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LIBRIS Formathandbok  (Information om MARC21)
FältnamnIndikatorerMetadata
00004807naa a2200625 4500
001oai:DiVA.org:umu-146374
003SwePub
008180406s2018 | |||||||||||000 ||eng|
0247 a https://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-1463742 URI
0247 a https://doi.org/10.1186/s13148-018-0471-62 DOI
040 a (SwePub)umu
041 a engb eng
042 9 SwePub
072 7a ref2 swepub-contenttype
072 7a art2 swepub-publicationtype
1001 a Perrier, Flavie4 aut
2451 0a Identifying and correcting epigenetics measurements for systematic sources of variation
264 c 2018-03-21
264 1a London :b BioMed Central,c 2018
338 a electronic2 rdacarrier
520 a Background: Methylation measures quantified by microarray techniques can be affected by systematic variation due to the technical processing of samples, which may compromise the accuracy of the measurement process and contribute to bias the estimate of the association under investigation. The quantification of the contribution of the systematic source of variation is challenging in datasets characterized by hundreds of thousands of features.In this study, we introduce a method previously developed for the analysis of metabolomics data to evaluate the performance of existing normalizing techniques to correct for unwanted variation. Illumina Infinium HumanMethylation450K was used to acquire methylation levels in over 421,000 CpG sites for 902 study participants of a case-control study on breast cancer nested within the EPIC cohort. The principal component partial R-square (PC-PR2) analysis was used to identify and quantify the variability attributable to potential systematic sources of variation. Three correcting techniques, namely ComBat, surrogate variables analysis (SVA) and a linear regression model to compute residuals were applied. The impact of each correcting method on the association between smoking status and DNA methylation levels was evaluated, and results were compared with findings from a large meta-analysis.Results:  A sizeable proportion of systematic variability due to variables expressing 'batch' and 'sample position' within 'chip' was identified, with values of the partial R-2 statistics equal to 9.5 and 11.4% of total variation, respectively. After application of ComBat or the residuals' methods, the contribution was 1.3 and 0.2%, respectively. The SVA technique resulted in a reduced variability due to 'batch' (1.3%) and 'sample position' (0.6%), and in a diminished variability attributable to 'chip' within a batch (0.9%). After ComBat or the residuals' corrections, a larger number of significant sites (k = 600 and k = 427, respectively) were associated to smoking status than the SVA correction (k = 96).Conclusions: The three correction methods removed systematic variation in DNA methylation data, as assessed by the PC-PR2, which lent itself as a useful tool to explore variability in large dimension data. SVA produced more conservative findings than ComBat in the association between smoking and DNA methylation.
650 7a MEDICIN OCH HÄLSOVETENSKAPx Klinisk medicinx Cancer och onkologi0 (SwePub)302032 hsv//swe
650 7a MEDICAL AND HEALTH SCIENCESx Clinical Medicinex Cancer and Oncology0 (SwePub)302032 hsv//eng
653 a Epigenetics
653 a Methylation
653 a Normalization
653 a PC-PR2
653 a Smoking status
7001 a Novoloaca, Alexei4 aut
7001 a Ambatipudi, Srikant4 aut
7001 a Baglietto, Laura4 aut
7001 a Ghantous, Akram4 aut
7001 a Perduca, Vittorio4 aut
7001 a Barrdahl, Myrto4 aut
7001 a Harlid, Sophiau Umeå universitet,Onkologi4 aut0 (Swepub:umu)soha0105
7001 a Ong, Ken K.4 aut
7001 a Cardona, Alexia4 aut
7001 a Polidoro, Silvia4 aut
7001 a Haugdahl Nøst, Therese4 aut
7001 a Overvad, Kim4 aut
7001 a Omichessan, Hanane4 aut
7001 a Dollé, Martijn4 aut
7001 a Bamia, Christina4 aut
7001 a Huerta, José Marìa4 aut
7001 a Vineis, Paolo4 aut
7001 a Herceg, Zdenko4 aut
7001 a Romieu, Isabelle4 aut
7001 a Ferrari, Pietro4 aut
7102 a Umeå universitetb Onkologi4 org
7730 t Clinical Epigeneticsd London : BioMed Centralg 10q 10x 1868-7083x 1868-7075
8564 u https://doi.org/10.1186/s13148-018-0471-6y Fulltext
8564 u https://umu.diva-portal.org/smash/get/diva2:1195766/FULLTEXT01.pdfx primaryx Raw objecty fulltext:print
8564 u https://clinicalepigeneticsjournal.biomedcentral.com/track/pdf/10.1186/s13148-018-0471-6
8564 8u https://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-146374
8564 8u https://doi.org/10.1186/s13148-018-0471-6

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