Cargando…

Methylation data imputation performances under different representations and missingness patterns

BACKGROUND: High-throughput technologies enable the cost-effective collection and analysis of DNA methylation data throughout the human genome. This naturally entails missing values management that can complicate the analysis of the data. Several general and specific imputation methods are suitable...

Descripción completa

Detalles Bibliográficos
Autores principales:	Lena, Pietro Di, Sala, Claudia, Prodi, Andrea, Nardini, Christine
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	BioMed Central 2020
Materias:	Research Article
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7325236/ https://www.ncbi.nlm.nih.gov/pubmed/32600298 http://dx.doi.org/10.1186/s12859-020-03592-5

Ejemplares similares

Evaluation of pre-processing on the meta-analysis of DNA methylation data from the Illumina HumanMethylation450 BeadChip platform
por: Sala, Claudia, et al.
Publicado: (2020)

Estimage: a webserver hub for the computation of methylation age
por: Di Lena, Pietro, et al.
Publicado: (2021)

Addressing Missing Data in GC × GC Metabolomics: Identifying Missingness Type and Evaluating the Impact of Imputation Methods on Experimental Replication
por: Davis, Trenton J., et al.
Publicado: (2022)

Editorial: Computational Methods for Analysis of DNA Methylation Data
por: Di Lena, Pietro, et al.
Publicado: (2022)

Reading Profiles in Multi-Site Data With Missingness
por: Eckert, Mark A., et al.
Publicado: (2018)

Ignoring Non-ignorable Missingness
por: Rabe-Hesketh, Sophia, et al.
Publicado: (2022)

Bootstrap calibration of TRANSMIT for informative missingness of parental genotype data
por: Allen, Andrew S, et al.
Publicado: (2003)

Semi-Parametric Methods of Handling Missing Data in Mortal Cohorts under Non-Ignorable Missingness
por: Wen, Lan, et al.
Publicado: (2018)

Much Ado About Missingness: A Demonstration of Full Information Maximum Likelihood Estimation to Address Missingness in Functional Magnetic Resonance Imaging Data
por: Nelson, Timothy D., et al.
Publicado: (2021)

Gender-related data missingness, imbalance and bias in global health surveys
por: Weber, Ann M, et al.
Publicado: (2021)

Missing continuous outcomes under covariate dependent missingness in cluster randomised trials
por: Hossain, Anower, et al.
Publicado: (2016)

On varieties of doubly robust estimators under missingness not at random with a shadow variable
por: Miao, Wang, et al.
Publicado: (2016)

Missing binary outcomes under covariate‐dependent missingness in cluster randomised trials
por: Hossain, Anower, et al.
Publicado: (2017)

The Impact of Nonrandom Missingness in Surveillance Data for Population-Level Summaries: Simulation Study
por: Weiss, Paul Samuel, et al.
Publicado: (2022)

Data Missingness Reporting and Use of Methods to Address It in Critical Care Cohort Studies
por: Wu, Ting Ting, et al.
Publicado: (2023)

High‐dimensional principal component analysis with heterogeneous missingness
por: Zhu, Ziwei, et al.
Publicado: (2022)

Reducing Bias of Allele Frequency Estimates by Modeling SNP Genotype Data with Informative Missingness
por: Lin, Wan-Yu, et al.
Publicado: (2012)

Data missingness in the Michigan NEMSIS (MI-EMSIS) dataset: a mixed-methods study
por: Abir, Mahshid, et al.
Publicado: (2021)

BSImp: Imputing Partially Observed Methylation Patterns for Evaluating Methylation Heterogeneity
por: Chang, Ya-Ting Sabrina, et al.
Publicado: (2022)

A Novel LSTM for Multivariate Time Series with Massive Missingness
por: Fouladgar, Nazanin, et al.
Publicado: (2020)

Informative missingness in electronic health record systems: the curse of knowing
por: Groenwold, Rolf H. H.
Publicado: (2020)

The Impact of Conscientiousness on Participant Drop-Out: A Novel Method for Estimating Missingness
por: Yoneda, Tomiko, et al.
Publicado: (2020)

Missingness in the expanded prostate cancer index short form (EPIC-26) – prevalence, patterns, and explanatory factors
por: Talvitie, Anna-Maija, et al.
Publicado: (2023)

Quartets enable statistically consistent estimation of cell lineage trees under an unbiased error and missingness model
por: Han, Yunheng, et al.
Publicado: (2023)

Using Threshold Regression as an Approach to Incorporate Informative Missingness in Long Life Family Study Data
por: Zhbannikov, Ilya, et al.
Publicado: (2021)

Kernel Sparse Representation with Hybrid Regularization for On-Road Traffic Sensor Data Imputation
por: Chen, Xiaobo, et al.
Publicado: (2018)

The impact of complex informative missingness on the validity of the transmission/disequilibrium test (TDT)
por: Guo, Chao-Yu
Publicado: (2007)

Impact of Hearing Impairment on Missingness of Cognitive Test Scores in the ARIC Study
por: Deal, Jennifer, et al.
Publicado: (2020)

Causal Algebras on Chain Event Graphs with Informed Missingness for System Failure
por: Yu, Xuewen, et al.
Publicado: (2021)

On Missingness Features in Machine Learning Models for Critical Care: Observational Study
por: Singh, Janmajay, et al.
Publicado: (2021)

OptiMissP: A dashboard to assess missingness in proteomic data-independent acquisition mass spectrometry
por: Arioli, Angelica, et al.
Publicado: (2021)

Public health inequalities, structural missingness, and digital revolution: time to question assumptions
por: Naumova, Elena N.
Publicado: (2021)

Imputation Performance in Latin American Populations: Improving Rare Variants Representation With the Inclusion of Native American Genomes
por: Jiménez-Kaufmann, Andrés, et al.
Publicado: (2022)

Estimation methods with ordered exposure subject to measurement error and missingness in semi-ecological design
por: Kim, Hyang-Mi, et al.
Publicado: (2012)

Comparison of methods for handling covariate missingness in propensity score estimation with a binary exposure
por: Coffman, Donna L., et al.
Publicado: (2020)

Importance of missingness in baseline variables: A case study of the All of Us Research Program
por: Cronin, Robert M., et al.
Publicado: (2023)

Imputing missing genotypes: effects of methods and patterns of missing data
por: Ogut, Funda, et al.
Publicado: (2011)

Reuse of imputed data in microarray analysis increases imputation efficiency
por: Kim, Ki-Yeol, et al.
Publicado: (2004)

mbImpute: an accurate and robust imputation method for microbiome data
por: Jiang, Ruochen, et al.
Publicado: (2021)

Multiple Imputation for General Missing Data Patterns in the Presence of High-dimensional Data
por: Deng, Yi, et al.
Publicado: (2016)

Cannot write session to /tmp/vufind_sessions/sess_3vfhjfod0r5qhl5dqcjiouhuru