What is the difference between
independence.test in R and CATT (Cochrane and Armitage) tests?
How these tests are calculated? Where do we and how do we define x=0.0 0.5 1.0 (genetic studies) for both of the tests?
As a follow-up to my comment, if
This is a conditional version of the CATT. About scoring of the ordinal variable (here, the frequency of the minor allele denoted by the letter
There are five different genetic models that are generally considered in GWAS, and they reflect how genotypes might be collapsed: codominant (T/T (92) C/T (53) C/C (12), yielding the usual $\chi^2(2)$ association test), dominant (T/T (92) vs. C/T-C/C (65)), recessive (T/T-C/T (145) vs. C/C (12)), overdominant (T/T-C/C (104) vs. C/T (53)) and log-additive (0 (92) < 1 (53) < 2 (12)). Note that genotype recoding is readily available in inheritance functions from the SNPassoc package. The "scores" should reflect these collapsing schemes.
Following Agresti (CDA, 2002, p. 182), CATT is computed as $n\cdot r^2$, where $r$ stands for the linear correlation between the numerical scores and the binary outcome (case/control), that is
There also exist various built-in CATT functions in R/Bioconductor ecosystem for GWAS, e.g.
Finally, here are two references that discuss the choice of scoring scheme depending on the genetic model under consideration, and some issues with power/robustness
See also the GeneticsDesign (bioc) package for power calculation with linear trend tests.