowden M, Mucci L, Loda M, Parmigiani G, Holmes CC, Wang W. Transcriptome deconvolution of heterogeneous tumor samples with immune infiltration. iScience, 2018. e-Pub 2018.
- Shin SJ, Li J, Ning J, Bojadzieva J, Strong LC, Wang W. Bayesian estimation of a semipara- metric recurrent event model with applications to the penetrance estimation of multiple primary cancers in Li-Fraumeni Syndrome. Biostatistics, 2018. e-Pub 2018.
- Shin SJ, Yuan Y*, Strong LC, Bojadzieva J, Wang W*. Bayesian semiparametric estimation of cancer-specific age-at-onset penetrance with application to Li-Fraumeni Syndrome. JASA, 2018. e-Pub 2018.
- Li J, Fu C, Speed TP, Wang W*, Symmans F*. Accurate RNA Sequencing From Formalin- Fixed Cancer Tissue to Represent High-Quality Transcriptome From Frozen Tissue. Journal of Clinical Oncology Precision Oncology, 2018. e-Pub 2018. PMID: 29862382.
- Holik AZ, Law CW, Liu R, Wang Z, Wang W, Ahn J, Asselin-Labat ML, Smyth GK, Ritchie ME. RNA-seq mixology: designing realistic control experiments to compare protocols and analysis methods. Nucleic Acids Res 45(5):e30, 2017. e-Pub 2016. PMID: 27899618.
- Lefterova MI, Shen P, Odegaard JI, Fung E, Chiang T, Peng G, Davis RW, Wang W, Kharrazi M, Schrijver I, Scharfe C. Next-generation molecular testing of newborn dried blood spots for cystic fibrosis. J Mol Diagn 18(2):267-82, 2016. e-Pub 2016. PMID: 26847993.
- Fan Y, Xi L, Hughes DS, Zhang J, Zhang J, Futreal PA, Wheeler DA, Wang W. MuSE: accounting for tumor heterogeneity using a sample-specific error model improves sensitivity and specificity in mutation calling from sequencing data. Genome Biol 17(1):178, 2016. e-Pub 2016. PMID: 27557938.
- Ahn J, Liu S, Wang W*, Yuan Y*. Bayesian latent-class mixed-effect hybrid models for dyadic longitudinal data with non-ignorable dropouts. Biometrics 69(4):914-24, 2013. e-Pub 2013. PMID: 24328715.
- Cancer Genome Atlas Research Network, Weinstein JN, Collisson EA, Mills GB, Shaw KR, Ozenberger BA, Ellrott K, Shmulevich I, Sander C, Stuart JM. The Cancer Genome Atlas Pan-Cancer analysis project. Nat Genet 45(10):1113-20, 2013. PMID: 24071849.
- Ahn J, Yuan Y, Parmigiani G, Suraokar MB, Diao L, Wistuba II, Wang W. DeMix: deconvolution for mixed cancer transcriptomes using raw measured data. Bioinformatics 29(15):1865-71, 2013. e-Pub 2013. PMID: 23712657.
- Peng G, Fan Y, Palculict TB, Shen P, Ruteshouser EC, Chi AK, Davis RW, Huff V, Scharfe C, Wang W. Rare variant detection using family-based sequencing analysis. Proc Natl Acad Sci U S A 110(10):3985-90, 2013. e-Pub 2013. PMID: 23426633.
- Srivastava S, Wang W, Manyam G, Ordonez C, Baladandayuthapani V. Integrating Multi-Platform Genomic Data Using Hierarchical Bayesian Relevance Vector Machines. EURASIP J Bioinform Syst Biol 2013(1):9, 2013. e-Pub 2013. PMID: 23809014.
- Hua Y, Gorshkov K, Yang Y, Wang W, Zhang N, Hughes DP. Slow down to stay alive: HER4 protects against cellular stress and confers chemoresistance in neuroblastoma. Cancer 118(20):5140-54, 2012. e-Pub 2012. PMID: 22415601.
- Zhang N, Xu Y, O'Hely M, Speed TP, Scharfe C, Wang W. SRMA: an R package for resequencing array data analysis. Bioinformatics 28(14):1928-30, 2012. e-Pub 2012. PMID: 22581181.
- Wilkins EJ, Rubio JP, Kotschet KE, Cowie TF, Boon WC, O'Hely M, Burfoot R, Wang W, Sue CM, Speed TP, Stankovitch J, Horne MK. A DNA Resequencing Array for Genes Involved in Parkinson's Disease. Parkinsonism Relat Disord 18(4):386-90, 2012. e-Pub 2012. PMID: 22243833.
