Quality assessment of transcriptome data using intrinsic statistical properties.

ABSTRACT: In view of potential application to biomedical diagnosis, tight transcriptome data quality control is compulsory. Usually, quality control is achieved using labeling and hybridization controls added at different stages throughout the processing of the biologic RNA samples. These control measures, however, only reflect the performance of the individual technical manipulations during the entire process and have no bearing as to the continued integrity of the RNA sample itself. Here we demonstrate that intrinsic statistical properties of the resulting transcriptome data signal and signal-variance distributions and their invariance can be identified independently of the animal species studied and the labeling protocol used. From these invariant properties we have developed a data model, the pa

SUBMITTER: Brysbaert G 

PROVIDER: S-EPMC5054119 | biostudies-literature | 2010 Mar

REPOSITORIES: biostudies-literature