Imprinted gene detection software tools | RNA sequencing data analysis
Dysregulation of imprinted genes, which are expressed in a parent-of-origin-specific manner, plays an important role in various human diseases, such as cancer and behavioral disorder. To date, however, fewer than 100 imprinted genes have been identified in the human genome. The recent availability of high-throughput technology makes it possible to have large-scale prediction of imprinted genes.
Identifies imprinted genes with high sensitivity and specificity and a low false discovery rate (FDR) when the number of sequenced tissue samples was fairly large. dsPIG is a Bayesian model which allows to measure the imbalance of allelic expression among various tissues and calculate the posterior probability of imprinting status for each gene. By applying dsPIG to mRNA-Seq data, 94 imprinted genes in 20 cerebellum samples and 57 imprinted genes in 9 diverse tissue samples with expected low FDR were predicted.
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