- Shen P*, Wang W*, Krishnakumar S, Palm C, Chi AK, Enns GM, Davis RW, Speed TP, Mindrinos MN, Scharfe C. High quality DNA sequence capture of 524 disease candidate genes. Proc Natl Acad Sci U S A 108(16):6549-54, 2011. PMID: 21467225.
- Wang W, Shen P, Thiyagarajan S, Lin S, Palm C, Horvath R, Klopstock T, Cutler D, Pique L, Schrijver I, Davis RW, Mindrinos M, Speed TP, Scharfe C. Identification of Rare DNA Variants in Mitochondrial Disorders with Improved Array-based Sequencing. Nucleic Acids Res 39(1):doi: 10.1093/nar/gkq750, 2011. PMID: 20843780.
- Wang W, Niendorf KB, Patel D, Blackford A, Marroni F, Sober AJ, Parmigiani G, Tsao H. Estimating CDKN2A carrier probability and personalizing cancer risk assessments in hereditary melanoma using MelaPRO. Cancer Res 70(2):552-9, 2010. e-Pub 2010. PMID: 20068151.
- Lin S*, Wang W*, Palm C, Davis RW, Juneau K. A Molecular Inversion Probe Assay for Detecting Alternative Splicing. BMC Genomics 11:712, 2010. e-Pub 2010. PMID: 21167051.
- Wang W, Carvalho B, Miller ND, Pevsner J, Chakravarti A, Irizarry RA. Estimating genome-wide copy number using allele-specific mixture models. J Comput Biol 15(7):857-66, 2008. PMID: 18707534.
- Wang W, Chen S, Brune KA, Hruban RH, Parmigiani G, Klein AP. PancPRO: risk assessment for individuals with a family history of pancreatic cancer. J Clin Oncol 25(11):1417-22, 2007. PMID: 17416862.
- Nicodemus KK, Wang W, Shugart YY. Stability of variable importance scores and rankings using statistical learning tools on single-nucleotide polymorphisms and risk factors involved in gene x gene and gene x environment interactions. BMC Proc 1 Suppl 1:S58, 2007. e-Pub 2007. PMID: 18466558.
- González JR, Wang W, Ballana E, Estivill X. A recessive Mendelian model to predict carrier probabilities of DFNB1 for nonsyndromic deafness. Hum Mutat 27(11):1135-42, 2006. PMID: 16941638.
- Chen S, Wang W, Lee S, Nafa K, Lee J, Romans K, Watson P, Gruber SB, Euhus D, Kinzler KW, Jass J, Gallinger S, Lindor NM, Casey G, Ellis N, Giardiello FM, Offit K, Parmigiani G, Colon Cancer Family Registry. Prediction of germline mutations and cancer risk in the Lynch syndrome. JAMA 296(12):1479-87, 2006. PMID: 17003396.
- Xu Z, Sproul A, Wang W, Kukekov N, Greene LA. Siah1 interacts with the scaffold protein POSH to promote JNK activation and apoptosis. J Biol Chem 281(1):303-12, 2006. e-Pub 2005. PMID: 16230351.
- Chen S, Wang W, Broman KW, Katki HA, Parmigiani G. BayesMendel: an R environment for Mendelian risk prediction. Stat Appl Genet Mol Biol 3:Article21, 2004. e-Pub 2004. PMID: 16646800.
- Peng G, Fan Y, Wang W. FamSeq: a variant calling program for family-based sequencing data using graphics processing units. PLOS Comput Biol. e-Pub 2014. PMID: 25357123.
- Shen P*, Wang W* , Chi AK, Fan Y, Davis RW and Scharfe C. Multiplex target capture with long padlock probes. Genome Medicine(5):50. e-Pub 2013. PMID: 23718862.
- Davis CF et al., The Cancer Genome Atlas Research Network.. The Somatic Genomic Landscape of Chromophobe Renal Cell Carcinoma. Cancer Cell. e-Pub 2014.
- Ewing AD, Houlahan KE, Hu Y, Ellrott K, Caloian C, Yamaguchi TN, Bare JC, P’ng C, Waggott D, Sabelnykova VY; ICGC-TCGA DREAM Somatic Mutation Calling Challenge participants, Kellen MR, Norman TC, Haussler D, Friend SH, Stolovitzky G, Margolin AA, Stuart JM, Boutros PC.. Combining tumor genome simulation with crowdsourcing to benchmark somatic single-nucleotide- variant detection. Nature Methods. e-Pub 2015.
