Competence classification of cumulus and granulosa cell transcriptome in embryos matched by morphology and female age

ABSTRACT: Mural granulosa cells (MGC) and cumulus cells (CC) were isolated immediately after oocyte retrieval during IVF treatment from the 16 competent and non competent follicles. mRNA was extracted resulting in 19 MGC and 27 CC samples of sufficient quality to be included in the study and expression profiles were generated on the Human Gene 1.0 ST Affymetrix array . Prediction of live birth after embryo transfer was performed using machine learning algorithms (support vector machines) with performance estimation by leave-one-out cross validation and independent validation on an external data set. We defined a signature of 30 genes expressed in CC predictive of live birth. This live birth prediction model had an accuracy of 81%, a sensitivity of 0.83, a specificity of 0.80, a positive predictive v

ORGANISM(S): Homo sapiens

SUBMITTER: Rehannah Borup Helweg-Larsen 

PROVIDER: E-MTAB-4012 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress