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Protocols

Grinn specifications

Information


Unique identifier OMICS_12505
Name Grinn
Software type Package/Module
Interface Command line interface, Graphical user interface
Restrictions to use None
Input data Genomic, proteomic, and metabolomic data
Operating system Unix/Linux, Mac OS, Windows
Programming languages R
License GNU General Public License version 3.0
Computer skills Advanced
Version 2.7
Stability Stable
Maintained Yes

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Documentation


Maintainer


  • person_outline Kwanjeera W.

Grinn citations

 (4)
library_books

Assessing Performance of Spore Samplers in Monitoring Aeromycobiota and Fungal Plant Pathogen Diversity in Canada

2018
Appl Environ Microbiol
PMCID: 5930333
PMID: 29475862
DOI: 10.1128/AEM.02601-17

[…] igh humidity is essential for growth of most mesophilic fungi and was considered a good predictor of fungal prevalence. The total variance explained by the RDA model (ca. 22%) was higher than that of Grinn-Gofroń and Bosiacka () (ca. 16.5%) and suggested that mean air temperature was the most important factor affecting the composition of airborne fungal spores. Overall, our results suggest that th […]

call_split

A comparative study of hourly and daily relationships between selected meteorological parameters and airborne fungal spore composition

2017
PMCID: 5818593
PMID: 29497241
DOI: 10.1007/s10453-017-9493-3
call_split See protocol

[…] analysis (DCA) results detected a linear structure of the spore data. Detailed information about the applied multivariate methods, stepwise forward selection and tests of significance is available in Grinn-Gofroń and Bosiacka ().Redundancy among the meteorological variables was explored with the variance inflation factor (VIF). VIF analysis (available in CANOCO) is a diagnostic tool used to identi […]

library_books

Computational dynamic approaches for temporal omics data with applications to systems medicine

2017
BioData Min
PMCID: 5473988
PMID: 28638442
DOI: 10.1186/s13040-017-0140-x

[…] he correlation analysis with other types of relationships such as biochemical reactions and molecular structural and mass spectral similarity (MetaMapR).In addition, they provide a dynamic interface (Grinn) to integrate gene, protein, and metabolite data using more advanced biological-network-based approaches such as Gaussian graphical models, partial correlation and Bayesian networks for omics da […]

library_books

Genomic, Proteomic, and Metabolomic Data Integration Strategies

2015
PMCID: 4562606
PMID: 26396492
DOI: 10.4137/BMI.S29511

[…] tools such as MetaMapR incorporate correlation analysis with other relationships such as biochemical reactions and molecular structural and mass spectral similarity. The recently developed R package Grinn implements a Neo4j graph database to provide a dynamic interface to rapidly integrate gene, protein, and metabolite data using both biological-network-based and correlation-based approaches.Whil […]

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