Results 11 to 20 of about 1,318,109 (301)

DISTMIX: direct imputation of summary statistics for unmeasured SNPs from mixed ethnicity cohorts [PDF]

Bioinform., 2015
Motivation: To increase the signal resolution for large-scale meta-analyses of genome-wide association studies, genotypes at unmeasured single nucleotide polymorphisms (SNPs) are commonly imputed using large multi-ethnic reference panels.
Donghyung Lee, T. Bigdeli, Vernell S. Williamson, Vladimir I. Vladimirov, Vladimir I. Vladimirov, B. Riley, A. Fanous, S. Bacanu   +7 more
semanticscholar   +2 more sources

GAUSS: a summary-statistics-based R package for accurate estimation of linkage disequilibrium for variants, Gaussian imputation, and TWAS analysis of cosmopolitan cohorts

Bioinformatics
Motivation As the availability of larger and more ethnically diverse reference panels grows, there is an increase in demand for ancestry-informed imputation of genome-wide association studies (GWAS), and other downstream analyses, e.g.
Donghyung Lee, S. Bacanu
semanticscholar   +2 more sources

xQTLImp: efficient and accurate xQTL summary statistics imputation [PDF]

, 2019
AbstractMotivationQuantitative trait locus (QTL) analysis of multiomic molecular traits, such as gene transcription (eQTL), DNA methylation (mQTL) and histone modification (haQTL), has been widely used to infer the effects of genomic variation on multiple levels of molecular activities.
Tao Wang, Quanwei Yin, Yongzhuang Liu, Ming‐Huei Chen, Yadong Wang, Jiajie Peng   +5 more
openalex   +2 more sources

Missing data imputation and corrected statistics for large-scale behavioral databases [PDF]

Behavior Research Methods, 2011
This paper presents a new methodology to solve problems resulting from missing data in large-scale item performance behavioral databases. Useful statistics corrected for missing data are described, and a new method of imputation for missing data is proposed. This methodology is applied to the DLP database recently published by Keuleers et al.
Pierre Courrieu, Arnaud Rey
openalex   +6 more sources

Comparing Multiple Imputation Methods to Address Missing Patient Demographics in Immunization Information Systems: Retrospective Cohort Study

JMIR Public Health and Surveillance
BackgroundImmunization Information Systems (IIS) and surveillance data are essential for public health interventions and programming; however, missing data are often a challenge, potentially introducing bias and impacting the accuracy of vaccine coverage
Sara Brown, Ousswa Kudia, Kaye Kleine, Bryndan Kidd, Robert Wines, Nathanael Meckes   +5 more
doaj   +2 more sources

ImputeGAN: Generative Adversarial Network for Multivariate Time Series Imputation

Entropy, 2023
Since missing values in multivariate time series data are inevitable, many researchers have come up with methods to deal with the missing data. These include case deletion methods, statistics-based imputation methods, and machine learning-based ...
Rui Qin, Yong Wang
doaj   +2 more sources

DIST: direct imputation of summary statistics for unmeasured SNPs [PDF]

Bioinformatics, 2013
Abstract Motivation: Genotype imputation methods are used to enhance the resolution of genome-wide association studies, and thus increase the detection rate for genetic signals. Although most studies report all univariate summary statistics, many of them limit the access to subject-level genotypes.
Donghyung Lee, Tim B. Bigdeli, Brien P. Riley, Ayman H. Fanous, Silviu‐Alin Bacanu   +4 more
openalex   +4 more sources

Fast and accurate imputation of summary statistics enhances evidence of functional enrichment [PDF]

Bioinform., 2013
MOTIVATION Imputation using external reference panels (e.g. 1000 Genomes) is a widely used approach for increasing power in genome-wide association studies and meta-analysis.
B. Pasaniuc, N. Zaitlen, Huwenbo Shi, G. Bhatia, A. Gusev, Joseph K. Pickrell, J. Hirschhorn, D. Strachan, N. Patterson, A. Price   +9 more
semanticscholar   +3 more sources

Methods for Addressing Missingness in Electronic Health Record Data for Clinical Prediction Models: Comparative Evaluation

JMIR Medical Informatics
BackgroundMissing data are a common challenge in electronic health record (EHR)–based prediction modeling. Traditional imputation methods may not suit prediction or machine learning models, and real-world use requires workflows that are implementable for
Jean Digitale, Deborah Franzon, Mark J Pletcher, Charles E McCulloch, Efstathios D Gennatas   +4 more
doaj   +2 more sources

Imputation of Municipal Statistics Data

Vestnik NSUEM, 2020
Tatyana Skripkina
openalex   +3 more sources