- Fang LT, Afshar PT, Chhibber A,Mohiyuddin M, Fan Y, Mu J, Gibeling G, Barr S, Asadi NB, Gerstein M, Koboldt D, Wang W, Wong WH, Lam H.. An ensemble approach to accurately detect so- matic mutations using SomaticSeq. Genome Biology. e-Pub 2015.
- Palculict TB, Ruteshouser EC, Fan Y, Wang W, Strong L, Huff V. Identification of germline DICER1 mutations and loss of heterozygosity in familial Wilms tumor using whole genome sequenc- ing. Journal of Medical Genetics. e-Pub 2015.
- Nikooienejad A, Wang W*, Johnson VE*.. Bayesian variable selection for binary outcomes in high dimensional genomic studies using non-local priors. Bioinformatics. e-Pub 2016.
- Ahn J, Morita S, Wang W*, Yuan Y*. Bayesian analysis of longitudinal dyadic data with informative missing data using a dyadic shared-parameter model. Stat Methods Med Res:962280217715051. e-Pub 2017. PMID: 28629259.
- McCarthy DJ, Rostom R, Huang Y,Kunz DJ,Danecek P, Bonder MJ, Hagai T, HipSci Consortium, Wang W, Gaffney DJ, Simons BD, Stegle O, Teichmann SA. Cardelino: Integrating whole exomes and single-cell transcriptomes to reveal phenotypic impact of somatic variants.
- Dentro S, et al., PCAWG Evolutionary and Heterogeneity Working Group-PCAWG network, Wang W*, Morris QA*, Wedge D*, Van Loo P*.. Portraits of genetic intra-tumour heterogeneity and sub- clonal selection across cancer types.
- Nikooienejad A, Wang W, Johnson VE. Bayesian variable selection in high dimensional survival time cancer genomic datasets using nonlocal priors.
- Gerstung M, et al., PCAWG Evolutionary and Heterogeneity Working Group-PCAWG network.. The evolutionary history of 2,658 cancers.
Grant & Contract Support
| Title: | Integrative Pipeline for Analysis & Translational Application of TCGA Data (GDAC) Supplement |
| Funding Source: | NIH/NCI |
| Role: | Co-Investigator |
| Title: | Next-Generation Genomic Sequence Identification of the 19q Familial Wilms Tumor Predisposition Gene |
| Funding Source: | Cancer Prevention & Research Institute of Texas (CPRIT) |
| Role: | Co-Investigator |
| Title: | Core C UT Spore in Lung Cancer |
| Funding Source: | NIH/NCI (subcontract from University of Texas Southwestern Medical Center) |
| Role: | Co-Investigator |
| Title: | An Integrative Pipeline for Analysis & Translational Application of TCGA Data (GDAC) |
| Funding Source: | NIH/NCI |
| Role: | Co-Investigator |
| Title: | Bioinformatics tools for genomic analysis of tumor and stromal pathways in cancer |
| Funding Source: | NIH/NCI (Subcontract from Dana Farber Cancer Institute) |
| Role: | Principal Investigator-MDACC |
| Title: | Personalized risk assessment for families with Li-Fraumeni Syndrome |
| Funding Source: | Cancer Prevention & Research Institute of Texas (CPRIT) |
| Role: | Principal Investigator |
| Title: | Statistical methods for genomic analysis of heterogeneous tumors |
| Funding Source: | NIH/NCI |
| Role: | Principal Investigator |
| Title: | GCC/Keck Center's Computational Cancer Biology Training Program |
| Funding Source: | Cancer Prevention Institute of Research (subcontract from University of Houston) |
| Role: | Principal Investigator-MDACC |
| Title: | An Integrative Pipeline for Analysis & Translational Application of TCGA Data (GDAC) |
| Funding Source: | NIH/NCI |
| Role: | Co-Investigator |
| Title: | Cancer risk in LI Fraumeni syndrome (LFS) kindreds in regions of high founder mutation prevalence and regions of low prevalence in absence of founder as determined by LFSpro |
| Funding Source: | MD Anderson Cancer Center The Sister Institution Network Fund |
| Role: | Co-Principal Investigator |
| Title: | Consistent variable selection in p>>n settings |
| Funding Source: | Subaward Agreement from Texas A & M via NIH |
| Role: | Principal Investigator-MDACC |