Other Association Testing
Click on a button corresponding to an association testing process not generally used for GWAS. Refer to the table below and the Comparison of Association Testing Processes for guidance.
Process |
Choose this process for... |
Testing association between various types of traits and numerically coded genotypes from multiple SNPs at a time using logistic, linear, survival regression, and generalized linear mixed models on SNP genotypes themselves or principal components used to represent the SNP genotypes |
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Rare Variant Tutorial |
Guiding you through the process needed to perform a particular method for association testing between a trait and rare variants within a gene or region |
Testing association between a trait or disease and rare variants, and optionally common variants, that occur in the same gene or pathway |
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Testing association between multiple traits (separately and jointly) and SNP genotypes or alleles from a single SNP at a time |
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Testing association between various types of traits and marker genotypes (using ANOVA) or alleles (using regression testing) from a single marker at a time, with many adjustments possible, including for Q and K matrices representing population structure and relatedness, respectively Caution: This process can take an inordinate amount of time and computational resources. Consider choosing SNP-Trait Association when analyzing SNPs or multiallelic markers that can be treated as SNPs based on the most frequent allele. |
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Testing association between various types of traits and the interaction between pairs of SNPs, adjusting for SNP main effects |
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Searching for pairs of SNPs predictive of a binary trait beyond the predictive ability of single SNPs, using penalized logistic regression (PLR) |
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Used to fit different combinations of Q and K variables and model fitness information from each model, such as AIC, AICC. |
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Testing association between various types of traits and SNP genotypes or alleles from a single SNP at a time, while adjusting simultaneously for population structure and family relatedness Note: You must already have computed the Q and K matrices. |
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Estimating the genetic variance explained by markers variables using a mixed model framework. |
See GWAS Testing for additional association testing processes.
See Genetics for other subcategories.