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GSimp: A Gibbs sampler based left-censored missing value imputation approach for metabolomics studies [article]

Runmin Wei, Jingye Wang, Erik Jia, Tianlu Chen, Yan Ni, Wei Jia
2017 bioRxiv   pre-print
Thus, a practical left-censored missing value imputation method is urgently needed. We have developed an iterative Gibbs sampler based left-censored missing value imputation approach (GSimp).  ...  Left-censored missing values commonly exist in targeted metabolomics datasets and can be considered as missing not at random (MNAR).  ...  Again, GSimp performs best with the highest correlations among four The purpose of this study is to develop a left-censored missing value imputation approach for targeted metabolomics data analysis  ... 
doi:10.1101/177410 fatcat:yorrdb3o35cezl243wbfxpnbii

GSimp: A Gibbs sampler based left-censored missing value imputation approach for metabolomics studies

Runmin Wei, Jingye Wang, Erik Jia, Tianlu Chen, Yan Ni, Wei Jia, Jens Nielsen
2018 PLoS Computational Biology  
Thus, a practical left-censored missing value imputation method is urgently needed. We developed an iterative Gibbs sampler based left-censored missing value imputation approach (GSimp).  ...  The R code for GSimp, evaluation pipeline, tutorial, real-world and simulated targeted metabolomics datasets are available at: (2018) GSimp: A Gibbs sampler based leftcensored missing value imputation  ...  Peng) for their endless love and support. They are also grateful to Mr. Link who is always curious about the unexplored land.  ... 
doi:10.1371/journal.pcbi.1005973 pmid:29385130 pmcid:PMC5809088 fatcat:4pr66p7yafbobnm44rnko7cidm

BayesMetab: treatment of missing values in metabolomic studies using a Bayesian modeling approach

Jasmit Shah, Guy N. Brock, Jeremy Gaskins
2019 BMC Bioinformatics  
other imputation algorithms when there is a mixture of missingness due to MAR and MNAR.  ...  We develop a Bayesian model, called BayesMetab, that systematically accounts for missing values based on a Markov chain Monte Carlo (MCMC) algorithm that incorporates data augmentation by allowing MVs  ...  [15] and is a MV imputation method based on left-censored (MNAR) using an iterative Gibbs sampler approach which allows flexible choice of the threshold/truncation value.  ... 
doi:10.1186/s12859-019-3250-2 pmid:31861984 pmcid:PMC6923847 fatcat:thc4ibnsgjgbnm7mobxsomdbcy

Missing value imputation in proximity extension assay-based targeted proteomics data

Michael Lenz, Andreas Schulz, Thomas Koeck, Steffen Rapp, Markus Nagler, Madeleine Sauer, Lisa Eggebrecht, Vincent Ten Cate, Marina Panova-Noeva, Jürgen H. Prochaska, Karl J. Lackner, Thomas Münzel (+4 others)
2020 PLoS ONE  
Multivariate analysis of this data is hampered by frequent missing values (random or left censored), calling for imputation approaches.  ...  Here, we assessed the performance of two methods for imputation of values missing completely at random, the previously top-benchmarked 'missForest' and the recently published 'GSimp' method.  ...  Dorsch (Bayer AG) for project management.  ... 
doi:10.1371/journal.pone.0243487 pmid:33315883 fatcat:tf3h5nplc5d2rdrzyombz7rcrq

Kernel weighted least square approach for imputing missing values of metabolomics data

Nishith Kumar, Md. Aminul Hoque, Masahiro Sugimoto
2021 Scientific Reports  
We developed a new kernel weight function-based proposed missing data imputation technique that resolves the problems of missing values and outliers.  ...  For user convenience, an R package of the proposed kernel weight-based missing value imputation technique was developed, which is available at https://github.com/NishithPaul/tWLSA.  ...  We would like to thank Editage (www. edita ge. com) for English language editing.  ... 
doi:10.1038/s41598-021-90654-0 pmid:34045614 fatcat:zceujfog2ngjpdpcnazkqefhum

Bioinformatics Methods for Mass Spectrometry-Based Proteomics Data Analysis

Chen Chen, Jie Hou, John J Tanner, Jianlin Cheng
2020 International Journal of Molecular Sciences  
We first introduce bioinformatics software and tools designed for mass spectrometry-based protein identification and quantification, and then we review the different statistical and machine learning methods  ...  that have been developed to perform comprehensive analysis in proteomics studies.  ...  GSimp [123] A Gibbs sampler-based left-censored missing value imputation approach for metabolomics studies.  ... 
doi:10.3390/ijms21082873 pmid:32326049 pmcid:PMC7216093 fatcat:5zbrkah4xvec3mq3ypal7cxfbu

Altered profiles of fecal metabolites correlate with visceral hypersensitivity and may contribute to symptom severity of diarrhea-predominant irritable bowel syndrome

Wen-Xue Zhang, Yu Zhang, Geng Qin, Kai-Min Li, Wei Wei, Su-Yun Li, Shu-Kun Yao
2019 World Journal of Gastroenterology  
Fecal metabolites, including amino acids and organic acids, were measured by targeted metabolomics approaches. Correlation analyses between these parameters were performed.  ...  A possible potential biomarker panel was identified to correlate with IBS-SSS score (R 2 Adjusted = 0.693, P < 0.001).  ...  Du SY for enrollment of participants.  ... 
doi:10.3748/wjg.v25.i43.6416 pmid:31798278 pmcid:PMC6881512 fatcat:oaxtyff25ndzzjwyf636fpg35e

Innate lymphoid cell composition associates with COVID-19 disease severity [article]

Marina Garcia, Efthymia Kokkinou, Anna Carrasco Garcia, Tiphaine Parrot, Laura M. Palma Medina, Kimia T. Maleki, Wanda Christ, Renata Varnaite, Iva Filipovic, Hans-Gustaf Ljunggren, Niklas K. Bjorkstrom, Elin Folkesson (+9 others)
2020 medRxiv   pre-print
Using supervised and unsupervised approaches, we examined the ILC activation status and homing profile.  ...  Conclusion: This study provides insights into the potential role of ILCs in immune responses against SARS-CoV-2, particularly linked to the severity of COVID-19.  ...  GSimp: A Gibbs sampler based left-642 censored missing value imputation approach for metabolomics studies. PLoS 643 Comput Biol 2018; 14(1). doi:10.1371/journal.pcbi.1005973 644 28. R Core Team.  ... 
doi:10.1101/2020.10.13.20211367 fatcat:ny3gzs4nxzh3llggdtl7tjhwmu