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The ground or naive pluripotent state of human pluripotent stem cells (hPSCs), which was initially established in mouse embryonic stem cells (mESCs), is an emerging and tentative concept. To verify this vital concept in hPSCs, we performed a multivariate meta-analysis of major hPSC datasets via the combined analytic powers of percentile normalization, principal component analysis (PCA), t-distributed stochastic neighbor embedding (t-SNE), and SC3 consensus clustering. This robust bioinformatics approach has significantly improved the predictive values of our meta-analysis. Accordingly, we revealed various similarities or dissimilarities between some naive-like hPSCs (NLPs) generated from different laboratories. Our analysis confirms some previous studies and provides new evidence concerning the existence of three distinct naive-like pluripotent states. Moreover, our study offers global transcriptomic markers that define diverse pluripotent states under various hPSC growth protocols. [ABSTRACT FROM AUTHOR]