Search results for "Batch effect"

showing 2 items of 2 documents

Factors that influence the quality of metabolomics data in in vitro cell toxicity studies: a systematic survey

2021

Abstract REACH (Registration, Evaluation, Authorization and Restriction of Chemicals) is a global strategy and regulation policy of the EU that aims to improve the protection of human health and the environment through the better and earlier identification of the intrinsic properties of chemical substances. It entered into force on 1st June 2007 (EC 1907/2006). REACH and EU policies plead for the use of robust high-throughput "omic" techniques for the in vitro investigation of the toxicity of chemicals that can provide an estimation of their hazards as well as information regarding the underlying mechanisms of toxicity. In agreement with the 3R’s principles, cultured cells are nowadays wide…

Quality ControlHEPATOTOXICITYSciencemedia_common.quotation_subjectDiseasesComputational biologyMETABOLISMBiologyHEPATOCYTESCitric AcidArticleXenobioticsProductes químicschemistry.chemical_compoundMetabolomicsMedical researchCell Line TumorMetabolomeHumansMetabolomicsSPECTROMETRY DATAQuality (business)HEPARG CELLSAcetaminophenmedia_commonBATCH EFFECT CORRECTIONMultidisciplinaryFATTY-ACIDDrug discoveryValproic AcidQRReproducibility of ResultsHep G2 CellsIn vitroBioactive compoundGLUTAMINEMetabolic pathwayLiverchemistryToxicityMetabolomeMedicineCURRENT STATEChemical and Drug Induced Liver InjuryXenobioticMetabolic Networks and PathwaysBiomarkersVALPROATEScientific Reports
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Detection of batch effects in liquid chromatography-mass spectrometry metabolomic data using guided principal component analysis.

2014

Metabolomics based on liquid chromatography-mass spectrometry (LC-MS) is a powerful tool for studying dynamic responses of biological systems to different physiological or pathological conditions. Differences in the instrumental response within and between batches introduce unwanted and uncontrolled data variation that should be removed to extract useful information. This work exploits a recently developed method for the identification of batch effects in high throughput genomic data based on the calculation of a delta statistic through principal component analysis (PCA) and guided PCA. Its applicability to LC-MS metabolomic data was tested on two real examples. The first example involved t…

Quality ControlPrincipal Component AnalysisChromatographyChemistryGenomic dataGuided principal component analysisMass spectrometryBatch effectMass SpectrometryAnalytical ChemistryData setPlasmaMetabolomicsLiquid chromatography–mass spectrometryPeak intensityPrincipal component analysisCalibrationLiquid chromatography-mass spectrometry (LC-MS)HumansMetabolomicsBiological systemStatisticChromatography LiquidTalanta
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