Quartet Methylomics
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1010721 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:The Quartet Project aims to provide resources for QC of multiple types of omic technologies and the effective integration of diverse datasets from various scenarios. Large quantities of multi-omics materials, datasets, and best practices for their QC utilities were developed for whole process QC of large-scale, multi-center, and longitudinal multi-omics profiling.
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Project description:We experimented how well various supervised machine learning methods such as decision tree, partial least squares discriminant analysis (PLSDA), support vector machine and random forest perform in classifying endometriosis from the control samples trained on both transcriptomics and methylomics data. The assessment was done from two different perspectives for improving classification performances: (a) implication of three different normalization techniques, and (b) implication of differential analysis using the generalized linear model (GLM). We concluded that an appropriate machine learning diagnostic pipeline for endometriosis should use TMM normalization for transcriptomics data, and quantile or voom normalization for methylomics data, GLM for feature space reduction and classification performance maximization.
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Project description:A major concern in common disease epigenomics is distinguishing causal from consequential epigenetic variation. One means of addressing this issue is to identify the temporal origins of epigenetic variants via longitudinal analyses. However, prospective birth-cohort studies are expensive and time-consuming. Here we report DNA methylomics of archived Guthrie cards for the retrospective longitudinal analyses of in utero-derived DNA methylation variation. We first validate two methodologies for generating comprehensive DNA methylomes from Guthrie cards. Then, using an integrated epigenomic/genomic analysis of Guthrie cards and follow-up samplings, we identify inter-individual DNA methylation variation that is present both at birth and three years later. These findings suggest that disease-relevant epigenetic variation could be detected at birth i.e. before overt clinical disease. Guthrie card methylomics offers a potentially powerful and cost-effective strategy for studying the dynamics of inter-individual epigenomic variation in a range of common human diseases. Bisulphite converted DNA was sequenced
2012-08-27 | E-GEOD-38127 | biostudies-arrayexpress
Project description:We experimented how well various supervised machine learning methods such as decision tree, partial least squares discriminant analysis (PLSDA), support vector machine and random forest perform in classifying endometriosis from the control samples trained on both transcriptomics and methylomics data. The assessment was done from two different perspectives for improving classification performances: (a) implication of three different normalization techniques, and (b) implication of differential analysis using the generalized linear model (GLM). We concluded that an appropriate machine learning diagnostic pipeline for endometriosis should use TMM normalization for transcriptomics data, and quantile or voom normalization for methylomics data, GLM for feature space reduction and classification performance maximization.
2019-07-18 | GSE134056 | GEO
Project description:A major concern in common disease epigenomics is distinguishing causal from consequential epigenetic variation. One means of addressing this issue is to identify the temporal origins of epigenetic variants via longitudinal analyses. However, prospective birth-cohort studies are expensive and time-consuming. Here we report DNA methylomics of archived Guthrie cards for the retrospective longitudinal analyses of in utero-derived DNA methylation variation. We first validate two methodologies for generating comprehensive DNA methylomes from Guthrie cards. Then, using an integrated epigenomic/genomic analysis of Guthrie cards and follow-up samplings, we identify inter-individual DNA methylation variation that is present both at birth and three years later. These findings suggest that disease-relevant epigenetic variation could be detected at birth i.e. before overt clinical disease. Guthrie card methylomics offers a potentially powerful and cost-effective strategy for studying the dynamics of inter-individual epigenomic variation in a range of common human diseases. Bisulphite converted DNA was hybridised to the Illumina Infinium 450k Human Methylation Beadchip
2012-08-27 | E-GEOD-37966 | biostudies-arrayexpress
Project description:A major concern in common disease epigenomics is distinguishing causal from consequential epigenetic variation. One means of addressing this issue is to identify the temporal origins of epigenetic variants via longitudinal analyses. However, prospective birth-cohort studies are expensive and time-consuming. Here we report DNA methylomics of archived Guthrie cards for the retrospective longitudinal analyses of in utero-derived DNA methylation variation. We first validate two methodologies for generating comprehensive DNA methylomes from Guthrie cards. Then, using an integrated epigenomic/genomic analysis of Guthrie cards and follow-up samplings, we identify inter-individual DNA methylation variation that is present both at birth and three years later. These findings suggest that disease-relevant epigenetic variation could be detected at birth i.e. before overt clinical disease. Guthrie card methylomics offers a potentially powerful and cost-effective strategy for studying the dynamics of inter-individual epigenomic variation in a range of common human diseases.
2012-08-27 | GSE37966 | GEO
Project description:A major concern in common disease epigenomics is distinguishing causal from consequential epigenetic variation. One means of addressing this issue is to identify the temporal origins of epigenetic variants via longitudinal analyses. However, prospective birth-cohort studies are expensive and time-consuming. Here we report DNA methylomics of archived Guthrie cards for the retrospective longitudinal analyses of in utero-derived DNA methylation variation. We first validate two methodologies for generating comprehensive DNA methylomes from Guthrie cards. Then, using an integrated epigenomic/genomic analysis of Guthrie cards and follow-up samplings, we identify inter-individual DNA methylation variation that is present both at birth and three years later. These findings suggest that disease-relevant epigenetic variation could be detected at birth i.e. before overt clinical disease. Guthrie card methylomics offers a potentially powerful and cost-effective strategy for studying the dynamics of inter-individual epigenomic variation in a range of common human diseases.
2012-08-27 | GSE38127 | GEO