Identification of a robust non-coding RNA signature in diagnosing autism spectrum disorder by cross-validation of microarray data from peripheral blood samples.

ABSTRACT: Novel molecular signatures are needed to improve the early and accurate diagnosis of autism spectrum disorder (ASD), and indicate physicians to provide timely intervention. This study aimed to identify a robust blood non-coding RNA (ncRNA) signature in diagnosing ASD. One hundred eighty six blood samples in the microarray dataset were randomly divided into the training set (n = 112) and validation set (n = 72). Then, the microarray probe expression profile was re-annotated into the expression profile of 4143 ncRNAs though probe sequence mapping. In the training set, least absolute shrinkage and selection operator (LASSO) penalized generalized linear model was adopted to identify the 20-ncRNA signature, and a diagnostic score was calculated for each sample according to the ncRNA expression

SUBMITTER: Cheng W 

PROVIDER: S-EPMC7220435 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature