MLPA identification of dystrophin mutations and in silico evaluation of the predicted protein in dystrophinopathy cases from India
BMC Medical Genetics2017Vol. 18(1), pp. 67–67
Citations Over TimeTop 20% of 2017 papers
Sekar Deepha, Seena Vengalil, Veeramani Preethish‐Kumar, Kiran Polavarapu, Atchayaram Nalini, Narayanappa Gayathri, Meera Purushottam
Abstract
We found that, while the predictions made by the software utilized might have overall significance, the results were not convincing on a case by case basis. This reflects the inadequacy of the currently available tools and also underlines the possible inadequacy of MLPA to detect other minor mutations that might enhance or suppress the effect of the primary mutation in this large gene. Next Generation Sequencing or targeted Sanger sequencing on a case by case basis might improve phenotype- genotype correlation.
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