Package: combi 1.17.0

Stijn Hawinkel

combi: Compositional omics model based visual integration

This explorative ordination method combines quasi-likelihood estimation, compositional regression models and latent variable models for integrative visualization of several omics datasets. Both unconstrained and constrained integration are available. The results are shown as interpretable, compositional multiplots.

Authors:Stijn Hawinkel [cre, aut]

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NEWS

# Install 'combi' in R:

install.packages('combi', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/centerforstatistics-ugent/combi/issues

Datasets:

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

On BioConductor:combi-1.17.0(bioc 3.20)combi-1.16.0(bioc 3.19)

bioconductor-package

7 exports 0.71 score 94 dependencies 1 mentions

Last updated 2 months agofrom:125ac6398b

Exports:addLink checkMeanVarTrend combi convPlot extractCoords extractData inflPlot

Dependencies:abind ade4 alabama ape askpass BB Biobase BiocGenerics biomformat Biostrings cli cluster cobs codetools colorspace cpp11 crayon curl data.table DBI DelayedArray digest fansi farver foreach GenomeInfoDb GenomeInfoDbData GenomicRanges ggplot2 glue gtable httr igraph IRanges isoband iterators jsonlite labeling lattice lifecycle limma magrittr MASS Matrix MatrixGenerics MatrixModels matrixStats mgcv mime multtest munsell nleqslv nlme numDeriv openssl permute phyloseq pillar pixmap pkgconfig plyr quadprog quantreg R6 RColorBrewer Rcpp RcppArmadillo reshape2 rhdf5 rhdf5filters Rhdf5lib rlang S4Arrays S4Vectors scales sp SparseArray SparseM statmod stringi stringr SummarizedExperiment survival sys tensor tibble UCSC.utils utf8 vctrs vegan viridisLite withr XVector zlibbioc

Manual for the combi pacakage

Rendered fromcombi.Rmdusingknitr::rmarkdownon Jun 14 2024.

Last update: 2021-11-30
Started: 2020-03-18

Citation

Development and contributors

Readme and manuals

Help Manual

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