Methylation analysis of white blood cells DNA samples from healthy males
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE201689 | GEO | 2022/07/07
REPOSITORIES: GEO
Similar Datasets
Project description:We report the higher sensitivity of NGS-based methylation analysis compared to the array-based techniques for the detection of low-frequency, mosaic, monoallelic methylation. This study describes a computational framework for the analysis of methylation sequencing data.
2022-07-07 | GSE201688 | GEO
Project description:The goals of the study were to assess array platform performance and analysis algorithm performance. The most widely used method for detecting genome-wide protein-DNA interactions is chromatin immunoprecipitation on tiling microarrays, commonly known as ChIP-chip. Here, we conducted the first objective analysis of tiling array platforms, amplification procedures, and signal detection algorithms in a simulated ChIP-chip experiment. Mixtures of human genomic DNA and "spike-ins" comprised of nearly 100 human sequences at various concentrations were hybridized to four tiling array platforms by eight independent groups. Blind to the number of spike-ins, their locations, and the range of concentrations, each group made predictions of the spike-in locations. We found that microarray platform choice is not the primary determinant of overall performance. In fact, variation in performance between labs, protocols and algorithms within the same array platform was greater than the variation in performance between array platforms. However, each array platform had unique performance characteristics that varied with tiling resolution and the number of replicates, which have implications for cost versus detection power. Long oligonucleotide arrays were slightly more sensitive at detecting very low enrichment. On all platforms, simple sequence repeats and genome redundancy tended to result in false positives. LM-PCR and WGA, the most popular sample amplification techniques, reproduced relative enrichment levels with high fidelity. Performance among signal detection algorithms was heavily dependent on array platform. The spike-in DNA samples and the data presented here provide a stable benchmark against which future ChIP platforms, protocol improvements, and analysis methods can be evaluated. Keywords: ChIP-chip, competition For data usage terms and conditions, please refer to http://www.genome.gov/27528022 and http://www.genome.gov/Pages/Research/ENCODE/ENCODEDataReleasePolicyFinal2008.pdf
2008-01-09 | GSE10090 | GEO
Project description:The goals of the study were to assess array platform performance and analysis algorithm performance. The most widely used method for detecting genome-wide protein-DNA interactions is chromatin immunoprecipitation on tiling microarrays, commonly known as ChIP-chip. Here, we conducted the first objective analysis of tiling array platforms, amplification procedures, and signal detection algorithms in a simulated ChIP-chip experiment. Mixtures of human genomic DNA and "spike-ins" comprised of nearly 100 human sequences at various concentrations were hybridized to four tiling array platforms by eight independent groups. Blind to the number of spike-ins, their locations, and the range of concentrations, each group made predictions of the spike-in locations. We found that microarray platform choice is not the primary determinant of overall performance. In fact, variation in performance between labs, protocols and algorithms within the same array platform was greater than the variation in performance between array platforms. However, each array platform had unique performance characteristics that varied with tiling resolution and the number of replicates, which have implications for cost versus detection power. Long oligonucleotide arrays were slightly more sensitive at detecting very low enrichment. On all platforms, simple sequence repeats and genome redundancy tended to result in false positives. LM-PCR and WGA, the most popular sample amplification techniques, reproduced relative enrichment levels with high fidelity. Performance among signal detection algorithms was heavily dependent on array platform. The spike-in DNA samples and the data presented here provide a stable benchmark against which future ChIP platforms, protocol improvements, and analysis methods can be evaluated. Keywords: ChIP-chip, competition, artificial DNA For data usage terms and conditions, please refer to http://www.genome.gov/27528022 and http://www.genome.gov/Pages/Research/ENCODE/ENCODEDataReleasePolicyFinal2008.pdf
2008-01-09 | GSE10076 | GEO
Project description:Methylation analysis of white blood cells DNA samples from healthy males
