asthma

<p><code>data.frame</code> with 51 SNPs and 6 epidemiological variables: country, gender, age, bmi, smoke ans case/control status.</p>

datasets

Functions to perform most of the common analysis in genome association studies are implemented. These analyses include descriptive statistics and exploratory analysis of missing values, calculation of Hardy-Weinberg equilibrium, analysis of association based on generalized linear models (either for quantitative or binary traits), and analysis of multiple SNPs (haplotype and epistasis analysis). Permutation test and related tests (sum statistic and truncated product) are also implemented. Max-statistic and genetic risk-allele score exact distributions are also possible to be estimated. The methods are described in Gonzalez JR et al., 2007 <doi: 10.1093/bioinformatics/btm025>.

Juan Gonzalez

SNPassoc

SNPs-Based Whole Genome Association Studies

Victor Moreno

Juan R Gonzalez

asthma function

<p>The <code>asthma</code> data frame has 1578 rows (individuals) and 57 columns (variables) of data from a genetic study on asthma.</p>

asthma: SNP data on asthma case-control study

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