BBS Faculty Member - X. Shirley Liu

X. Shirley Liu

Department of Biostatistics and Computational Biology

Dana-Farber Cancer Institute
Center for Life Science Bldg 11007
450 Brookline Ave.
Boston, MA 02215
Tel: 617-632-2472
Fax: 617-632-2444
Visit my lab page here.

The research in our laboratories are focused on the following three areas:

Bioinformatics: The development of high throughput genomic technologies has created many exciting opportunities as well as analysis challenges. Our group has developed some of the most widely used and cited bioinformatics methods to analyze high throughput data. Our transcription factor motif finding tools have been cited over 1500 times and our ChIP-chip/seq peak callers have over 6,000 registered users. We will continue to develop novel computational algorithms to analyze new high throughput data, such as ChIP-seq (MACS, CEAS), RIP-seq, DNase-seq, MNase-seq (NPS), DNA-seq, and RNA-seq (Gfold). We will also build integrative analysis pipelines (Cistrome) to better help experimental biologists, and conduct efficient data integration to better mine the hidden biological insights from publicly available high throughput data and refine hypotheses. Finally, we will integrate good genomics experimental design and bioinformatics analyses to best utilize the newest technologies in gene regulation studies.

Epigenetics: Epigenetics play an important role in gene regulation, and include diverse topics such as DNA methylation, nucleosome positioning, histone marks, epigenetic enzymes, and higher order chromatin interactions. We and colleagues generated the first high throughput nucleosome map in the human genome, identified monovalent genes in early embryonic development, and found the relationship between H3K36me3 exon enrichment and co-transcriptional splicing. We will focus on two major areas of epigenetic research. The first is use the dynamics of histone mark ChIP-seq and DNase-seq to infer in vivo transcription factor binding and understand transcription regulatory networks. The second is to use genome-wide approaches to understand the specificity and mechanism of epigenetic enzymes and lncRNAs (with epigenetic function). Despite intensive research efforts, our knowledge about these areas is still limited, so there will be exciting opportunities in the future.

Cancer: As one in three people in the developed countries will get cancer, research on the mechanisms and treatments of cancer will become increasingly important. We and colleagues identified the function of estrogen receptor, androgen receptor, and FoxA1 in breast and prostate cancers, TET1 in leukemia, DREAM complex in cell cycle control, and found metabolic and autoimmune genes as signatures associated with cancer initiation. Cancer is a genetic disease amenable for research using genomic approaches. First, we will integrate publicly available high throughput data to better understand cancer pathways. Recently many cancer studies have found mutations or misregulations in epigenetic enzymes. Many pharmaceutical and biotech companies as well as academic scientists are actively developing cancer drugs targeting epigenetic enzymes. We will study the genome-wide function and response of cancer cells to epigenetic drugs, and identify cancer patients that might respond better to certain cancer drugs based on the genetic, epigenetic, and gene expression status of their tumor.

Last Update: 6/2/2014


Zhang Y#, Liu T#, Meyer CA, Eeckhoute J, Johnson DS, Bernstein B, Nusbaum C, Myers RM, Brown M, Li W, Liu XS (2008). Model-based analysis of ChIP-Seq (MACS). Genome Biol. 9(9):R137.

He HH#, Meyer C#, Shin H, Bailey ST, Wei G, Wang Q, Zhang Y, Xu K, Ni M, Lupien M, Mieczkowski P, Lieb JD, Zhao K, Brown M*, Liu XS* (2010). Nucleosome dynamics defines transcriptional enhancers. Nat Genet, 42(4):343-7.

Xu K#, Wu ZJ#, Anna C. Groner AC, He HH, Cai C, Lis RT, Wu X, Stack EC, Loda M, Liu T, Xu H, Cato L, Thornton JE, Gregory RI, Morrissey M, Vessella RL, Montironi R, Magi-Galluzzi C, Kantoff PW, Balk SP, Liu XS*, Brown M* (2012). EZH2 Oncogenic activity in castration resistant prostate cancer is polycomb-independent. Science. 338(6113):1465-9. PMCID:PMC3625962. (cited by 46)

Du Z#, Fei T#, Verhaak RGW, Su Z, Zhang Y, Brown M*, Chen C*, Liu XS* (2013). Integrative genomic analyses reveal clinically relevant long noncoding RNAs in human cancer. Nat Struct Mol Biol. 20:908-13.

He HH#, Meyer CA#, Hu SS#, Chen MW, Zang C, Liu Y, Rao PK, Fei T, Xu H, Long H*, Liu XS*, Brown M* (2014). Refined DNase-seq protocol and data analysis reveals intrinsic bias in transcription factor footprint identification. Nat Methods 11(1):73-8.

© 2015 by the President and Fellows of Harvard College