questions about results

[HuiqinYi]

Dear Micheal and Katie,
I am trying to run OutFlank on my SNP dataset. There is no error messages during the run, but I don't get any outlier from my results.Here is my script and attached is my SNP dataset and plot.
`> library(OutFLANK)

o <- read.table("SNP.txt")
dim(o)
[1] 23085 134
o <- t(o)
dim(o)
[1] 134 23085
p <- read.csv("pop.csv")
head(p)
X pop
1 1 GXHZ01
2 2 GXHZ01
3 3 GXHZ01
4 4 GXHZ01
5 5 GXHZ01
6 6 GXHZ01
out <- MakeDiploidFSTMat(SNPmat = o,locusNames = seq(1,23085,by=1),popNames = p$pop)
Calculating FSTs, may take a few minutes...
[1] "10000 done of 23085"
[1] "20000 done of 23085"
OF_out <- OutFLANK(FstDataFrame = out,LeftTrimFraction = 0.05,RightTrimFraction = 0.05,Hmin = 0.1,NumberOfSamples = 14,qthreshold = 0.01)
ERROR: The largest FST in the trimmed set must be < 1. Please use a larger RightTrimFraction.
OF_out <- OutFLANK(FstDataFrame = out,LeftTrimFraction = 0.05,RightTrimFraction = 0.2,Hmin = 0.1,NumberOfSamples = 14,qthreshold = 0.01)
OutFLANKResultsPlotter(OF_out,withOutliers = T,NoCorr = T,Hmin = 0.1,binwidth = 0.005,titletext = "outliers")
outliers <- which(OF_out$results$OutlierFlag=="TURE")
print(outliers)
integer(0)
`
From the FST calculated by the program, there are a lot of 1, I wonder if OutFlank does not suit for highly differentiated populations. Or probably there are anything wrong with my script or data preparation, but I can not figure out what it is. I will be really thankful if you could help me with my problem.
Hope to get your reply in your advance.
Huiqin Yih
SNP.txt
Uploading pop.txt…
Uploading Rplot01.pdf…

[HuiqinYi]

pop.txt
Rplot01.pdf

[abcosta]

Hi,

Did you receive an answer for your question?
I'm having exactly the same problem. My results are quite similar and I'm comparing data sets that are potentially different species.
Thus, I am also wondering if there is something wrong with my data or if it means there is no outliers.

[DrK-Lo]

Hello, OutFLANK assumes that the FST data are chi-squared distributed. It appears from looking at your FST plot that the data are not chi-squared distributed. Sometimes when studying closely related species there may be admixture, and OutFLANK has been shown to have low performance in this scenario (see https://doi.org/10.1111/1755-0998.12592 <https://doi.org/10.1111/1755-0998.12592>).