metapone {metapone} | R Documentation

## METAbolic pathway testing using both POsitive and NEgative mode data

### Description

Metapone conducts pathway tests for untargeted metabolomics data. It has three main characteristics: (1) expanded database combining SMPDB and Mummichog databases, with manual cleaning to remove redundancies; (2) A new weighted testing scheme to address the issue of metabolite-feature matching uncertainties; (3) Can consider positive mode and negative mode data in a single analysis.

### Usage

    metapone(pos = NULL, neg = NULL, pa, hmdbCompMZ, pos.adductlist =
    c("M+H", "M+NH4", "M+Na", "M+ACN+H", "M+ACN+Na", "M+2ACN+H", "2M+H",
    "2M+Na", "2M+ACN+H"), neg.adductlist = c("M-H", "M-2H", "M-2H+Na",
    "M-2H+K", "M-2H+NH4", "M-H2O-H", "M-H+Cl", "M+Cl", "M+2Cl"),
    use.fractional.count = TRUE, match.tol.ppm = 5, p.threshold = 0.05,
    n.permu = 200, fractional.count.power = 0.5, max.match.count = 10)

### Arguments

`pos` | The positive ion mode test results. A matrix with four columns: m/z, retention time, p-value, test statistic. The package doesn't require both pos and neg to be present. One ion mode result is sufficient.
`neg` | The negative ion mode test results. A matrix with four columns: m/z, retention time, p-value, test statistic. The package doesn't require both pos and neg to be present. One ion mode result is sufficient.
`pa` | Pathway information. A data frame with five columns: database pathway ID, pathway name, HMDB ID, KEGG ID, category of pathway.
`hmdbCompMZ` | the m/z values of common adduct ions of HMDB metaboites. See the help file of hmdbCompMZ for details.
`pos.adductlist` | The vector of positive adduct ions to be considered.
`neg.adductlist` | The vector of negative adduct ions to be considered.
`use.fractional.count` | A lot of features match to multiple metabolites by m/z. Whether to discount such matches by using fractional counts.
`match.tol.ppm` | The ppm level when conducting m/z match.
`p.threshold` | The threshold of p-values of metabolic features to be considered significant.
`n.permu` | The number of permutations in permutation test.
`fractional.count.power` | The fractional counts are taken to this power to transform the weights.
`max.match.count` | When calculating fractional counts, some features might be matched to too many. In that case the number of matches is capped by the value of max.match.count.

### Value

The method returns a generic S4 object of class "metapone.result":

`@test.results` | A matrix with 6 columns: "p_value", "n_significant metabolites", "n_mapped_metabolites", "n_metabolites", "significant metabolites", "mapped_metabolites". Each row is for a pathway.
`@mapped.features` | A list. Each item is for a pathway. The item lists matched significant metabolites.

### Author(s)

Tianwei Yu<yutianwei@cuhk.edu.cn>)

### References

https://smpdb.ca/ https://shuzhao-li.github.io/mummichog.org/software.html

### See Also

hmdbCompMZ, pa

### Examples

    data(hmdbCompMZ.metapone)
    data(pa)
    data(pos)
    data(neg)
    r<-metapone(pos, neg, pa, hmdbCompMZ=hmdbCompMZ.metapone, p.threshold=0.05,
       n.permu=100,fractional.count.power=0.5, max.match.count=10)
    hist(ptable(r)[,1])

[Package metapone version 1.0.0 Index]