addCells | R Documentation |
The function deals a little with the n+1 problem.
addCells(cnr, newX, newY, newqc, newYe = NULL, do.clean = TRUE, ...)
cnr |
a cnr bundle |
newX |
bin data for the new cells to be incorporated |
newY |
phenotype data for the new cells |
newqc |
qc metadata for the new cells |
newYe |
exprssion data for new cells |
do.clean |
weather to remove additional data stored in the cnr, default is TRUE |
... |
additional parameters if needed |
Your data needs to be 'exact' to the existing cnr for it to be compatible. This means it needs to have the same bin coordinates and number of X bins, annotation colums, and same qc colums. It is assumed you generated it with the same pipeline.
Returns a CNR object after adding new cells. If 'do.clean = TRUE' only the original eight data items will be returned.
X copy number data
Y phenotype data
exprs expression data
qc quality control data
chromInfo bin to chromosome information
gene.index gene to bin and chromosome information
cells list of cells
bulk bulk DNA or single-cell copy number. If TRUE, data is bulk DNA log2 ratio
... additional analyzed results
library(gac) data(cnr) sapply(cnr, dim) data(pheno) data(qc) ## create unique cell names n.cells <- nrow(cnr$Y) new.cells <- paste0("cell", n.cells + 1:2) ## new X w simulated data newX <- data.frame(cbind(rep(c(5,2), c(3000, 2000)), rep(c(2,4), c(3000, 2000)))) names(newX) <- new.cells head(newX) tail(newX) ## creating new phenotypes newY <- head(pheno, n = 2) newY$cellID <- new.cells rownames(newY) <- newY$cellID newY[, c(6:9)] <- newY[,c(6,9)]+3 newY ## creating new QC newQC <- head(qc, 2) newQC$cellID <- new.cells rownames(newQC) <- newQC$cellID newQC[,2:4] <- newQC[,2:4] + 2 newQC ## add cells cnr <- addCells(cnr, newX = newX, newY = newY, newqc = newQC) sapply(cnr, dim)
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