timothyfrasier
commented
5 years ago Hi Matthias:
Sorry about this, I didn’t explain this correctly in the tutorial.
related will always calculate the moment-based inbreeding coefficients, regardless of whether or not you set allow.inbreeding to TRUE. Setting this to TRUE is only needed if you are using the likelihood-based relatedness estimators, and are therefore accounting for inbreeding in the relatedness estimators. There is an error in the manual, in that none of the moment-based estimators can account for inbreeding, whereas I suggest that the Ritland and Lynch & Ritland methods can. It is only the two likelihood-based estimators that can account for inbreeding. I need to fix this soon…
Thus, if you are estimating relatedness using a moment-based estimator, and also want inbreeding coefficients, you do not need to set allow.inbreeding to TRUE. You will still get an inbreeding output file that will have two columns representing two different inbreeding estimates. The columns will be labeled LH and LR. These correspond to the inbreeding coefficients estimated using the Li & Horvitz (1953) method, as modified by Ritland (1996); and the method described in Lynch & Ritland (1999). Again, these will be estimated (and this file will be created) regardless of which moment-based relatedness estimator you are using.
The L2 and L3 columns correspond to the inbreeding coefficients associated with the diadml and trioml estimators, respectively.
Again, I apologize for the confusion. Please let me know if you have any other questions.
Sincerely, Tim Frasier
Li CC, Horvitz DG (1953) Some methods of estimating the inbreeding coefficient. American Journal of Human Genetics, 5, 107–117. Lynch M, Ritland K (1999) Estimation of pairwise relatedness with molecular markers. Genetics, 152, 1753–1766. Ritland K (1996) Estimators for pairwise relatedness and inbreeding coef- ficients. Genetical Research, 67, 175–186.
Timothy R. Frasier Coordinator - Forensic Sciences Program Associate Professor - Department of Biology Saint Mary's University 923 Robie Street Halifax, NS B3H 3C3, Canada Email: timothy.frasier@smu.camailto:timothy.frasier@smu.ca Tel: (902) 491-6382 www.frasierlab.cahttp://frasierlab.ca
On Dec 10, 2018, at 3:33 AM, Matthias Loretto notifications@github.com<mailto:notifications@github.com> wrote:
Hi Timothy, I have a question concerning the inbreeding estimates in your package. if I set "allow.inbreeding=T" in the coancestry function, only inbreeding estimates for two methods are calculated: LH, LR - probably lynchrd and ritland, but not the likelihood methods? With your example data (code below) some inbreeding estimates of LH are very high (max 1.89) with my own data even up to a value of 6. Any idea how to get the inbreeding values for the likelihood methods and why some of these values are so high?
thanks, Matthias
input <- readgenotypedata("GenotypeData.txt") output_inbred2 <- coancestry(input$gdata, trioml=1, lynchli=1, lynchrd=1, quellergt=1, ritland=1, wang=1, dyadml=1, allow.inbreeding = T) str(output_inbred2$inbreeding) summary(output_inbred2$inbreeding$LH)
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mcLoretto
duanedief
fabiomarroni
Mabel-Agy
Hi Timothy, I have a question concerning the inbreeding estimates in your package. if I set "allow.inbreeding=T" in the coancestry function, only inbreeding estimates for two methods are calculated: LH, LR - probably lynchrd and ritland, but not the likelihood methods? With your example data (code below) some inbreeding estimates of LH are very high (max 1.89) with my own data even up to a value of 6. Any idea how to get the inbreeding values for the likelihood methods and why some of these values are so high?
thanks, Matthias
input <- readgenotypedata("GenotypeData.txt") output_inbred2 <- coancestry(input$gdata, trioml=1, lynchli=1, lynchrd=1, quellergt=1, ritland=1, wang=1, dyadml=1, allow.inbreeding = T) str(output_inbred2$inbreeding) summary(output_inbred2$inbreeding$LH)