qpgraph protocols

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qpgraph statistics

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qpgraph specifications

Information


Unique identifier OMICS_14610
Name qpgraph
Software type Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux, Mac OS, Windows
Programming languages R
License GNU General Public License version 3.0, GNU General Public License version 2.0
Computer skills Advanced
Version 2.14.0
Stability Stable
Requirements
AnnotationDbi, methods, parallel, grid, BiocGenerics, Biobase, IRanges, GenomicRanges, snow, S4Vectors, GenomeInfoDb, BiocStyle, BiocParallel, RUnit, GenomicFeatures, genefilter, mvtnorm, annotate, GOstats, Category, Rgraphviz, R(>=3.4), qtl, Matrix(>=1.0), graph(>=1.45.1), org.EcK12.eg.db, rlecuyer
Maintained Yes

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Maintainer


  • person_outline Robert Castelo <>

Publications for qpgraph

qpgraph in pipelines

 (2)
2017
PMCID: 5560814
PMID: 28642272
DOI: 10.1534/genetics.117.202531

[…] genes associated with at least one genotype marker (with p-value <0.0001) were included in the network analysis. a mixed graphical markov model as implemented in the bioconductor package “qpgraph” () was used to infer the gene–gene interactions and marker to gene causal relationships. for details, see file s1., raw sequence reads were downloaded from national center for biotechnology […]

2011
PMCID: 3110175
PMID: 21666801
DOI: 10.1371/journal.pbio.1000623

[…] tissue network for selected variables was performed using undirected gaussian graphical markov networks that represent q-order partial correlations between variables, implemented in the r package “qpgraph” that forms part of the bioconductor project (http://www.bioconductor.org). in these networks, missing edges denote zero partial correlations between pairs of variables, and thus imply […]


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qpgraph in publications

 (13)
PMCID: 5877975
PMID: 29463742
DOI: 10.1073/pnas.1716839115

[…] analysis (si appendix, section 12). the direct ancestry test was also performed on the masked data (si appendix, section 16), and the admixture graphs ( and si appendix, fig. s18) were fitted using qpgraph from the admixtools package () (si appendix, section 17). the chromopainter () analysis was run on the unmasked dataset (si appendix, fig. s19)., we thank the staff at the danish national […]

PMCID: 5675555
PMID: 28714977
DOI: 10.1038/ng.3917

[…] group. we determined the significance of the f3-statistic using a block jackknife and a block size of 5 cm. we considered statistics over 3 standard errors below zero to be significant., we used qpgraph to model each indian group on the cline as a mixture of ani and asi ancestry, using the model (yri, (indian group, (georgians, ani)), [(asi, onge])) proposed by moorjani et al. this approach […]

PMCID: 5473988
PMID: 28638442
DOI: 10.1186/s13040-017-0140-x

[…] protein, and metabolite data using more advanced biological-network-based approaches such as gaussian graphical models, partial correlation and bayesian networks for omics data integration (glasso, qpgraph). for instance, time-varying enrichment integromics subpathway analysis tool (chronos) is an r package built to extract regulatory sub-pathways along with their mirna regulators at each time […]

PMCID: 5515717
PMID: 27698418
DOI: 10.1038/nature19844

[…] at 2680-2340 bp carried little or no papuan ancestry, providing unambiguous confirmation that the ancestral population of polynesians was not fully formed by the end of the lapita period., we used qpgraph to explore models of population separation and mixture that might accommodate the ancient dna data (). we obtain fits using models in which polynesians today are mixtures of first remote […]

PMCID: 5003663
PMID: 27459054
DOI: 10.1038/nature19310

[…] neanderthal admixture than mbuti from sub-saharan africa., we estimated fst in smartpca with default parameters, inbreed: yes, and fstonly: yes., we carried out admixture graph modeling with the qpgraph software using mbuti as an outgroup unless otherwise specified., we used the qpwave, software, described in of ref., to test whether a set of ‘left’ populations is consistent […]


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qpgraph institution(s)
Department of Experimental and Health Sciences, Universitat Pompeu Fabra, Barcelona, Spain; Research Program on Biomedical Informatics, Institut Municipal d’Investigació Mèdica, Barcelona, Spain; Department of Statistical Science, Università di Bologna, Bologna, Italy
qpgraph funding source(s)
This work was supported by the Spanish Ministerio de Ciencia e Innovación (MICINN) (grant TIN2008-00556/TIN), by the ISCIII COMBIOMED Network (grant RD07/0067/0001), by a research fellowship of the Ramon y Cajal program from the Spanish MICINN (RYC-2006-000932) and by the Ministero dell’Università e della Ricerca (grant PRIN-2007AYHZWC, FISR MITICA).

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