Calibration data mammalian array: Human, Mouse, Rat
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PROVIDER: PRJNA730555 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Calibration data EPIC array: Mouse and Rat
| PRJNA730557 | ENA
Project description:An Infinium microarray platform (GPL28271, HorvathMammalMethylChip40) was used to generate DNA methylation data from synthetic DNA from 3 species. The DNA samples from each species were enzymatically manipulated so that they would exhibit 0%, 25%, 50%, 75% and 100% percent methylation at each CpG location, respectively. The variable “ProportionMethylated” (with ordinal values 0, 0.25, 0.5, 0.75, 1) can be interpreted as a benchmark for each CpG that maps to the respective genome. Thus, the DNA methylation levels of each CpG are expected to have a high positive correlation with ProportionMethylated across the arrays measurement from a given species. The mammalian array was applied to synthetic DNA data from 3 species: human (n=10 mammalian arrays, 2 per methylation level), mouse (n=20, 4 per methylation level), and rat (n=15, 3 per methylation level).
2021-08-27 | GSE174567 | GEO
Project description:Illumina Infinium HumanMethylation850 BeadChip (also known as Illumina EPIC array, GPL23976) was used to generate DNA methylation data from synthetic DNA from 3 species. The DNA samples from each species were enzymatically manipulated so that they would exhibit 0%, 25%, 50%, 75% and 100% percent methylation at each CpG location, respectively. The variable “ProportionMethylated” (with ordinal values 0, 0.25, 0.5, 0.75, 1) can be interpreted as a benchmark for each CpG that maps to the respective genome. Thus, the DNA methylation levels of each CpG are expected to have a high positive correlation with ProportionMethylated across the arrays measurement for the human species. The human EPIC array was applied to calibration data from mouse (n=15 EPIC arrays, 3 per methylation level) and rat (n=10, 2 per methylation level). The EPIC array data were normalized using the noob method (R function preprocessNoob in minfi).
2021-08-27 | GSE174568 | GEO
Project description:Calibration array used to assess probe specific binding behaviour across eight different amounts of DNA starting material. This calibration step was performed to select one best out of three probes per gene based on probe responsiveness on increasing DNA staring material. It was further used to calibrate a subsequent microarray experiment to account for probe specific binding behaviour as part of the normalization process (see also Dennenmoser et al. 2017 Copy number increases of transposable elements and protein coding genes in an invasive fish of hybrid origin).
2017-07-01 | GSE93063 | GEO
Project description:Calibration sausages WGS containing mammalian and avian species
| PRJEB34001 | ENA
Project description:Picky is an optimal microarray design software which designed the NSF Rice 45K Array. A series of microarray experiments using a one-chip version of this array were conducted to validate as well as to develop a calibration method for Picky designed microarrays. Synthesized samples with known content were used in the validation. PICKY designed microarrays were found to be highly reliable. The PICKY predicted closest nontarget information was used to quantitatively calibrate the best microarray hybridization conditions using the same microarrays and synthesized samples. Because this method works under most microarray protocols, it is generally applicable in any lab that uses PICKY as their microarray design tool. The associate publication provides more details about the experiment design and discussions about its results. Keywords: Microarray Calibration
2009-10-22 | GSE14717 | GEO
Project description:Picky is an optimal microarray design software which designed the NSF Rice 45K Array. A series of microarray experiments using a one-chip version of this array were conducted to validate as well as to develop a calibration method for Picky designed microarrays. Synthesized samples with known content were used in the validation. PICKY designed microarrays were found to be highly reliable. The PICKY predicted closest nontarget information was used to quantitatively calibrate the best microarray hybridization conditions using the same microarrays and synthesized samples. Because this method works under most microarray protocols, it is generally applicable in any lab that uses PICKY as their microarray design tool. The associate publication provides more details about the experiment design and discussions about its results. Keywords: Microarray Calibration 20 probes on the NSF Rice Oligonucleotide 45K Array grouped into two sets were chosen for microarray calibration. 40 antisense oligonucleotides were synthesized based on the target and closest nontarget gene sequences for each of the chosen probes. 5 different experiments were designed with varied concentrations and dye labeling schemes for the 40 antisense oligos. Two hybridizations were conducted for each experiment at each calibration temperature. 7 sets of experiments were conducted at 70, 60, 55, 53, 50, 48 and 45 degree C using a total of 70 microarrays. Each microarray is scanned at multiple PMT settings to obtain multiple data files. After inspection, weak signal results at 70 degree C and a few contaminated microarray results were discarded. Altogether, 165 valid GenePix GPR files were produced and included in this series.
2010-06-21 | E-GEOD-14717 | biostudies-arrayexpress
Project description:Inter-species array between human, rat and mouse
| PRJNA154071 | ENA
Project description:A custom 8x60 k expression microarray for larvae of European fire salamander (Salamandra salamandra) was designed based on transcriptome sequencing. It is known the fact, that oligonucleotide probes differ in the binding behavior towards their target sequences. Therefore, we performed a calibration of our microarray where we assessed the binding behavior of the individual probes empirically. This information was used to normalize gene expression data measurements with the same microarray in another experiment. Please refer to the accompanying publication (Czypionka et al. 2015." Ecological transcriptomics – a non-lethal sampling approach for endangered fire salamanders" Methods in Ecology and Evolution) for more information. Labeled cRNA was prepared from Salamander larvae kept at 9°C and 17°C. A cRNA calibration pool was prepared with equimolar amounts of cRNA prepared from (a) a larvae (temperature: 9°C: source: pond KOE), (b) a larvae (temperature: 17°C: source: pond KOE), (c) a larvae (temperature: 9°C: source: stream KoGB (Klufterbach) and (d) a larvae (temperature: 17°C: source: stream KoGB (Klufterbach). See Steinfartz et al. (2007) (doi: 10.1111/j.1365-294X.2007.03490.x) for information of the source populations. Increasing amounts of labeled cRNA (75 ng, 150 ng, 300 ng, 600 ng, 1000 ng, 1400 ng, 1800 ng, 2200 ng), corresponding to (1/8, 1/4, 1/2, 1, 1 2/3, 2 1/3, 3 and 3 3/3 times the recommended amount of 600 ng) were hybridized to 8 microarrays (one microarray per dilution). The change in observed signal intensity in relation to the change in amount of labeled cRNA was used to infer the target-binding behavior of the individual probes. This information was extracted, to be used for a normalization procedure in another experiment with the same microarray (see Czypionka et al. 2015." Ecological transcriptomics – a non-lethal sampling approach for endangered fire salamanders" Methods in Ecology and Evolution). The current study provides only raw data for a calibration experiment, to validate the binding behavior of the different probes on a newly designed microarray for a non model organism (European Fire salamander). This calibration is based only on raw data. More information on targeted genes is provided in a different GEO dataset (currently submitted), where biological meaningful analysis are performed with data which are normalized based on this calibration.
2015-06-20 | E-GEOD-70055 | biostudies-arrayexpress