Structural Variant Discovery: Fast, statistical "next-generation
methods" for discovery of genetic variants in next-generation sequenced
Software: CLEVER & (soon) LASER
Statistical Modeling: A special focus is on Markovian and latent variable, such as hidden Markov and mixture models. On the theoretical end, the emphasis sometimes is on algebraic aspects.
- Alex has received a Vidi grant for research on the Genome of the Netherland!
- Alex presents Mate-Clever and Laser at
- "Statistical Genomics and Data Integration for Personalized Medicine", Ascona, 17 May
- Ben Raphael's lab, Brown University, Providence, 7 Jun
- Li Ding's lab, The Genome Institute, Wash U, St. Louis, 18 Jun
Mendelian-Inheritance-Aware Discovery and Genotyping of Midsize and Long Indels. T. Marschall et al. ISMB-HitSeq 2013.
Discovering motifs that induce sequencing errors.
M. Allhoff et al., BMC Bioinformatics (Recomb-Seq 2013).
[ Publisher Link]
CLEVER: Clique-enumerating variant finder.
T. Marschall et al., Recomb-Seq, ISMB-HitSeq and Bioinformatics, 2012.
[ Publisher Link ]
- CLEVER - Fast, reliable and user-friendly prediction of structural variants in next-gen-sequenced genomes.
- DCSSE - Discovery of motifs that induce next-generation sequencing errors.
- wDCB - Inference of subnetwork cancer markers using density-constrained biclustering.
- MirrorTreeTop - Efficient, score-optimal alignment of co-evolving gene trees in the presence of paralogs.