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HipSci HumanHT 12 Expression BeadChip analysis - Hereditary Cerebellar Ataxias

ABSTRACT: The HipSci project brings together diverse constituents in genomics, proteomics, cell biology and clinical genetics to create a UK national iPS cell resource and use it to carry out cellular genetic studies. In this sub-study we performed Expression analysis using the Illumina HumanHT -12 Expression BeadChip on iPS cells generated from skin biopsies or blood samples from rare disease patients diagnosed with Hereditary Cerebellar Ataxias.

PROVIDER: EGAS00001002020 | EGA |

REPOSITORIES: EGA

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Project description:The Human Induced Pluripotent Stem Cells Initiative (HipSci) project brings together diverse constituents in genomics, proteomics, cell biology and clinical genetics to create a UK national induced pluripotent stem cell (iPS cell) resource and use it to carry out cellular genetic studies. In this sub-study we performed Expression analysis using the Illumina HumanHT -12 Expression BeadChip on fibroblasts and iPS cells generated from skin biopsies from healthy volunteers.

2015-11-16 | E-MTAB-4057 | biostudies-arrayexpress

REL-2017-07-2020

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Comparison of normalization methods for Illumina BeadChip HumanHT-12 v3.

Project description:BACKGROUND: Normalization of microarrays is a standard practice to account for and minimize effects which are not due to the controlled factors in an experiment. There is an overwhelming number of different methods that can be applied, none of which is ideally suited for all experimental designs. Thus, it is important to identify a normalization method appropriate for the experimental setup under consideration that is neither too negligent nor too stringent. Major aim is to derive optimal results from the underlying experiment. Comparisons of different normalization methods have already been conducted, none of which, to our knowledge, comparing more than a handful of methods. RESULTS: In the present study, 25 different ways of pre-processing Illumina Sentrix BeadChip array data are compared. Among others, methods provided by the BeadStudio software are taken into account. Looking at different statistical measures, we point out the ideal versus the actual observations. Additionally, we compare qRT-PCR measurements of transcripts from different ranges of expression intensities to the respective normalized values of the microarray data. Taking together all different kinds of measures, the ideal method for our dataset is identified. CONCLUSIONS: Pre-processing of microarray gene expression experiments has been shown to influence further downstream analysis to a great extent and thus has to be carefully chosen based on the design of the experiment. This study provides a recommendation for deciding which normalization method is best suited for a particular experimental setup.

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2022-12-31 | GSE102154 | GEO

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