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MVgen()
|
Amputation of a dataset |
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check.conditions()
|
Check if the design is valid |
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check.design()
|
Check if the design is valid |
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datasim
|
A single simulated dataset |
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eBayes.mod()
|
MI-aware Modifed eBayes Function |
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formatLimmaResult()
|
Format a Result from Limma |
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hid.ebayes()
|
MI-aware Modifed eBayes Function |
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limmaCompleteTest.mod()
|
Computes a hierarchical differential analysis |
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make.contrast()
|
Builds the contrast matrix |
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make.design.1()
|
Builds the design matrix for designs of level 1 |
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make.design.2()
|
Builds the design matrix for designs of level 2 |
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make.design.3()
|
Builds the design matrix for designs of level 3 |
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make.design()
|
Builds the design matrix |
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meanImp_emmeans()
|
Multiple Imputation Estimate |
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mi4limma()
|
Differential analysis after multiple imputation |
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mi4p-package
|
mi4p: Multiple imputation for proteomics |
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mm_peptides
|
mm_peptides - peptide-level intensities for mouse |
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multi.impute()
|
Multiple imputation of quantitative proteomics datasets |
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norm.200.m100.sd1.vs.m200.sd1.list
|
A list of simulated datasets. |
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proj_matrix()
|
Variance-Covariance Matrix Projection |
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protdatasim()
|
Data simulation function |
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qData
|
Extract of the abundances of Exp1_R25_pept dataset |
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rubin1.all()
|
First Rubin rule (all peptides) |
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rubin1.one()
|
First Rubin rule (a given peptide) |
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rubin2.all()
|
Computes the 2nd Rubin's rule (all peptides) |
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rubin2bt.all()
|
2nd Rubin's rule Between-Imputation component (all peptides) |
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rubin2bt.one()
|
2nd Rubin's rule Between-Imputation Component (a given peptide) |
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rubin2wt.all()
|
2nd Rubin's rule Within-Variance Component (all peptides) |
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rubin2wt.one()
|
2nd Rubin's rule Within-Variance Component (a given peptide) |
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sTab
|
Experimental design for the Exp1_R25_pept dataset |
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test.design()
|
Check if xxxxxx |
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within_variance_comp_emmeans()
|
Multiple Imputation Within Variance Component |