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Quality control measures for placental sample purity in DNA methylation array analyses.

ABSTRACT: The purity of tissue samples can affect the accuracy and utility of DNA methylation array analyses. This is particularly important for the placenta which is globally hypomethylated compared to other tissues. Placental villous tissue from early pregnancy terminations can be difficult to separate from non-villous tissue, resulting in potentially inaccurate results. We used several methods to identify mixed placenta samples using DNA methylation array datasets from our laboratory and those contained in the NCBI GEO database, highlighting the importance of determining sample purity during quality control processes.

SUBMITTER: Wan Q

PROVIDER: S-EPMC7705927 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature

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Quality control measures for placental sample purity in DNA methylation array analyses.

Wan Qianhui Q Yiner-Lee Leemaqz Shalem S Pederson Stephen Martin SM McCullough Dylan D McAninch Dale Christopher DC Jankovic-Karasoulos Tanja T Smith Melanie Denise MD Bogias Konstantinos Justinian KJ Liu Ning N Breen James J Roberts Claire Trelford CT Bianco-Miotto Tina T

Placenta 20190917

The purity of tissue samples can affect the accuracy and utility of DNA methylation array analyses. This is particularly important for the placenta which is globally hypomethylated compared to other tissues. Placental villous tissue from early pregnancy terminations can be difficult to separate from non-villous tissue, resulting in potentially inaccurate results. We used several methods to identify mixed placenta samples using DNA methylation array datasets from our laboratory and those containe ...[more]

PMID: 31569011

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Quality control measures for placental sample purity in DNA methylation array analyses

Project description:The purity of tissue samples can affect the accuracy and utility of DNA methylation array analyses. This is particularly important for the placenta which is hypomethylated. Placental villous tissue from early pregnancy terminations can be difficult to separate from the non-villous tissue, resulting in potentially inaccurate results. We used several methods to identify mixed placental samples using DNA methylation array datasets from our laboratory and those contained in the NCBI GEO database, highlighting the importance of determining sample purity during quality control processes.

2020-06-09 | GSE131945 | GEO

Quality control measures for placental sample purity in DNA methylation array analyses

Project description:Quality control measures for placental sample purity in DNA methylation array analyses

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Different measures of "genome-wide" DNA methylation exhibit unique properties in placental and somatic tissues.

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Tumor purity quantification by clonal DNA methylation signatures.

Project description:Motivation:Controlling for tumor purity in molecular analyses is essential to allow for reliable genomic aberration calls, for inter-sample comparison and to monitor heterogeneity of cancer cell populations. In genome wide screening studies, the assessment of tumor purity is typically performed by means of computational methods that exploit somatic copy number aberrations. Results:We present a strategy, called Purity Assessment from clonal MEthylation Sites (PAMES), which uses the methylation level of a few dozen, highly clonal, tumor type specific CpG sites to estimate the purity of tumor samples, without the need of a matched benign control. We trained and validated our method in more than 6000 samples from different datasets. Purity estimates by PAMES were highly concordant with other state-of-the-art tools and its evaluation in a cancer cell line dataset highlights its reliability to accurately estimate tumor admixtures. We extended the capability of PAMES to the analysis of CpG islands instead of the more platform-specific CpG sites and demonstrated its accuracy in a set of advanced tumors profiled by high throughput DNA methylation sequencing. These analyses show that PAMES is a valuable tool to assess the purity of tumor samples in the settings of clinical research and diagnostics. Availability and implementation:https://github.com/cgplab/PAMES. Contact:matteo.benelli@uslcentro.toscana.it or f.demichelis@unitn.it. Supplementary information:Supplementary data are available at Bioinformatics online.

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Copy number variation has little impact on bead-array-based measures of DNA methylation.

Project description:Integration of various genome-scale measures of molecular alterations is of great interest to researchers aiming to better define disease processes or identify novel targets with clinical utility. Particularly important in cancer are measures of gene copy number DNA methylation. However, copy number variation may bias the measurement of DNA methylation. To investigate possible bias, we analyzed integrated data obtained from 19 head and neck squamous cell carcinoma (HNSCC) tumors and 23 mesothelioma tumors.Statistical analysis of observational data produced results consistent with those anticipated from theoretical mathematical properties. Average beta value reported by Illumina GoldenGate (a bead-array platform) was significantly smaller than a similar measure constructed from the ratio of average dye intensities. Among CpGs that had only small variations in measured methylation across tumors (filtering out clearly biological methylation signatures), there were no systematic copy number effects on methylation for three and more than four copies; however, one copy led to small systematic negative effects, and no copies led to substantial significant negative effects.Since mathematical considerations suggest little bias in methylation assayed using bead-arrays, the consistency of observational data with anticipated properties suggests little bias. However, further analysis of systematic copy number effects across CpGs suggest that though there may be little bias when there are copy number gains, small biases may result when one allele is lost, and substantial biases when both alleles are lost. These results suggest that further integration of these measures can be useful for characterizing the biological relationships between these somatic events.

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Multilayer microfluidic array for highly efficient sample loading and digital melt analysis of DNA methylation.

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SAQC: SNP array quality control.

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2023-04-21 | GSE230132 | GEO

Placental epigenetic clocks: estimating gestational age using placental DNA methylation levels.

Project description:The human pan-tissue epigenetic clock is widely used for estimating age across the entire lifespan, but it does not lend itself well to estimating gestational age (GA) based on placental DNAm methylation (DNAm) data. We replicate previous findings demonstrating a strong correlation between GA and genome-wide DNAm changes. Using substantially more DNAm arrays (n=1,102 in the training set) than a previous study, we present three new placental epigenetic clocks: 1) a robust placental clock (RPC) which is unaffected by common pregnancy complications (e.g., gestational diabetes, preeclampsia), and 2) a control placental clock (CPC) constructed using placental samples from pregnancies without known placental pathology, and 3) a refined RPC for uncomplicated term pregnancies. These placental clocks are highly accurate estimators of GA based on placental tissue; e.g., predicted GA based on RPC is highly correlated with actual GA (r>0.95 in test data, median error less than one week). We show that epigenetic clocks derived from cord blood or other tissues do not accurately estimate GA in placental samples. While fundamentally different from Horvath's pan-tissue epigenetic clock, placental clocks closely track fetal age during development and may have interesting applications.

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