inst/doc/FateID.R

In FateID: Quantification of Fate Bias in Multipotent Progenitors

## ----echo=FALSE---------------------------------------------------------------
knitr::opts_chunk$set(fig.width=8, fig.height=8) 

## ----eval = FALSE-------------------------------------------------------------
#  install.packages("FateID")

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library(FateID)

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data(intestine)

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x <- intestine$x
head(x[,1:5])

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y <- intestine$y
head(y)

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tar <- c(6,9,13)

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FMarker <- list(c("Defa20__chr8","Defa24__chr8"), "Clca3__chr3", "Alpi__chr1")
xf <- getPart(x,FMarker,fthr=NULL,n=5)
head(xf$part)
head(xf$tar)
tar <- xf$tar
y <- xf$part

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rc <- reclassify(x, y, tar, clthr=.75, nbfactor=5, use.dist=FALSE, seed=12345, nbtree=NULL, q=0.9)
y  <- rc$part

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v <- intestine$v
rc <- reclassify(v, y, tar, clthr=.75, nbfactor=5, use.dist=FALSE, seed=12345, nbtree=NULL, q=0.9)
y  <- rc$part

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x  <- rc$xf

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x <- getFeat(v,y,tar,fpv=0.01)

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tar <- c(6,9,13)
x <- intestine$x
y <- intestine$y
fb  <- fateBias(x, y, tar, z=NULL, minnr=5, minnrh=10, adapt=TRUE, confidence=0.75, nbfactor=5, use.dist=FALSE, seed=12345, nbtree=NULL)

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dr  <- compdr(x, z=NULL, m=c("tsne","cmd","umap"), k=2, tsne.perplexity=30, seed=12345)

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plotFateMap(y,dr,k=2,m="umap")

## ----eval=FALSE---------------------------------------------------------------
#  plotFateMap(y,dr,k=3,m="umap")

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plotFateMap(y,dr,k=2,m="umap",fb=fb,g="t6")

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pr <- plotFateMap(y,dr,k=2,m="umap",trthr=.33,fb=fb,prc=TRUE)

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v <- intestine$v
pr <-plotFateMap(y, dr, k=2, m="umap", g=c("Defa20__chr8", "Defa24__chr8"), n="Defa", x=v)

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E <- plotFateMap(y,dr,k=2,m="umap",g="E",fb=fb)
head(E)

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pr  <- prcurve(y,fb,dr,k=2,m="umap",trthr=0.33,start=3)

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n <- pr$trc[["t6"]]

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v <- intestine$v
fs  <- filterset(v,n=n,minexpr=2,minnumber=1)

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s1d <- getsom(fs,nb=50,alpha=.5)

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ps  <- procsom(s1d,corthr=.85,minsom=3)

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fcol <- sample(rainbow(max(y)))

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plotheatmap(ps$nodes.z, xpart=y[n], xcol=fcol, ypart=unique(ps$nodes), xgrid=FALSE, ygrid=TRUE, xlab=FALSE)

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plotheatmap(ps$all.z, xpart=y[n], xcol=fcol, ypart=ps$nodes, xgrid=FALSE, ygrid=TRUE, xlab=FALSE)

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plotheatmap(ps$all.e, xpart=y[n], xcol=fcol, ypart=ps$nodes, xgrid=FALSE, ygrid=TRUE, xlab=FALSE)

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plotheatmap(ps$all.b, xpart=y[n], xcol=fcol, ypart=ps$nodes, xgrid=FALSE, ygrid=TRUE, xlab=FALSE)

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g <- names(ps$nodes)[ps$nodes == 1]

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plotexpression(fs, y, g, n, col=fcol, name="Node 1", cluster=FALSE, alpha=.5, types=NULL)

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plotexpression(fs, y, "Clca4__chr3", n, col=fcol, cluster=FALSE, alpha=.5, types=NULL)

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plotexpression(fs, y, g, n, col=fcol, name="Node 1", cluster=FALSE, types=sub("\\_\\d+","",n))

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group <- head(g,6)
plotexpressionProfile(fs, y, group, n, name="Node 1", cluster=FALSE)

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thr <- .5
a   <- "t13"
b   <- "t6"
cl  <- c(3,4,5)
A <- rownames(fb$probs)[fb$probs[,a] > thr]
A <- A[y[A] %in% cl]
B <- rownames(fb$probs)[fb$probs[,b] > thr]
B <- B[y[B] %in% cl]
de <- diffexpnb(v,A=A,B=B,DESeq=FALSE,norm=FALSE,vfit=NULL,locreg=FALSE)

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plotdiffgenesnb(de,mthr=-4,lthr=0,Aname=a,Bname=b,padj=FALSE)

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gene2gene(intestine$v,intestine$y,"Muc2__chr7","Apoa1__chr9")

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gene2gene(intestine$v, intestine$y, "Muc2__chr7", "Apoa1__chr9", fb=fb, tn="t6", plotnum=FALSE)

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k <- impGenes(fb,"t6")