Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
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TY - JOUR
T1 - Recovering Independent Associations in Genetics: A Comparison
AU - Sperrin, Matthew
AU - Jaki, Thomas
PY - 2012/8
Y1 - 2012/8
N2 - In genetics, it is often of interest to discover single nucleotide polymorphisms (SNPs) that are directly related to a disease, rather than just being associated with it. Few methods exist, however, for addressing this so-called “true sparsity recovery” issue. In a thorough simulation study, we show that for moderate or low correlation between predictors, lasso-based methods perform well at true sparsity recovery, despite not being specifically designed for this purpose. For large correlations, however, more specialized methods are needed. Stability selection and direct effect testing perform well in all situations, including when the correlation is large.
AB - In genetics, it is often of interest to discover single nucleotide polymorphisms (SNPs) that are directly related to a disease, rather than just being associated with it. Few methods exist, however, for addressing this so-called “true sparsity recovery” issue. In a thorough simulation study, we show that for moderate or low correlation between predictors, lasso-based methods perform well at true sparsity recovery, despite not being specifically designed for this purpose. For large correlations, however, more specialized methods are needed. Stability selection and direct effect testing perform well in all situations, including when the correlation is large.
U2 - 10.1089/cmb.2011.0141
DO - 10.1089/cmb.2011.0141
M3 - Journal article
VL - 19
SP - 978
EP - 987
JO - Journal of Computational Biology
JF - Journal of Computational Biology
SN - 1066-5277
IS - 8
ER -