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Ordering patients on smooth manifolds using lineage estimation tools
Hi all
thank you for the interesting pipeline, its a neat work that impresses me everytime :)
i was wondering if you could explain the rationale behind your get var genes function Get.High.Var.Genes
, especially the part on binLims BinLims <- seq(log(10/length(M)),max(M),Bins + 1)
; i dont quite understand the rationale for setting start as the number of genes in the assay, but setting the greatest highest rowmeans max(M
expression as the end for seq(). conventionally, i only noticed BinLims setting up using min and max(M) of expression values instead of the length of number of genes.
from your Misc.Processing script:
Get.High.Var.Genes <- function(Dat, Bins = 10, frac = .2){
M = rowMeans(Dat)
V = RowVar(Dat)
BinLims <- seq(log(10/length(M)),max(M),Bins + 1)
In = c()
for (i in 1:Bins){
In_red <- which(as.logical((M >= BinLims[i])*
(M < BinLims[i+1])))
temp <- V[In_red]/M[In_red]
temp2 <- sort(temp, decreasing = T, index.return = T)
I <- temp2$ix
topX <- round(length(In_red)*frac)
In <- c(In,In_red[I[1:topX]])
}
In <- In[!is.na(In)]
In <- unique(In)
return(In)
}
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