metaXCMS statistics

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Citations per year

Number of citations per year for the bioinformatics software tool metaXCMS
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Tool usage distribution map

This map represents all the scientific publications referring to metaXCMS per scientific context
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Associated diseases

This word cloud represents metaXCMS usage per disease context
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Protocols

metaXCMS specifications

Information


Unique identifier OMICS_02635
Name metaXCMS
Software type Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux, Mac OS, Windows
Programming languages R
Computer skills Advanced
Stability No
Maintained No

Versioning


No version available

Publications for metaXCMS

metaXCMS citations

 (6)
library_books

Conserved Responses in a War of Small Molecules between a Plant Pathogenic Bacterium and Fungi

2018
MBio
PMCID: 5964348
DOI: 10.1128/mBio.00820-18

[…] nt’s t test or analysis of variance (ANOVA) followed by Tukey-Kramer analysis to show significant differences. Untargeted metabolomics analyses were performed from four replicates within the XCMS and metaXCMS software packages implemented in the R language (https://github.com/spraker/Spraker_XCMS_analysis_Fusarium). For analyses of known F. fujikuroi metabolites, the MAVEN software package () was […]

call_split

Untargeted plasma and tissue metabolomics in rats with chronic kidney disease given AST 120

2016
Sci Rep
PMCID: 4773761
PMID: 26932318
DOI: 10.1038/srep22526
call_split See protocol

[…] A second order analysis in metaXCMS was used to determine common metabolic differences in plasma, liver, heart and kidney tissue between control and CKD rats. All tissues shared 8 common metabolites, which were significantly in […]

library_books

An evolving computational platform for biological mass spectrometry: workflows, statistics and data mining with MASSyPup64

2015
PeerJ
PMCID: 4655102
PMID: 26618079
DOI: 10.7717/peerj.1401

[…] unequivocal assignment of mass signals to the correct compounds and the estimation of the statistical confidence of metabolite identifications is still challenging.The R packages XCMS/XCMS2 (; ) and metaXCMS (; ) permit the realization of complete metabolic workflows and the comparison of various samples. Correct application of included functions improve the detection, quantification and identifi […]

library_books

A diurnal serum lipid integrates hepatic lipogenesis and peripheral fatty acid utilization

2013
Nature
PMCID: 4141623
PMID: 24153306
DOI: 10.1038/nature12710

[…] es were converted to mzXML files and subsequently aligned by XCMS. The resulting aligned features derived from wt, LPPARDKO, Scramble and LACC1KD serum were compared to identify common features using metaXCMS with a mass tolerance of 0.01 and retention time tolerance of 60 seconds. Identical procedures were carried out to generate common features from adPPARδ and adGFP liver lysates. Subsequently, […]

library_books

Integrated Metabolo Proteomic Approach to Decipher the Mechanisms by Which Wheat QTL (Fhb1) Contributes to Resistance against Fusarium graminearum

2012
PLoS One
PMCID: 3398977
PMID: 22866179
DOI: 10.1371/journal.pone.0040695

[…] RP vs SP). The adducts, isotopes and neutral losses were identified using CAMERA algorithm based on peak annotation . Following this, the data from all four treatment combinations were combined using MetaXCMS , separately for rachis and spikelets. The accurate mass and their abundance (relative intensity) were imported to MS Excel; peaks that were not consistent among replicates and those annotate […]

library_books

Ion annotation assisted analysis of LC MS based metabolomic experiment

2012
Proteome Sci
PMCID: 3380757
PMID: 22759585
DOI: 10.1186/1477-5956-10-S1-S8

[…] In analysis of LC-MS data from multiple experiments, the ions selected from each experiment are compared to determine overlapping ions. For example, the software tool metaXCMS [] performs second-order analysis of untargeted metabolomic data from multiple sample groups representing different models of the same phenotype. The pairs of sample groups are first analyzed […]


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metaXCMS institution(s)
Department of Genetics, Washington University School of Medicine, St Louis, MO, USA

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