Data Analyst for rare genetic variant pathways
Rare variants are being investigated as the genetic basis of
inheritable diseases to account for the “missing heritability” problem
encountered by common variant studies. However, owing to their rarity,
it is hard to achieve statistically significant association at the
single variant or single gene level. Testing sets of genes (e.g.
pathways, protein complexes) instead of individual genes overcomes
this problem, by pooling sparse signals into a more consistent one. We
have been initially successful in the application of this type of
analysis to rare copy number variants (Pinto et al Nature 2010, see
link) and we are now interested in systematically adopting this
strategy for several medium and large-scale projects. We are also
interested in assessing the role played by specific parameters, such
as size or type of variants, evaluating results using different
statistical tests and exploring overlap with previously known disease
We are seeking a highly motivated bioinformatics data analyst focusing
on gene-set and pathway analysis for genetic rare variant data. The
typical analysis will involve scripting (preferred language: R) to
implement statistical tests and filters, followed by visualization
(using Cytoscape or other software tools) and critical discussion of
results. The successful candidate will be directly supervised by the
informatics facility manager and will interact with graduate students,
post-doctoral fellows or independent investigators.
The applicant will have a MSc (or PhD) in statistics, computer
science, physics, mathematics, computational biology, bioinformatics,
biology, genetics, biochemistry or medical sciences. Candidates with a
formal/quantitative background should be motivated in learning
essential genetics. Candidates with a biological background should be
motivated in strengthening their programming skills and understanding
of statistical models.
Knowledge of at least one scripting language (e.g. R, Python, Perl,
Matlab) is strictly required; proficiency in R programming is highly
desirable. Evidence of excellent communication and teamwork skills is
essential. A solid understanding of essential statistics (exploratory
data analysis, inferential statistics, clustering) is also required.
Candidates with previous experience in bioinformatics data analysis in
areas such as transcriptomics, proteomics, quantitative genetics,
network or pathways or metabolomics will be preferred.
The work will be conducted at the The Centre for Applied Genomics
(TCAG) / The Hospital for Sick Children (SickKids), Toronto, one of
the leading genomics centres in the world. Toronto is a major
international centre of genomics, proteomics and systems biology
research; there will ample opportunity for professional development
through research seminars, workshops and research in progress
Salary is commensurate with education and qualifications. Candidates
are encouraged to express a target salary range.
2 year contract, extendable in presence of funding.
HOW TO APPLY:
Please send your CV and the names of 3 references to
‘daniele.merico[at]sickkids.ca’. Please use the following subject:
‘Pathway Analyst Job: application’.
Open until position is filled.