Description Usage Arguments Value Author(s) Examples
Perform a fast version of the ruv::RUVIII algorithm for scRNA-Seq data noise estimation
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 |
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
1 2 3 4 5 6 7 8 9 | 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)
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