fastRUVIII {scMerge} | R Documentation |
Perform a fast version of the ruv::RUVIII algorithm for scRNA-Seq data noise estimation
fastRUVIII( Y, M, ctl, k = NULL, eta = NULL, svd_k = 50, include.intercept = TRUE, average = FALSE, BPPARAM = SerialParam(), BSPARAM = ExactParam(), fullalpha = NULL, return.info = FALSE, inputcheck = TRUE )
Y |
The unnormalised scRNA-Seq data matrix. A m by n matrix, where m is the number of observations and n is the number of features. |
M |
The replicate mapping matrix. The mapping matrix has m rows (one for each observation), and each column represents a set of replicates. The (i, j)-th entry of the mapping matrix is 1 if the i-th observation is in replicate set j, and 0 otherwise. See ruv::RUVIII for more details. |
ctl |
An index vector to specify the negative controls. Either a logical vector of length n or a vector of integers. |
k |
The number of unwanted factors to remove. This is inherited from the ruvK argument from the scMerge::scMerge function. |
eta |
Gene-wise (as opposed to sample-wise) covariates. See ruv::RUVIII for details. |
svd_k |
If BSPARAM is set to |
include.intercept |
When eta is specified (not NULL) but does not already include an intercept term, this will automatically include one. See ruv::RUVIII for details. |
average |
Average replicates after adjustment. See ruv::RUVIII for details. |
BPPARAM |
A |
BSPARAM |
A |
fullalpha |
Not used. Please ignore. See ruv::RUVIII for details. |
return.info |
Additional information relating to the computation of normalised matrix. We recommend setting this to true. |
inputcheck |
We recommend setting this to true. |
A normalised matrix of the same dimensions as the input matrix Y.
Yingxin Lin, John Ormerod, Kevin Wang
L = ruvSimulate(m = 200, n = 500, nc = 400, nCelltypes = 3, nBatch = 2, lambda = 0.1, sce = FALSE) Y = L$Y; M = L$M; ctl = L$ctl improved1 = scMerge::fastRUVIII(Y = Y, M = M, ctl = ctl, k = 20, BSPARAM = BiocSingular::ExactParam()) improved2 = scMerge::fastRUVIII(Y = Y, M = M, ctl = ctl, k = 20, BSPARAM = BiocSingular::RandomParam(), svd_k = 50) old = ruv::RUVIII(Y = Y, M = M, ctl = ctl, k = 20) all.equal(improved1, old) all.equal(improved2, old)