Description Usage Arguments Details Value Examples
This function estimates proportion matrix (A matrix) from observed mixture expression data based on marker genes.
1 | AfromMarkers(data, MGlist, scaleRecover = TRUE)
|
data |
A data set that will be internally coerced into a matrix. Each row is a gene and each column is a sample. data should be in non-log linear space with non-negative numerical values (i.e. >= 0). Missing values are not supported. All-zero rows will be removed internally. |
MGlist |
A list of vectors, each of which contains known markers and/or CAM-detected markers for one subpopulation. |
scaleRecover |
If TRUE, scale ambiguity of each column vector in A matrix is removed based on sum-to-one constraint on each row. |
With the expression levels of subpopulation-specific
marker genes, the relative proportions of constituent subpopulations are
estimated by spatial median using l1median
.
Marker genes could be from unsupervised/supervised detection or
from literatures.
Scale ambiguity is optionally removed based on sum-to-one constraint of rows.
Return the estimated proportion matrix (A matrix).
1 2 3 4 5 6 7 8 9 | #obtain data and marker genes
data(ratMix3)
S <- ratMix3$S
pMGstat <- MGstatistic(S, c("Liver","Brain","Lung"))
pMGlist.FC <- lapply(c("Liver","Brain","Lung"), function(x)
rownames(pMGstat)[pMGstat$idx == x & pMGstat$OVE.FC > 10])
#estimate A matrix from markers
Aest <- AfromMarkers(ratMix3$X, pMGlist.FC)
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