Technical considerations for placental tissue processing and the subsequent impact on genome-wide DNA methylation analysis
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ABSTRACT:
PROVIDER: PRJNA1123714 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:To assess the impact of postnatal processing on placental DNA methylation, array data from flash frozen placental tissue was compared to perfluorocarbon-immersed and formalin fixed paraffin embedded placental tissue. We observed tissue exposed to perfluorocarbon showed no significant DNA methylation differences when compared to unprocessed tissue, while formalin processing altered the quality and reliability of the data produced on the DNA methylation array platform. Placental DNA methylation allows for the study of gene-environment interactions that influence the fetal environment and development. Our study highlights that placental postprocessing techniques must be considered in the evaluation and interpretation of epigenetic studies.
2024-09-19 | GSE269799 | GEO
Project description:Transcript Mapping on Affymetrix ENCODE arrays for 3 different biological replicates of Placental Poly(A)+ RNA (each with either 2 or 3 technical replicates) Keywords = Transcript Mapping, Human, Affymetrix, Genome Tiling Arrays Keywords: other
2005-05-18 | GSE2671 | GEO
Project description:2-4-8 cell porcine embryo technical repeat dye-swap for Agilent EMPV1 (4x44k Format)
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Project description:Transcript Mapping on Affymetrix ENCODE arrays for 3 different biological replicates of Placental Poly(A)+ RNA (each with either 2 or 3 technical replicates) Keywords = Transcript Mapping, Human, Affymetrix, Genome Tiling Arrays Keywords: other
2010-06-10 | E-GEOD-2671 | biostudies-arrayexpress
Project description:RNA-seq: technical variability and sampling
| PRJNA234515 | ENA
Project description:Background: RNA-seq is revolutionizing the way we study transcriptomes. mRNA can be surveyed without prior knowledge of gene transcripts. Alternative splicing of transcript isoforms and the identification of previously unknown exons are being reported. Initial reports of differences in exon usage, and splicing between samples as well as quantitative differences among samples are beginning to surface. Biological variation has been reported to be larger than technical variation. In addition, technical variation has been reported to be in line with expectations due to random sampling. However, strategies for dealing with technical variation will differ depending on the magnitude. The size of technical variance, and the role of sampling are examined in this manuscript. Results: Independent Solexa/Illumina experiments containing technical replicates are analyzed. When coverage is low, large disagreements between technical replicates are apparent. Exon detection between technical replicates is highly variable when the coverage is less than 5 reads per nucleotide and estimates of gene expression are more likely to disagree when coverage is low. Although large disagreements in the estimates of expression are observed at all levels of coverage. Conclusions: Technical variability is too high to ignore. Technical variability results in inconsistent detection of exons at low levels of coverage. Further, the estimate of the relative abundance of a transcript can substantially disagree, even when coverage levels are high. This may be due to the low sampling fraction and if so, it will persist as an issue needing to be addressed in experimental design even as the next wave of technology produces larger numbers of reads. We provide practical recommendations for dealing with the technical variability, without dramatic cost increases.
2014-01-15 | GSE54068 | GEO
Project description:Background: RNA-seq is revolutionizing the way we study transcriptomes. mRNA can be surveyed without prior knowledge of gene transcripts. Alternative splicing of transcript isoforms and the identification of previously unknown exons are being reported. Initial reports of differences in exon usage, and splicing between samples as well as quantitative differences among samples are beginning to surface. Biological variation has been reported to be larger than technical variation. In addition, technical variation has been reported to be in line with expectations due to random sampling. However, strategies for dealing with technical variation will differ depending on the magnitude. The size of technical variance, and the role of sampling are examined in this manuscript. Results: Independent Solexa/Illumina experiments containing technical replicates are analyzed. When coverage is low, large disagreements between technical replicates are apparent. Exon detection between technical replicates is highly variable when the coverage is less than 5 reads per nucleotide and estimates of gene expression are more likely to disagree when coverage is low. Although large disagreements in the estimates of expression are observed at all levels of coverage. Conclusions: Technical variability is too high to ignore. Technical variability results in inconsistent detection of exons at low levels of coverage. Further, the estimate of the relative abundance of a transcript can substantially disagree, even when coverage levels are high. This may be due to the low sampling fraction and if so, it will persist as an issue needing to be addressed in experimental design even as the next wave of technology produces larger numbers of reads. We provide practical recommendations for dealing with the technical variability, without dramatic cost increases.
2014-01-15 | GSE54067 | GEO