Compared to other studies (or software packages) that focus on robust association tests, the method presented here allows for both quantitative and binary outcomes and is able to deal with covariates.
The methodology described above has been implemented, for both quantitative and binary phenotypes, in the open-source IntRapid software, and is freely available for download from the website http://www.well.ox.ac.uk/INTRAPID.ac.uk/INTRAPID
The open-source software has been designed to efficiently handle analysis of directly genotyped and imputed rare variants on a genome-wide scale, and can accommodate both quantitative traits and binary phenotypes in a generalised linear modelling framework, as described above.
For quantitative and binary variables, potentially transmitted with the -1438A/G polymorphism, the PBAT test was used [ 28].
Statistical methods as linear or logistic regressions measure marker wise the actual association of the genetic variants with quantitative and binary diseases and traits.
The differences in values between two groups were evaluated by Chi analysis for frequencies or student t test for quantitative index and binary logistic regression was done using SPSS 11.5 software (SPSS Inc, Chicago, Illinois, USA).
A large study pooling data from the 4 registered phases I and II trials of florbetapir PET imaging, confirmed the ability of florbetapir uptake analysis to characterize amyloid levels in clinically probable AD, MCI, and HC groups using both continuous and binary quantitative measures of amyloid burden [ 70].
Genome-wide association studies of quantitative trait loci and binary trait loci in 500 Mn-exposed workers were performed using Illumina Infinium HumanExome BeadChip arrays.
GWAS of quantitative trait loci (QTL) and binary trait loci (BTL) will be performed for exposed workers using the Infinium HumanExome BeadChip array (V.1.0, 12-sample HD; Illumina).
The authors study the trade-offs between TextRunner, a state-of-the-art Open IE, and SRL-based extractor across a broad range of metrics and experimental conditions, both qualitative (such as N-ary and binary relations) and quantitative (such as small and large corpus).
Our framework covers all major study designs (i.e., case-control, cross-sectional, cohort and family studies) and all common phenotypes (e.g., binary, quantitative, and age at onset), and it allows arbitrary covariates (e.g., environmental factors and ancestry variables).
