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The latter can be estimated using our method from case-control studies as described below.
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The method described above is based on data from case-control studies unadjusted for covariates.
We also present the results from case-control studies and show that standard methods may also overestimate power.
In the future we will extensively test our method using large case-control datasets from public databases such as the NCBI database of genotypes and phenotypes (dbGap) [ 24] and the Welcome Trust Case Control Consortium WTCCCC) [ 25].
The method integrates the case-control gene expression data with the TF binding data from ChIP-seq experiments.
Here we develop this method further for case-control studies.
Methods: A case-control study was performed with a total of 992 adult subjects, including 410 adult asthmatics and 582 healthy controls from regions of North India.
Methods: A case-control study was performed with a total of 992 subjects, including 410 adult asthmatics and 582 healthy controls from regions of North India.
Methods: The data came from a case-control design, nested in a community survey of elderly people.
It should be noted that Method H produced biased estimates from the case-control samples and the bias was more severe when the population frequency of the disease allele was used than when the frequency was directly estimated from the case-control samples.
We demonstrate major power advantages of our method both in analysis of data from a case-control study of the association between colorectal adenoma and DNA variants in the NAT2 genomic region, which are well known to be related to a common biological phenotype, and under different models of gene-gene interactions with use of simulated data.
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