Work Summary:

My PhD thesis (Summary part)
Bayesian inference for retrospective population genetics models using Markov chain Monte Carlo methods
is mainly about reconstructing recent genetic ancestry of a group of sampled individuals from a certain population using marker data.

Another recent topic of mine has been estimation of haplotype distributions from pooled SNP data (several individuals genotyped in one go).

Publications:

Pirinen M (2009):
Estimating population haplotype frequencies from pooled SNP data using incomplete prior information.
Bioinformatics (accepted).

Gasbarra G*, Kulathinal S*, Pirinen M* and Sillanpää MJ (2009):
Estimating haplotype frequencies by combining data from large DNA pools with database information.
IEEE/ACM Trans. on Computational Biology and Bioinformatics (accepted).
* denotes equal contribution

Gasbarra D, Pirinen M, Sillanpää MJ, and Arjas E (2009):
Bayesian quantitative trait locus mapping based on reconstruction of genealogical histories.
Genetics 183:709-721.

Pirinen M, Kulathinal S, Gasbarra D and Sillanpää MJ (2008):
Estimating population haplotype frequencies from pooled DNA samples using PHASE algorithm.
Genetics Research volume 90, issue 6, pp. 509-524.

Gasbarra D, Pirinen M, Sillanpää MJ, and Arjas E (2007):
Estimating Genealogies from Linked Marker Data: A Bayesian Approach.
BMC Bioinformatics 8:411

Gasbarra D, Pirinen M, Sillanpää MJ, Salmela E and Arjas E (2007):
Estimating Genealogies from Unlinked Marker Data: A Bayesian Approach.
Theoretical Population Biology 72:305-322

Pirinen M and Gasbarra D (2006):
Finding Consistent Gene Transmission Patterns on Large and Complex Pedigrees.
IEEE/ACM Trans. on Computational Biology and Bioinformatics vol.3 no.3:252-262

Research Areas:

Association analyses related to Wellcome Trust Case Control Consortium 2.
Modelling the genetic ancestry of the sampled individuals.

Software:

APE and Hippo live here.

Keywords

• association analyses
• pedigrees
• MCMC