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Project description:The discovery of copy number variation in healthy individuals is far from complete, and due to the resolution of detection systems used, the majority of loci reported so far are relatively large (~65% > 10kb). Applying a two-stage high-resolution array CGH approach to analyse 50 healthy Caucasian males from northern France, we discovered 2208 copy number variants (CNVs) detected by more than one consecutive probe. These clustered into 1469 copy number variant regions (CNVRs), of which 721 are thought to be novel. The majority of these are small (median size 4.4kb) and most have common boundaries, with a coefficient of variation less than 0.1 for 83% of end-points in those observed in multiple samples. Only 6% of the CNVRs analysed showed evidence of both copy number losses and gains at the same site. A further 6089 variants were detected by single probes: 48% of these were observed in more than one individual. In total, 2570 genes were seen to intersect variants: 1284 in novel loci. Genes involved in differentiation and development were significantly overrepresented, and approximately half the genes identified feature in the OMIM database. The biological importance of many of the genes affected, along with the well-conserved nature of the majority of the copy number variants, suggests they could have important implications for phenotype and, thus, be useful for association studies of complex diseases. Keywords: comparative genomic hybridization
2007-08-14 | GSE8691 | GEO
Project description:The goals of the study were to assess array platform performance and analysis algorithm performance. The most widely used method for detecting genome-wide protein-DNA interactions is chromatin immunoprecipitation on tiling microarrays, commonly known as ChIP-chip. Here, we conducted the first objective analysis of tiling array platforms, amplification procedures, and signal detection algorithms in a simulated ChIP-chip experiment. Mixtures of human genomic DNA and "spike-ins" comprised of nearly 100 human sequences at various concentrations were hybridized to four tiling array platforms by eight independent groups. Blind to the number of spike-ins, their locations, and the range of concentrations, each group made predictions of the spike-in locations. We found that microarray platform choice is not the primary determinant of overall performance. In fact, variation in performance between labs, protocols and algorithms within the same array platform was greater than the variation in performance between array platforms. However, each array platform had unique performance characteristics that varied with tiling resolution and the number of replicates, which have implications for cost versus detection power. Long oligonucleotide arrays were slightly more sensitive at detecting very low enrichment. On all platforms, simple sequence repeats and genome redundancy tended to result in false positives. LM-PCR and WGA, the most popular sample amplification techniques, reproduced relative enrichment levels with high fidelity. Performance among signal detection algorithms was heavily dependent on array platform. The spike-in DNA samples and the data presented here provide a stable benchmark against which future ChIP platforms, protocol improvements, and analysis methods can be evaluated. Keywords: ChIP-chip, competition For data usage terms and conditions, please refer to http://www.genome.gov/27528022 and http://www.genome.gov/Pages/Research/ENCODE/ENCODEDataReleasePolicyFinal2008.pdf DNA was spiked-in to a background DNA sample. Same DNA samples used in the arrays in this Series; these are technical array replicates.
2010-05-26 | E-GEOD-10090 | biostudies-arrayexpress
Project description:The goals of the study were to assess array platform performance and analysis algorithm performance. The most widely used method for detecting genome-wide protein-DNA interactions is chromatin immunoprecipitation on tiling microarrays, commonly known as ChIP-chip. Here, we conducted the first objective analysis of tiling array platforms, amplification procedures, and signal detection algorithms in a simulated ChIP-chip experiment. Mixtures of human genomic DNA and "spike-ins" comprised of nearly 100 human sequences at various concentrations were hybridized to four tiling array platforms by eight independent groups. Blind to the number of spike-ins, their locations, and the range of concentrations, each group made predictions of the spike-in locations. We found that microarray platform choice is not the primary determinant of overall performance. In fact, variation in performance between labs, protocols and algorithms within the same array platform was greater than the variation in performance between array platforms. However, each array platform had unique performance characteristics that varied with tiling resolution and the number of replicates, which have implications for cost versus detection power. Long oligonucleotide arrays were slightly more sensitive at detecting very low enrichment. On all platforms, simple sequence repeats and genome redundancy tended to result in false positives. LM-PCR and WGA, the most popular sample amplification techniques, reproduced relative enrichment levels with high fidelity. Performance among signal detection algorithms was heavily dependent on array platform. The spike-in DNA samples and the data presented here provide a stable benchmark against which future ChIP platforms, protocol improvements, and analysis methods can be evaluated. Keywords: ChIP-chip, competition, artificial DNA For data usage terms and conditions, please refer to http://www.genome.gov/27528022 and http://www.genome.gov/Pages/Research/ENCODE/ENCODEDataReleasePolicyFinal2008.pdf DNA samples had spike-in DNA added to simulate peaks in ChIP-chip experiments. Same DNA samples used in the arrays in this Series; these are technical array replicates.
2010-05-26 | E-GEOD-10076 | biostudies-arrayexpress
Project description:MIPP-Seq: Ultra-sensitive rapid detection and validation of low-frequency mosaic mutations
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