DrK-Lo
commented
1 year ago Hi Jay,
The "NumberOfSamples" in this case it should be 2 because you have 2 populations, but that doesn't effect He. The number of unique He values in principle is determined by the number of individuals in your dataset.
From: jayyeam @.> Sent: 11 April 2023 12:33 To: whitlock/OutFLANK @.> Cc: Subscribed @.***> Subject: [whitlock/OutFLANK] Weird binning in Heterozygosity values (Issue #33)
Hello!
I am working on a dataset that has 70 samples and ~540,000 snps grouped into two different populations. I was working through the tutorial and created a plot looking at outlier$results$FST and outlier$results$He. However, of my 540,000 snps, I only find 131 unique He values. I have followed the tutorial precisely, and haven't made any adjustments, so I am curious whether this is something to be expected. Here is the code:
outlier <- OutFLANK(FstDataFrame,NumberOfSamples = 70, RightTrimFraction = 0.06, LeftTrimFraction = 0.35, qthreshold = 0.05, Hmin = 0.1) OutFLANKResultsPlotter(outlier, withOutliers = TRUE, NoCorr = TRUE, Hmin = 0.1, binwidth = 0.005, Zoom = FALSE, RightZoomFraction = 0.05, titletext = NULL)
plot(outlier$results$He, outlier$results$FST, pch=20, col="grey") points(outlier$results$He[outlier$results$qvalues<0.01], y = outlier$results$FST[outlier$results$qvalues<0.01], pch=21, col="blue")
heterozygosityplot.pdfhttps://github.com/whitlock/OutFLANK/files/11202745/heterozygosityplot.pdf
I have also created a manhattan plot using the qvalues from OutFLANK, and it appears normal. So I am hoping to get some insights as to why the Heterozygosity looks so strange. manhattan_qvalues_outflank.pdfhttps://github.com/whitlock/OutFLANK/files/11202790/manhattan_qvalues_outflank.pdf
Thank you! Jay
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Hello!
I am working on a dataset that has 70 samples and ~540,000 snps grouped into two different populations. I was working through the tutorial and created a plot looking at outlier$results$FST and outlier$results$He. However, of my 540,000 snps, I only find 131 unique He values. I have followed the tutorial precisely, and haven't made any adjustments, so I am curious whether this is something to be expected. Here is the code:
outlier <- OutFLANK(FstDataFrame,NumberOfSamples = 70, RightTrimFraction = 0.06, LeftTrimFraction = 0.35, qthreshold = 0.05, Hmin = 0.1) OutFLANKResultsPlotter(outlier, withOutliers = TRUE, NoCorr = TRUE, Hmin = 0.1, binwidth = 0.005, Zoom = FALSE, RightZoomFraction = 0.05, titletext = NULL)
plot(outlier$results$He, outlier$results$FST, pch=20, col="grey") points(outlier$results$He[outlier$results$qvalues<0.01], y = outlier$results$FST[outlier$results$qvalues<0.01], pch=21, [col="blue")]
I have also created a manhattan plot using the qvalues from OutFLANK, and it appears normal. So I am hoping to get some insights as to why the Heterozygosity looks so strange.
Thank you! Jay