Dear List members

I want to do the sliding window analysis of some specific values. Here is my code:

require(zoo)
dat <- read.table("chr1.txt", header = TRUE, sep="\t")
dat2 <- cbind(dat[1,3]) #The first column is also important. It represents the position of the site on the chromosome.
TS <- zoo(c(dat2))
a <- rollapply(TS, width=1000000, by=200000, FUN=mean, align="left") #The third column values should roll against the first column values. I might be wrong here with the code.
plot1 <- plot.default(a, col="red", type="l") #It returns me some errors for this command.

Error in plot.window(...) : need finite 'xlim' values
In addition: Warning messages:
1: In min(x) : no non-missing arguments to min; returning Inf
2: In max(x) : no non-missing arguments to max; returning -Inf
3: In min(x) : no non-missing arguments to min; returning Inf
4: In max(x) : no non-missing arguments to max; returning -Inf

Part of the original data looks like as follows:
pos    Fit    Fst    Fis
12794    0.928380160665041    -0.0877263098996843    0.934156378600823
12816    0.901040947621283    0.0382417096943425    0.897106109324759
12821    0.901040947621283    0.0382417096943425    0.897106109324759
12827    0.901040947621283    0.0382417096943425    0.897106109324759
12855    0.909446752933768    0.00347893012209298    0.909130624726955
13324    0.498125727088629    0.0975914515920549    0.443850267379679
13338    0.53827858671811    0.103194947279406    0.485148514851485
13339    -0.059306330783135    -0.0198369843236668    -0.038701622971286
13379    0.610641507226514    0.175889055559966    0.527541169789892
13381    0.144593428517224    -0.0343016958072985    0.172962226640159
13390    0.216526396327467    0.179801071155318    0.0447761194029849
13454    0.498125727088629    0.0975914515920549    0.443850267379679
13457    0.309860615307135    -0.0501399771889025    0.342812006319115
13462    0.536517915763086    -0.0302077737766018    0.550108147080029

That is, Fst against pos.

I am very willing to be educated concerning the mistakes I made for the code.

All the best
Li



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