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  Project 2 : Computational approaches to deconvolute expression in tumour and normal cells from RNAseq data


   London Research Institute

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  Dr P Van Loo  No more applications being accepted  Funded PhD Project (Students Worldwide)

About the Project

This 4-year Crick PhD studentship is offered in Dr Peter Van Loo's Cancer Genomics Group based at the Cancer Research UK London Research Institute (LRI). There are two positons available to join the group in September 2015, this is position 2 of 2. The successful applicant will join the Crick PhD Programme in September 2015.

Genomic changes play a key role in the development and evolution of cancer, and, due to advances is sequencing technology, we are now beginning to understand what the key changes are that drive cancer. As the cancer genome gradually reveals its secrets, the next challenge comes into focus: to understand how these genomic changes lead to transcriptomic (and proteomic, interactomic, …) changes and thereby drive cancer development and evolution. As cancer samples contain both tumour cells and admixed normal cells, any measurement of the transcriptome represents a mix of expression signals from tumour cells and admixed normal cells, confounding the interpretation of the transcriptional state of the tumour cells. Gene expression analysis by massively parallel sequencing (RNAseq) allows allele-specific expression measurements. It can be shown that, given the fraction of tumour cells, the allele-specific copy number profiles of the tumour cells, and under a few reasonable hypotheses, the expression in tumour cells can be separated from that in normal cells. This would allow a unique view into cancer transcriptomes.
In this project, the successful candidate will develop approaches to deconvolute tumour-cell-specific expression signals from normal-cell-specific expression signals, using RNAseq data, and apply these methods to large pan-cancer RNAseq datasets. In the longer term, the methods developed in this project will be a key building block of an integrative genomics-transcriptomics approach to study the influence of point mutations, copy number changes and structural variants on transcription at the gene or transcript level and at the transcriptome level.
This position is suitable for a computational biologist, or a statistician, mathematician or physicist with a strong interest in biology.

The project above is an example of a research project available in the Cancer Genomics Group - the two projects will be decided on in consultation with the supervisor.

Talented and motivated students passionate about doing research are invited to apply for this PhD position. Students who join the 2015 Crick PhD Programme, will start their PhDs at the LRI in September 2015, will register for their PhD at one of the Crick partner universities (Imperial College London, King's College London or University College London), and will transfer into the Crick with their research group in early 2016.

Applicants should hold or expect to gain a first/upper second-class honours degree or equivalent in a relevant subject and have appropriate research experience as part of, or outside of, a university degree course and/or a Masters degree in a relevant subject.
APPLICATIONS MUST BE MADE ONLINE VIA OUR WEBSITE BY 5PM GMT NOVEMBER 12TH 2014. APPLICATIONS WILL NOT BE ACCEPTED IN ANY OTHER FORMAT.
http://www.london-research-institute.org.uk/phd/


Funding Notes

Successful applicants will be awarded a non-taxable annual stipend of £22,000 plus payment of university tuition fees. Students of all nationalities are eligible to apply.

References

1. Nik-Zainal S#, Van Loo P#, Wedge DC#, et al. The life history of 21 breast cancers. Cell. 2012;149:994-1007.
2. Bolli N, et al. Heterogeneity of genomic evolution and mutational profiles in multiple myeloma. Nat Commun. 2014;5:2997.
3. Van Loo P#, Nordgard SH#, Lingjærde OC, Russnes HG, Rye IH, Sun W, Weigman VJ, Marynen P, Zetterberg A, Naume B, Perou CM, Børresen-Dale AL#, Kristensen VN#. Allele-specific copy number analysis of tumors. Proc Natl Acad Sci U S A. 2010;107(39):16910-5.
4. Van Loo P, Voet T. Single cell analysis of cancer genomes. Curr Opin Genet Dev. 2014;24:82-91.