A graphical tool for evaluating the power of variance component multipoint linkage analysis studies through simulations.


PowQ allows power calculations of variance component linkage analysis studies through simulations for study samples that can comprise assorted family structures, including extended pedigrees.

The multipoint framework implemented in PowQ provides both accurate estimates of the expected power and confidence intervals for the location of the QTL. When the power study is evaluated in a region smaller than the expected confidence interval for the QTL location (or in a single-point framework) it is likely to provide an underestimate of the real dataset power.

PowQ also allows power comparisons of nested samples, which are easily calculated providing an initial sample and its possible extensions/reductions, both in terms of family units and in terms of family members. Relative power computation allows identification of the most informative and/or economical sample.

The user selects one pedigree file, or two for a comparative study, a map file with the markers position and the QTL position, and a genetic model for the simulated trait.

Founder individuals of each family belonging to the pedigree file are assumed to be unrelated, and founder haplotypes are assumed to be in linkage equilibrium.

Power is computed by randomly sampling from the inheritance space, assuming complete knowledge of IBD sharing among pedigree members and counting the number of times the test statistic falls above the required thresholds.





Input files format

Input parameters



Implementation details





PowQ was developed by Mario Falchi at the Twin Research Unit and by Cesare Cappio Borlino at Shardna


The variance component linkage analysis approach follows the Merlin implementation (Abecasis et al 2001).


For any comments and suggestions, please email: mario.falchi@kcl.ac.uk




PowQ can be cited with the following paper:


Falchi M, Borlino CC. PowQ: a user-friendly package for the design of variance component multipoint linkage analysis studies.

Bioinformatics. 2006 Jun 1;22(11):1404-5.