2014 BCB Rotation Advertisement
for Yun Li Group of Statistical and Computational Genetics and Genomics
Background: Li Group is recruiting rotation students from the BCB curriculum for year 2014-2015. My group develops statistical methods and computational tools for modern genetic, genomic, and epigenomic data. We do both method development and real data applications.
Qualifications: Solid background in Biology, Statistics and Computing. Just kidding: if you had all the above three, you can take my job. As a matter of fact, even I donÕt dare to say that I have ÒsolidÓ background in all three. The truth is that I look for people who have motivation/willingness-to-learn and the ability to learn and to think. If you get excited with us (me and my lab members), we can teach you, very quickly and painlessly ^_^. And then you should start to teach us something back!
Group Website: NOT very well maintained/updated É http://www.unc.edu/~yunmli/
Lab Members: (if you are interested in any project or in my lab in general, DO talk to them. I value their opinions A LOT!)
á Qing Duan, BCB PhD 4th year, firstname.lastname@example.org
á Guosheng Zhang, BCB PhD 4th year, email@example.com
á Kuan-Chieh Huang, Biostatistics PhD 5th year, firstname.lastname@example.org
á Suhua Chang, 1st year visiting scholar, email@example.com
á Song Yan, postdoctoral fellow, firstname.lastname@example.org
á Zheng Xu, postdoctoral fellow, email@example.com
á Eric Yi Liu, graduated 2013, PhD in Computer Science, now with Microsoft
á Andrea Byrnes, graduated 2013, PhD in Biostatistics, now with the Broad Institute
Projects: There are MANY SUPER exciting projects (well, at least to me and most of my team members) including (but not limited to and for good or bad, I am VERY open to new areas of research):
á Single cell transcriptome sequencing: there are trillions of cells in our body. Each of them is unique. How can we take measures from multiple single cells to answer questions like: Are there sub-populations in this tumor sample? Is the embryo from IVF viable with no genetic defect? Talk to: me (too obvious?), Zheng Xu, Suhua Chang, Qing Duan.
á DNA 3D structure: Chromosomes are heavily packed; but they are not packed in a random way. The structure they take, which is dynamic and has some stochasticity, is heavily associated with their function. My group is developing methods and software for data from 3C (Chromosome Conformation Capture) derived technologies. Talk to: me, Guosheng Zhang, Zheng Xu.
á (Bulk) Transcriptome sequencing analysis: Transcritome sequencing provides arguably (although few people argue nowadays; or agreement is almost unanimously reached) the most comprehensive information regarding the middle layer of the central dogma. We plan to perform real data analysis (not necessarily method development) in terms of: isoform quantification, eQTL, differential expression, differential splicing, use of phase-informative-reads (PIRs) to aid phasing. Talk to: me, Suhua (on use of PIRs).
á Genetic studies of Admixed Populations: African Americans and Hispanics are admixed, i.e., have their chromosomes from more than one ancestral populations. They provide excellent opportunities to boost both power and resolution for gene mapping, i.e., finding genes or genetic variants associated with phenotypic traits like blood lipid levels, height, risk of type 2 diabetes, cardiovascular diseases etc. Talk to: me, Qing Duan, Zheng Xu, Andrea Byrnes (former lab member).
á Epigenetic studies: DNA methylation is very important to study: there must be good reasons that the copy from our dad was COMPLETELY (well, nothing is exactly 100% in biology) de-methylated before we were formed as a single cell. Talk to: me, Guosheng Zhang, Song Yan.
á Analysis of DNA sequencing data. Although we are getting closer to $1,000 per genome, analysis still has a very high price tag. We have developed methods for genotype calling and haplotype construction in both unrelated and family data. We also developed online tools to help people with the design of sequencing-based studies. We have been developing methods for association analysis for both common and rare variants, for genetically both homogeneous and admixed populations. Talk to: me, Song Yan (association analysis part), Zheng Xu, Andrea Byrnes.
á Genotype imputation. In plain words, making up data, making up >90% of the data, and making them up smartly, quickly and accurately. We also develop methods to take the uncertainty in making-up/guessing data into subsequent analysis. Talk to: me, Qing Duan, Kuan-Chieh Huang, Eric Yi Liu.
á Your favorite project (as long as you can get my interest ^_^).