Statistical Bioinformatics Lab

Professor Wenyi Wang is a big data scientist. Her academic background is in both statistics and biology. Her main interest lies in wrangling with big data such as those in cancer multi-omics, and making sense out of it. Her lab’s statistical methodology development is data-driven a and often coupled with solving an important biological question. The lab’s two research focuses are:
1) Cancer risk prediction models using TP53 mutation-associated Li-Fraumeni syndrome as a model; and
2) Tumor heterogeneity and evolution using computational deconvolution of both transcriptomic and genomic data.

PI: Wenyi Wang

Department of Bioinformatics and Computational Biology

Wenyi Wang (王文漪) is an associate professor at Department of Bioinformatics and Computational Biology and Department of Biostatistics, MD Anderson Cancer center. She works in the area of statistical methods for high-throughput genomic data, cancer risk assessment and Bayesian modeling.

Curriculum Vitae

Latest News

GCC
10Jan
2019

MD/PhD student Carlos Vera Recio received NLM fellowship Congrats!

National Library of Medicine (NLM) Training Program in Biomedical Informatics and Data Science

19-3060_Dodd_V3
9Oct
2018

DeMixT paper accepted

Transcriptome Deconvolution of Heterogeneous Tumor Samples with Immune Infiltration will be published by iScience!

biostatspaper
9Sept
2018

Multiple primary model accepted

Our Bayesian estimation of a semiparametric recurrent event model for estimation of multiple primary cancers paper has been accepted by Biostatistics!

csrgithubpic
5May
2018

A new subclonal clustering method

Accompanying PCAWG11, our lab has developed is a new consensus clustering for subclonal reconstruction software, CSR (pronounced "Caesar").

hetpaperpic
5May
2018

PCAWG Results

A huge endeavor of the Pan-Cancer Analysis Working Group (PCAWG): Portraits of genetic intra-tumour heterogeneity (ITH) and subclonal selection across cancer types.

jasapaperpic
29Apr
2018

LFS statistical model accepted

Our first statistical modeling work for the Li-Fraumeni Syndrome (LFS) is acceptd by Journal of the American Statistical Association after a 3-year journey! Congrats everyone!

trainingprogrampic
29Apr
2018

Postdocs opportunities

My TAMU collaborator Val Johnson and I are jointly recruiting postdocs in cancer bioinformatics through this 2-year training program at TAMU. Citizenship or green card required. Send us your CV if interested.

Group Members

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