EigenMS protocols

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EigenMS specifications

Information


Unique identifier OMICS_14858
Name EigenMS
Software type Application/Script
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux, Mac OS, Windows
Programming languages MATLAB, R
License GNU General Public License version 2.0
Computer skills Advanced
Stability Stable
Maintained Yes

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  • person_outline Yuliya Karpievitch <>

Publication for EigenMS

EigenMS in pipelines

 (3)
2017
PMCID: 5553085
PMID: 28868138
DOI: 10.5256/f1000research.12777.r23714

[…] study ., dataset 1: pre-processed raw data and the data further processed with the data normalisation methods used in this study are available in excel files: raw is the unadjusted data; crmn.norm, eigenms.norm, pqn.norm, svr.norm, lowess.norm are the data further processed with the corresponding normalisation methods; injection sequence describes the injection order of the gc-ms experiment. […]

2017
PMCID: 5553085
PMID: 28868138
DOI: 10.5256/f1000research.12777.r23714

[…] system) (version 2.72), and the accuracy of data extraction of these software tools was compared. data was further processed and analysed with five different normalisation methods (crmn, eigenms, pqn, svr and lowess). the performance of the normalisation methods and the marker candidates identified were investigated. pca was performed with ezinfo (version 3.0.3). multilevel pca […]

2016
PMCID: 4992866
PMID: 27545962
DOI: 10.1038/srep31697

[…] converted to mzxml format with massmatrix mm file conversion tool and quantification was done in protmax by summing parent ion intensities. the quantified phosphopeptides were log10 transformed, eigenms normalized and missing values were imputed using k-nearest neighbour (knn) method., the data from experiment 2 were analysed with maxquant 1.4 and andromeda search algorithm. mass tolerance […]


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EigenMS in publications

 (8)
PMCID: 5553085
PMID: 28868138
DOI: 10.5256/f1000research.12777.r23714

[…] system) (version 2.72), and the accuracy of data extraction of these software tools was compared. data was further processed and analysed with five different normalisation methods (crmn, eigenms, pqn, svr and lowess). the performance of the normalisation methods and the marker candidates identified were investigated. pca was performed with ezinfo (version 3.0.3). multilevel pca […]

PMCID: 5499862
PMID: 28520864
DOI: 10.1093/gigascience/gix037

[…] peak intensity drift effects based on variance analysis, metnormalizer [] allows for normalization and integration of multiple batches in large-scale experiments using support vector regression, and eigenms [] detects biased trends in the data and eliminates them using single-value decomposition. all of these software packages are highly useful and are implemented in r; however, […]

PMCID: 5290663
PMID: 28153035
DOI: 10.1186/s12859-017-1501-7

[…] []. combat requires complete data, therefore missing values are imputed using bayesian principle components (pc) analysis with half-minimum value substitutions for negative imputed values []., eigenms first requires estimation of a categorical ‘treatment’ effect via anova. singular value decomposition is then applied to the matrix of residuals and additional bias trends are removed […]

PMCID: 4992866
PMID: 27545962
DOI: 10.1038/srep31697

[…] converted to mzxml format with massmatrix mm file conversion tool and quantification was done in protmax by summing parent ion intensities. the quantified phosphopeptides were log10 transformed, eigenms normalized and missing values were imputed using k-nearest neighbour (knn) method., the data from experiment 2 were analysed with maxquant 1.4 and andromeda search algorithm. mass tolerance […]

PMCID: 4280143
PMID: 25549083
DOI: 10.1371/journal.pone.0116221

[…] of the lc column performance, accumulation of contaminants in the ms ion source and ms sensitivity among others. in this study we aimed to test a singular value decomposition-based method, called eigenms, for normalization of metabolomics data. we analyzed a clinical human dataset where lc-ms serum metabolomics data and physiological measurements were collected from thirty nine healthy […]


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EigenMS institution(s)
Department of Statistics, TAMU, College Station, TX, USA; Pacific Northwest National Laboratory, Richland, WA, USA
EigenMS funding source(s)
Supported by NIH R25-CA-90301 training grant in biostatistics and bioinformatics at TAMU; the National Institute of Allergy and Infectious Diseases NIH/DHHS through interagency agreement Y1- AI-4894-01; National Center for Research Resources (NCRR grant no. RR 18522); PNNL is operated for the DOE Battelle Memorial Institute (contract DE-AC05-76RLO01830).

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