Protocol matters – reproducibility and rigor of DNA methylation data sets
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ABSTRACT:
PROVIDER: PRJNA692176 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Protocol matters – reproducibility and rigor of DNA methylation data sets [RNA-seq]
| PRJNA691974 | ENA
Project description:Protocol matters – reproducibility and rigor of DNA methylation data sets [BiSulfite-seq]
| PRJNA692180 | ENA
Project description:While epigenetics continues to be a burgeoning research area in neuroscience, unaddressed issues related to data reproducibility across laboratories remain. Indeed, separating meaningful experimental changes from background variability is a challenge in epigenomic studies. Genome-wide DNA methylation analysis of hippocampal tissues from wild-type rats across three independent laboratories revealed that seemingly minor protocol differences resulted in significant epigenome profile changes, even in the absence of experimental intervention. Difficult-to-match factors such as animal vendors and a subset of husbandry and tissue extraction procedures produced quantifiable variations between wild-type animals across the three laboratories. To enhance scientific rigor, we conclude that strict adherence to protocols is necessary for the execution and interpretation of epigenetic studies and that protocol-sensitive epigenetic changes, amongst naive animals, may confound experimental results.
2022-01-12 | GSE164831 | GEO
Project description:While epigenetics continues to be a burgeoning research area in neuroscience, unaddressed issues related to data reproducibility across laboratories remain. Indeed, separating meaningful experimental changes from background variability is a challenge in epigenomic studies. Genome-wide DNA methylation analysis of hippocampal tissues from wild-type rats across three independent laboratories revealed that seemingly minor protocol differences resulted in significant epigenome profile changes, even in the absence of experimental intervention. Difficult-to-match factors such as animal vendors and a subset of husbandry and tissue extraction procedures produced quantifiable variations between wild-type animals across the three laboratories. To enhance scientific rigor, we conclude that strict adherence to protocols is necessary for the execution and interpretation of epigenetic studies and that protocol-sensitive epigenetic changes, amongst naive animals, may confound experimental results.
2022-01-12 | GSE164800 | GEO
Project description:This SuperSeries is composed of the SubSeries listed below.
2022-01-12 | GSE164833 | GEO
Project description:The kidney differentiation protocol takes induced pluripotent stem cells through to kidney organoid via directed differentiation in approximately 25 days. The cells are grown in a monolayer in a dish for seven days and are subjected to growth factors before being pelleted on day seven. The organoids then continue to differentiate as a 3D structure, with at least 8 distinct kidney cell types identifiable around day 18. Here we investigate the reproducibility of the kidney differentiation protocol using RNA sequencing from day 18 organoids. Organoid differentiations were performed in separate batches, and within one of the batches, from three separate vials. The resulting RNA-seq data was analysed to identify genes with highly variable expression between batches and vials.
2018-10-31 | GSE89044 | GEO
Project description:In this study, we present a comprehensive evaluation of four RNA-Seq library preparation methods. We used three standard input protocols, the Illumina TruSeq Stranded Total RNA and TruSeq Stranded mRNA kits, and a modified NuGEN Ovation v2 kit; and an ultra-low-input RNA protocol, the TaKaRa SMARTer Ultra Low RNA Kit v3. Our evaluation of these kits included quality control measures such as overall reproducibility, 5’ and 3’ end-bias, and the identification of DEGs, lncRNAs, and alternatively spliced transcripts. Overall, we found that the two Illumina kits were most similar in terms of recovering DEGs, and the Illumina, modified NuGEN, and TaKaRa kits allowed identification of a similar set of DEGs. However, we also discovered that the Illumina, NuGEN and TaKaRa kits each enriched for different sets of genes.
2019-06-27 | GSE131397 | GEO
Project description:In this study, we present a comprehensive evaluation of four RNA-Seq library preparation methods. We used three standard input protocols, the Illumina TruSeq Stranded Total RNA and TruSeq Stranded mRNA kits, and a modified NuGEN Ovation v2 kit; and an ultra-low-input RNA protocol, the TaKaRa SMARTer Ultra Low RNA Kit v3. Our evaluation of these kits included quality control measures such as overall reproducibility, 5’ and 3’ end-bias, and the identification of DEGs, lncRNAs, and alternatively spliced transcripts. Overall, we found that the two Illumina kits were most similar in terms of recovering DEGs, and the Illumina, modified NuGEN, and TaKaRa kits allowed identification of a similar set of DEGs. However, we also discovered that the Illumina, NuGEN and TaKaRa kits each enriched for different sets of genes.
2019-06-27 | GSE131396 | GEO
Project description:Reproducibility in molecular and cellular studies is fundamental to scientific discovery. To establish the reproducibility of a well-defined long term neuronal differentiation protocol, we repeated the cellular and molecular comparison of the same two iPSC lines across five distinct laboratories. Despite uncovering acceptable variability within individual laboratories, we detect poor cross-site reproducibility of the differential gene expression signature between these two lines. Factor analysis identifies the laboratory as the largest source of variation along with several variation-inflating confounds such as passaging effects and progenitor storage. Single cell transcriptomics shows substantial cellular heterogeneity underlying inter-laboratory variability and being responsible for biases in differential gene expression inference. Factor analysis-based normalization of the combined dataset can remove the nuisance technical effects, enabling the execution of robust hypothesis generating studies. Our study shows that multi-center collaborations can expose systematic biases and identify critical factors to be standardized when publishing novel protocols, contributing to increased cross-site reproducibility.
2018-08-20 | GSE118733 | GEO
Project description:Reproducibility in molecular and cellular studies is fundamental to scientific discovery. To establish the reproducibility of a well-defined long term neuronal differentiation protocol, we repeated the cellular and molecular comparison of the same two iPSC lines across five distinct laboratories. Despite uncovering acceptable variability within individual laboratories, we detect poor cross-site reproducibility of the differential gene expression signature between these two lines. Factor analysis identifies the laboratory as the largest source of variation along with several variation-inflating confounds such as passaging effects and progenitor storage. Single cell transcriptomics shows substantial cellular heterogeneity underlying inter-laboratory variability and being responsible for biases in differential gene expression inference. Factor analysis-based normalization of the combined dataset can remove the nuisance technical effects, enabling the execution of robust hypothesis generating studies. Our study shows that multi-center collaborations can expose systematic biases and identify critical factors to be standardized when publishing novel protocols, contributing to increased cross-site reproducibility.
2018-08-20 | GSE118734 | GEO