Description Usage Arguments Details Value Author(s) References See Also Examples
Linear regression model to test whether the intrapair phenotypic differences in a continuous outcome (i.e., DNA methylation) in phenotype-discordant pairs are due to factors that are identical for both co-twins (i.e., a genotype). It is based on the work on Epigenetic Epidemiology by Tan, Q. (2013). It is similar to the abs_dif
function in this package, inspired by Berg, K. (1994).
1 |
formula |
an object of class |
data |
a data frame containing the variables in the model. |
... |
additional arguments to be passed to either |
Similar to the model implemented in the abs_dif
function in this package, log_dif
tests whether the logarithm of the difference in an outcome measure in phenotype-discordant pairs is explained by paired-level exposures such as age. Of note, the affected co-twin is set before (one row above of) his/her co-twin in the data
dataset.
This model was originally proposed by Tan, Q. (2013) in the context of Epigenetic Epidemiology, to evaluate whether phenotype-discordant pairs have DNA methylation differences due to pair-level exposures.
log_dif
returns an object of class
c("ols" "rms" "lm").
Aldo Cordova-Palomera.
Tan, Q. (2013). Epigenetic Epidemiology of Complex Diseases Using Twins. Medical Epigenetics, 1(1), 46-51.
Tan, Q., Frost, M., Heijmans, B. T., von Bornemann Hjelmborg, J., Tobi, E. W., Christensen, K., & Christiansen, L. (2014). Epigenetic signature of birth weight discordance in adult twins. BMC genomics, 15(1), 1062.
1 2 3 4 5 6 | data(flu_weight)
# The linear regression below tests whether DNA methylation differences at a
# given locus are predicted by pair level variables (such as gender, age
# or both).
(logarithm_differences <- log_dif(DNAmeth ~ Gender + Age, data=flu_weight))
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