#
# Reading data : one row for each strain !
#
tab=readLines("don.txt")
nl=length(tab)
#
# Compute overall min and max
#
minl = rep(0,nl)
maxl = minl
for (i in 1:nl) {
	v = as.numeric(strsplit(tab," ")[[i]][-1])
	minl[i] = min(v)
	maxl[i] = max(v)
}
mini = floor(min(minl))
maxi = ceiling(max(maxl))
#
# Declare a table with max size and fill it with data from lists
#
df1=rep(0,nl*maxi)
dim(df1) = c(nl, maxi)
cnames=rep(0,nl)
for (i in 1:nl) {
	li=unlist(strsplit(tab[i]," "))
	l1=length(li)
	xi=as.numeric(li[2:l1])
	cnames[i] = li[1]
	for (k in 1:l1-1) {
		df1[i, round(xi[k])] = xi[k]
	}
}
#
# Compute the number of columns containing not only zeroes
#
nz = 0
for (i in 1:maxi) {
	if (!all (df1[,i] == 0)) {
		nz = nz + 1
	}
}
#
# New table without columns of zeroes
#
df2=rep(0,nl*nz)
dim(df2) = c(nl, nz)
j = 1
for (i in 1:maxi) {
	if (!all (df1[,i] == 0)) {
		df2[,j] = df1[,i]
		j = j + 1
	}
}
#
# Ecriture du tableau sans colonnes de zeros transpose
# Writing transposed table without columns of zeroes
#
write.table(t(df2),"sor.txt",quote=FALSE,col.names = cnames,row.names = FALSE)