GraphsPermut: Permutation test of PLS-DA and OPLS-DA
In AlzbetaG/Metabol: The statistical analysis of metabolomic data
Description
Usage
Arguments
Details
Value
References
Description
Makes permutation test of PLS-DA and OPLS-DA, displays score plots (for OPLS-DA only), permutation plots and summary table.
Usage
1
2
GraphsPermut(data, name, groupnames, tsf = "clr", type = "opls",
permut = 100, QCs = FALSE)
Arguments
data
Data table with variables (metabolites) in columns. Samples in rows are sorted according to specific groups.
name
A character string or expression indicating a name of data set. It occurs in names of every output.
groupnames
A character vector defining specific groups in data. Every string must be specific for each group and they must not overlap.
tsf
Data transformation must be defined by "clr" (default), "log", "log10", "PQN", "lnPQN", "pareto" or "none". See Details.
type
Definition which type of method do you want to use. If "opls" is set (default), OPLS-DA is performed and the number of orthogonal components is automatically computed by using the cross-validation (with a maximum of 9 orthogonal components). If two groups are not nicely separated, the algorithm returns error. In this case set this parameter to "err". When "pls" is set, PLS-DA is done.
permut
Number of random permutations of response labels to estimate R2Y and Q2Y significance by permutation testing. Default is 100.
QCs
logical. If FALSE (default) quality control samples (QCs) are automatically distinguished and skipped.
Details
Data transformation: with "clr" clr trasformation is used (see References), with "log" natural logarithm is used, with "log10" decadic logarithm is used, with "pareto" data are only scaled by Pareto scaling, with "PQN" probabilistic quotient normalization is done, with "lnPQN" natural logarithm of PQN transformed data is done, with "none" no tranformation is done.
Up to twenty different groups can be distinguished in data (including QCs).
Value
Score plots and permutation plots of OPLS-DA.
Excel file with summary.
References
Aitchison, J. (1986) The Statistical Analysis of Compositional Data Monographs on Statistics and Applied Probability. Chapman & Hall Ltd., London (UK). p. 416.
Thevenot E. A. et al., Analysis of the human adult urinary metabolome variations with age, body mass index and gender by implementing a comprehensive workflow for univariate and OPLS statistical analyses,Journal of Proteome Research 14, 3322-3335, 2015.
AlzbetaG/Metabol documentation built on May 31, 2019, 12:39 a.m.
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Description Usage Arguments Details Value References
Description
Makes permutation test of PLS-DA and OPLS-DA, displays score plots (for OPLS-DA only), permutation plots and summary table.
Usage
1 2 | GraphsPermut(data, name, groupnames, tsf = "clr", type = "opls",
permut = 100, QCs = FALSE)
|
Arguments
data |
Data table with variables (metabolites) in columns. Samples in rows are sorted according to specific groups. |
name |
A character string or expression indicating a name of data set. It occurs in names of every output. |
groupnames |
A character vector defining specific groups in data. Every string must be specific for each group and they must not overlap. |
tsf |
Data transformation must be defined by "clr" (default), "log", "log10", "PQN", "lnPQN", "pareto" or "none". See Details. |
type |
Definition which type of method do you want to use. If "opls" is set (default), OPLS-DA is performed and the number of orthogonal components is automatically computed by using the cross-validation (with a maximum of 9 orthogonal components). If two groups are not nicely separated, the algorithm returns error. In this case set this parameter to "err". When "pls" is set, PLS-DA is done. |
permut |
Number of random permutations of response labels to estimate R2Y and Q2Y significance by permutation testing. Default is 100. |
QCs |
logical. If FALSE (default) quality control samples (QCs) are automatically distinguished and skipped. |
Details
Data transformation: with "clr" clr trasformation is used (see References), with "log" natural logarithm is used, with "log10" decadic logarithm is used, with "pareto" data are only scaled by Pareto scaling, with "PQN" probabilistic quotient normalization is done, with "lnPQN" natural logarithm of PQN transformed data is done, with "none" no tranformation is done.
Up to twenty different groups can be distinguished in data (including QCs).
Value
Score plots and permutation plots of OPLS-DA.
Excel file with summary.
References
Aitchison, J. (1986) The Statistical Analysis of Compositional Data Monographs on Statistics and Applied Probability. Chapman & Hall Ltd., London (UK). p. 416.
Thevenot E. A. et al., Analysis of the human adult urinary metabolome variations with age, body mass index and gender by implementing a comprehensive workflow for univariate and OPLS statistical analyses,Journal of Proteome Research 14, 3322-3335, 2015.
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Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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