MACOED statistics

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Associated diseases

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MACOED specifications

Information


Unique identifier OMICS_10111
Name MACOED
Software type Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux
Programming languages C++, MATLAB
Computer skills Advanced
Stability Stable
Maintained Yes

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Maintainer


  • person_outline Hong-Bin Shen <>

Publication for MACOED

MACOED in publications

 (3)
PMCID: 5906634
PMID: 29670206
DOI: 10.1038/s41598-018-24588-5

[…] time. with using the exhaustive strategy, all of epistatic combinations have been tested, so that the power of association studies is relatively higher. heuristic methods such as antepiseeker and macoed use prior knowledge or information retrieved by swarm intelligence to narrow down the combination space. the main limitation of heuristic methods is randomness. it means that the results may […]

PMCID: 5599559
PMID: 28912584
DOI: 10.1038/s41598-017-11064-9

[…] snp sites into m groups according to correlation among snps, only k-way (k < = m) snp combinations are selected out of the m groups. ant colony optimization (aco) is adopted in antepiseeker and macoed, where the former employs chi-square test(χ 2) score to evaluate association between snp combinations and phenotype, while the latter adopts bayesian based k2-score and logistic regression […]

PMCID: 4564769
PMID: 26442103
DOI: 10.3389/fgene.2015.00285

[…] search of epistasis within each built ant is performed, as well as within the set of snps that have the highest pheromone levels. the ant colony strategy was also exploited more recently in macoed (jing and shen, )., the positive feedback effect represents an interesting feature of the algorithm. unfortunately, many parameters require fine tuning, like the number of iterations, […]


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MACOED institution(s)
Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, Shanghai, China; Key Laboratory of System Control and Information Processing, Ministry of Education of China, Shanghai, China
MACOED funding source(s)
The National Natural Science Foundation of China [Nos. 61222306, 91130033, 61175024]; Shanghai Science and Technology Commission [No. 11JC1404800]; a Foundation for the Author of National Excellent Doctoral Dissertation of PR China [No. 201048]

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