Compositional omics model based visual integration

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Documentation for package ‘combi’ version 1.19.0

• DESCRIPTION file.
• User guides, package vignettes and other documentation.
• Package NEWS.

Help Pages

addLink	Add a link on a compositional plot
arrayMult	Array multiplication
buildCentMat	A function to build a centering matrix based on a dataframe
buildCompMat	Build the composition matrix for a certain dimension m dimensions
buildConfMat	Build confounder design matrices with and without intercepts
buildCovMat	A function to build the covariate matrix of the constraints
buildEmptyJac	Prepare an empty Jacobian matrix, with useful entries prefilled. In case of distribution "gaussian", it returns the lhs matrix of the linear system for finding the feature paramters
buildMarginalOffset	Build an offset matrix from an marginal model object
buildMu	A function to build the mu matrix
buildMuMargins	Build the marginal mu matrix
buildOffsetModel	Build a marginal offset matrix given a model
checkAlias	Check for alias structures in a dataframe, and throw an error when one is found
checkMeanVarTrend	Quickly check if the mean variance trend provides a good fit
checkMonotonicity	Check for monotonicity in compositional datasets fro given dimensions
combi	Perform model-based data integration
convPlot	Plot the convegrence of the different parameter estimates in a line plot
deriv2LagrangianFeatures	The score function to estimate the latent variables
deriv2LagrangianLatentVars	The jacobian function to estimate the latent variables
deriv2LagrangianLatentVarsConstr	The score function to estimate the latent variables
derivLagrangianFeatures	The score function to estimate the feature parameters
derivLagrangianLatentVars	The score function to estimate the latent variables
derivLagrangianLatentVarsConstr	The score function to estimate the latent variables
estFeatureParameters	Estimate the feature parameters
estIndepModel	Estimate the independence model belonging to one view
estLatentVars	Estimate the latent variables
estMeanVarTrend	Estimate a column-wise mean-variance trend
estOff	Estimate the row/column parameters of the independence model
extractCoords	Extract coordinates from fitted object
extractData	Helper function to extract data matrix from phyloseq, expressionset objects etc. Also filers out all zero rows
extractMat	A function to extract a data matrix from a number of objects
extractMat-method	A function to extract a data matrix from a number of objects
filterConfounders	Filter out the effect of known confounders
getInflLatentVar	Extract the influence on the estimation of the latent variable
gramSchmidtOrth	Gram schimdt orhtogonalize a with respect to b, and normalize
indentPlot	Functions to indent the plot to include the entire labels
inflPlot	A ggplot line plot showing the influences
influence.combi	Evaluate the influence function
jacConfounders	Jacobian when estimating confounder variables
jacConfoundersComp	Jacobian for conditioning under compositionality
jacFeatures	Evaluate the jacobian for estimating the feature parameters for one view
jacLatentVars	Evaluate the jacobian for estimating the latent variable for one view
jacLatentVarsConstr	Evaluate the jacobian for estimating the latent variable for one view for constrained ordination
plot.combi	Make multiplots of the data integration object
polyHorner	Horner's method to evaluate a polynomial, copied from the polynom package. the most efficient way
predictSpline	A custom spline prediction function, extending linearly with a slope such that prediction never drops below first bisectant
prepareJacMat	prepare the jacobian matrix
prepareJacMatComp	prepare the jacobian for the latent variabels compostional
prepareScoreMat	Prepare a helper matrix for score function evaluation under quasi-likelihood
print.combi	Print an overview of a fitted combi x
quasiJacIndep	The jacobian for column offset estimation
quasiScoreIndep	Quasi score equations for column offset parameters of sequence count data
rowMultiply	A function to efficiently row multiply a matrix and a vector
scaleCoords	A helper function to rescale coordinates
scoreConfounders	Score functions for confounder variables
scoreConfoundersComp	Score equations for conditioning under compositionality
scoreFeatureParams	Evaluate the score functions for the estimation of the feature parameters for a single dataset
scoreLatentVars	Evaluate the score functions for the estimation of the latent variables for a single dataset
seqM	A small auxiliary function for the indices of the lagrange multipliers
trimOnConfounders	Trim based on confounders to avoid taxa with only zero counts
zhangMetabo	Metabolomes of mice that underwent Pulsed Antibiotic Treatment (PAT) and controls
zhangMetavars	Baseline sample variables of PAT and control mice
zhangMicrobio	Microbiomes of mice that underwent Pulsed Antibiotic Treatment (PAT) and controls