new version of GHS_EXPRESS with probe signals and usefull changes
The original GHS_Express database was appended to the following article:
Zeller T, Wild P, Szymczak S, Rotival M, Schillert A, et al. (2010) Genetics and Beyond – The Transcriptome of Human Monocytes and Disease Susceptibility. PLoS ONE 5(5): e10693. doi:10.1371/journal.pone.0010693
The new version is based on probes rather than genes statistics and it provides results for less stringent SNP x probe signal association P-values (p<5x10-5 instead of p<10-5), this may be useful to replicate some cis-associations. The consequence is that the downloadable file is much larger than before (>600MB compressed). Other useful changes include naming of genotypes using base identifiers, the previous 0/1 naming sometimes raised ambiguities.
Note that for every cis association of interest it is important to check the possible presence of a SNP in the corresponding Illumina probe sequence using the most recent version of the 1000 genomes project database (http://browser.1000genomes.org/Homo_sapiens/Location/). Presence of a variant does not necessarily imply that a cis-association is spurious but it raises this possibility.
GRIDHAPLO: A grid package for Genome Wide Haplotype Association Study (GWHAS).
GridHaplo implements a sliding windows haplotype analysis approach for
analyzing GWAS SNP data set as described in Tregouet et al. GridHaplo is still under development but its beta version is available for download.
A new JAVA interface implementation of THESIAS: testing haplotype effects in association studies
THESIAS is a popular software for carrying haplotype association analysis in unrelated individuals. In addition to the command line interface, a graphical JAVA interface is now proposed allowing one to run THESIAS in an user-friendly manner. Besides, new functionalities have been added to THESIAS including the possibility to analyse polychotomous phenotype and X-linked polymorphisms.
DICE in Genetic Association Studies of Complex Traits
Approaching complex diseases by studying one or a few genetic polymorphisms has shown its limitations. It is now increasingly recognized that understanding the genetic basis of complex phenotypes requires not only to investigate all polymorphisms located in functional regions of candidate genes but also to integrate information about the network of genes involved in biological systems of major physiological importance, such as lipid metabolism, cellular adhesion, inflammation...
