I've been using GenABEL for some time now for GWAS analysis using related individuals. It has an excellent set of functions for estimating a kinship matrix from a dense marker panel and then using this in a linear mixed effects model to allow for related individuals in the analysis of a quantitative trait. GenABEL also has many other nice features for analysis and visualization of GWAS data that you can't find in PLINK, it's free, cross-platform, and implemented in R. I'll write another post about GenABEL later, but here I wanted to note that GenABEL's creator, Yurii Aulchenko, released another package called ProbABEL for genome-wide association of imputed data. ProbABEL can perform imputation analyzing quantitative, binary, and survival outcomes while taking imputation uncertainty into account.
BMC Bioinformatics - ProbABEL package for genome-wide association analysis of imputed data
GenABEL tutorial and reference manual