| plotexpressionProfile {FateID} | R Documentation | 
Plotting smoothed pseudo-temporal expression profiles for groups of genes
Description
This function allows plotting loess-smoothed pseudo-temporal expression profiles for groups of genes. To display gene expression profiles on the same scale, row sums are normalized to one.
Usage
plotexpressionProfile(
  x,
  y,
  g,
  n,
  logsc = FALSE,
  col = NULL,
  name = NULL,
  cluster = FALSE,
  alpha = 0.5,
  lwd = 1,
  ylim = NULL,
  seed = 12345,
  ylab = NULL
)
Arguments
x | 
 expression data frame with genes as rows and cells as columns. Gene IDs should be given as row names and cell IDs should be given as column names.  | 
y | 
 clustering partition. A vector with an integer cluster number for each cell. The order of the cells has to be the same as for the columns of   | 
g | 
 a gene ID corresponding to one of the rownames of   | 
n | 
 ordered vector of cell IDs to be included. Cell IDs need to be column names of   | 
logsc | 
 logical value. If   | 
col | 
 optional vector of valid color names used for the profiles of all genes in   | 
name | 
 optional character string. This argument corresponds to a title for the plot. Default value is   | 
cluster | 
 logical value. If   | 
alpha | 
 positive real number. Pseudo-temporal expression profiles are derived by a local regression of expression values across the ordered cells using the function   | 
lwd | 
 line width of profiles. Default value is 1.  | 
ylim | 
 vector of two numerical values: lower and upper limit of values shown on the y-axis. Default value is   | 
seed | 
 integer number. Random seed for determining colour scheme. Default is 12345.  | 
ylab | 
 Optional label for the y-axis. Default is   | 
Value
None
Examples
x <- intestine$x
y <- intestine$y
v <- intestine$v
fcol <- intestine$col
tar <- c(6,9,13)
fb <- fateBias(x,y,tar,z=NULL,minnr=5,minnrh=10,nbfactor=5,use.dist=FALSE,seed=NULL,nbtree=NULL)
dr <- compdr(x,z=NULL,m="cmd",k=2,tsne.perplexity=30)
pr <- prcurve(y,fb,dr,k=2,m="cmd",trthr=0.4,start=NULL)
n <- pr$trc[["t6"]]
fs  <- filterset(v,n,minexpr=2,minnumber=1)
s1d <- getsom(fs,nb=1000,alpha=.5)
ps <- procsom(s1d,corthr=.85,minsom=3)
# plot average profile of all genes of node 1 in the self-organizing map
g <- sample(names(ps$nodes)[ps$nodes == 1],5)
plotexpressionProfile(v,y,g,n,col=fcol,name="Node 1",alpha=.2)