Package index • CLAMP

All functions
`AUC()`	Compute AUC using Wilcoxon rank-sum test
`BH()`	Adjust p-values using Benjamini-Hochberg method
`CLAMPbase()`	CLAMP base matrix factorization
`CLAMPdotplot()`	Dot plot of top pathways for a single latent variable
`CLAMPdotplotAll()`	Dot plot of pathway-LV associations across all latent variables
`CLAMPfull()`	Runs the streamlined full CLAMP model.
`CLAMPfullnVP()`	Full CLAMP model with prior information and cross-validation
`CLAMPplotTopZ()`	Plot top genes per LV by Z loading
`CLAMPplotU()`	Plot the U matrix (pathway-LV associations) as a heatmap
`allAgainstAllAUCs()`	Compute all-vs-all AUC matrix
`binarizeTop()`	Binarize matrix by top-k values per column
`celltypeTargets`	Cell-type deconvolution matrix
`cleanFBM()`	Clean a Filebacked Big Matrix (FBM) by log-transforming and handling NAs
`commonRows()`	Find common row names between two matrices or data frames
`compareBs()`	Compare two sets of factor loadings or embeddings
`computeRowStatsFBM()`	Compute row-wise sum and sum of squares for a Filebacked Big Matrix
`compute_svd()`	Compute a truncated SVD for a CLAMP input matrix
`cpmCLAMP()`	Compute counts-per-million (CPM) for CLAMP pipelines
`cpmCLAMPFBM()`	Compute CPM on a file-backed matrix for CLAMP (in-place)
`crossVal()`	Cross-validation AUC for CLAMP latent variables and pathways
`cross_ZY()`	Cross-product Z^T Y with FBM or dense matrices
`dataWholeBlood`	Whole-blood reference expression matrix
`filterFBM()`	Filter rows of a Filebacked Big Matrix based on mean and variance
`findSplineMax()`	Find the location of the maximum of a smoothing spline
`getAUCstats()`	Count number of latent variables exceeding AUC thresholds
`getChat()`	Compute Chat matrix from prior annotation
`getGMT()`	Download and read a GMT file from a URL
`getMatchedPathwayMat()`	Subset and filter pathway matrix to match target genes
`getMatchedPathwayMat2()`	Subset and filter multiple pathway matrices to match target genes
`getMatchedPathwayMatList()`	Subset and filter multiple pathway matrices to match target genes
`getMatchedPathwayMatOld()`	Subset and filter pathway matrix to match target genes
`getMaxAUC()`	Get maximum AUC per latent variable
`getScaleFromSVs()`	Estimate noise scale from singular values with linear tail extrapolation
`gmtListToSparseMat()`	Convert a list of GMT gene sets to a sparse matrix
`majorCellTypes`	Major cell-type annotations
`mat_mult()`	Matrix multiplication with support for FBM objects
`max_correspondence_greedy()`	Greedy maximum correspondence from correlation matrix
`mymessage()`	Print a concatenated message
`num.pc()`	Estimate number of principal components via elbow or permutation method
`oneToOneMask()`	One-to-one masking of maximum associations
`panDB`	panDB gene-set database
`pinv.ridge()`	Ridge-regularized pseudoinverse via SVD
`plotTopZ_Complex()`	ComplexHeatmap visualization of top genes by latent variable
`preprocessCLAMP()`	Preprocess an expression matrix for CLAMP
`preprocessCLAMPFBM()`	Preprocess a bigstatsr FBM for CLAMP
`projectCLAMP()`	Project new data into CLAMP latent space
`read_gmt()`	Read a GMT file into a list
`ridge_B()`	Ridge regression update for B
`rotateSVD()`	Rotate SVD components to make dominant directions positive
`row_cor()`	Row-wise correlation between two matrices
`run_elbow()`	Run elbow method to estimate number of PCs
`run_permutation()`	Run permutation method to estimate number of PCs
`select_clamp_k()`	Select default number of CLAMP latent variables from an SVD
`select_svd_k()`	Select default number of components for a CLAMP solver SVD
`solveU()`	Fit the loading matrix Z using sparse regression of prior information U
`squashZscore()`	Squash extreme z-scores
`tscale()`	Row-wise scaling (mean 0, sd 1)
`winsor_topk()`	Winsorize matrix columns by capping the top-k values
`xCell`	xCell cell-signature matrix
`zscoreCLAMP()`	Z-score a filtered expression matrix for CLAMP
`zscoreCLAMPFBM()`	Z-score a filtered FBM in-place

Reference

All functions