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008			220503s2022 xxua o |||| 0|eng d
020			_a9781071619940
024	7		_a10.1007/978-1-0716-1994-0 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aQP624.5 .M46 _b2022 EB
245	0	0	_aEpigenome-Wide Association Studies : _bMethods and Protocols _cedited by Weihua Guan
250			_a1st edition 2022
264		1	_aNew York, NY _bSpringer International Publising _c2022
300			_a1 recurso en línea (X, 229 páginas) _b63 ilustraciones, 45 ilustraciones a color
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_aarchivo de texto _bPDF
490	0		_aMethods in Molecular Biology _x1940-6029 _v2432
505	0		_aQuantification Methods for Methylation Levels in Illumina Arrays -- Evaluating Reliability of DNA Methylation Measurement -- Accurate measurement of DNA methylation: Challenges and Bias Correction. Using R for Cell-Type Composition Imputation in Epigenome-Wide Association Studies -- Cell Type-Specific Signal Analysis in Epigenome-Wide Association Studies -- Controlling Batch Effect in Epigenome-Wide Association Study -- DNA methylation and Atopic Diseases -- Meta-analysis for Epigenome-Wide Association Studies -- Increase the Power of Epigenome-Wide Association Testing Using ICC-Based Hypothesis Weighting -- A Review of High-dimensional Mediation Analyses in DNA Methylation Studies -- DNA Methylation Imputation across Platforms -- Workflow to mine frequent DNA Co-Methylation Clusters in DNA Methylome Data -- BCurve: Bayesian Curve Credible Bands Approach for Detection of Differentially Methylated Regions -- Predicting chronological age from DNA methylation data: A machine learning approach for small datasets and limited predictors -- Application of Correlation Pre-Filtering Neural Network to DNA Methylation Data: Biological Aging Prediction -- Differential Methylation Analysis for Bisulfite Sequencing (BS-seq) Data.
520			_aThis volume details features of DNA methylation data, data processing pipelines, quality control measures, data normalization, and to discussions of statistical methods for data analysis, control of confounding and batch effects, and identification of differentially methylated regions. Chapters focus on microarray-based methylation measures and sequence-based measures. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary methodologies and software packages, step-by-step, readily reproducible analysis pipelines, and tips on troubleshooting and avoiding known pitfalls. Authoritative and cutting-edge, Epigenome- Wide Association Studies: Methods and Protocols: aims to be a useful practical guide to researches to help further their study in this field. .
988			_aSpringer_Protocols_2022
650		7	_2embne _9670608 _aADN mitocondrial
776	0	8	_iPrinted edition: _z9781071619933
776	0	8	_iPrinted edition: _z9781071619957
776	0	8	_iPrinted edition: _z9781071619964
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-1-0716-1994-0 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b07/2023 _dz _eb _zSI