AI Article Synopsis
- The study aims to create a statistical method for identifying tissue-specific (TS) genes using RNA-seq data, focusing on data variability from tissue replicates.
- Simulations demonstrate that the method can accurately identify over 94% of true TS genes with a sample size of 3, and around 84% of detected TS genes are confirmed as true positives.
- The method effectively handles discrete data and incorporates variability, proving to be a reliable tool for detecting TS genes in RNA-seq projects.
Article Abstract
Aim: To develop an analytic method for identifying tissue-specific (TS) genes from RNA-seq data.
Materials & Methods: Based on a negative binomial distribution, we develop a statistical method containing consecutive procedures incorporating data variability from replicates in each tissue.
Results: Simulations show that our approach can effectively identify at least 94% of the truly TS genes if the sample size is 3 and at least 84% of the TS genes detected by our method are truly TS genes. We illustrated the utility of our method in an in-house RNA-seq project and produced sensible results.
Conclusion: Our approach not only directly works on discrete data but also naturally incorporates data variability. It works effectively for detecting TS genes.
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| http://dx.doi.org/10.2217/pgs.15.118 | DOI Listing |
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