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Examine each gene and then build relationships with the other genes in the network. The results provided the best representation of biology in the database. The network is generated by calculating the co-expression between the genes and differentially expressed gene targets. The expression, clustering, and network of each gene is all determined by these results.
In many cases, it is possible to correct the problem, increase the number of sites being tested, increase the size of the library if necessary, and then retest those sites. However, these MRNAs are only useful for sites with a very high MAF in the specific population being tested.
In some cases, the outcome given by the online calculator is a single value that can be fed directly into a spreadsheet and multiplied by the beneficial allele frequency to obtain a predicted response.
We compared the enrichment of rare genetic variation across a panel of genes that do not typically support the phenotype under investigation with the same panel of genes that do support the phenotype. We focused on genes with existing variants linked to the phenotype, and tested for enrichment specifically in rare variants likely to be functionally important.
Twenty-one genes were shown to not be linked to the cardiac phenotype, and were used as negative controls. At the top of the list were the genes codeinhibitor (COI1), Calmodulin, BTB-POZ071, TFC1 , Bric à brac (a Bric a brac-Tramtrack nuclear export signal) and Actin-related family, which have no functional constraint on rare variation, and the oncogene
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