cr3pts {onemap} | R Documentation |
An interface between R and the C routine that performs the three-point analysis. Given the type of segregation of the three markers, this function creates the corresponding vectors and matrices that are necessary to the C routine and makes a call to it.
cr3pts(mrk1, mrk2, mrk3, segr.type1, segr.type2, segr.type3)
mrk1 |
a vector containing the genotypes of all individuals for the first marker. |
mrk2 |
a vector containing the genotypes for the second marker. |
mrk3 |
a vector containing the genotypes for the third marker. |
segr.type1 |
the type of segregation of the first marker
(mrk1 ). |
segr.type2 |
the type of segregation of the second marker
(mrk2 ). |
segr.type3 |
the type of segregation of the third marker
(mrk3 ). |
Returns a list with the following components:
theta12 |
a vector with the maximum likelihood estimates (MLEs)
of the recombination fraction between markers 1 and 2
(mrk1 and mrk2 , respectively), under the 16
possible assignments. |
theta23 |
a vector with the MLEs of the recombination fraction
between markers 2 and 3 (mrk2 and mrk3 ,
respectively), under the 16 assignments. |
theta13 |
a vector with the MLEs of the recombination fraction
between markers 1 and 3 (mrk1 and mrk3 ,
respectively), under the 16 assignments. |
like |
a vector with the likelihood of the data under each of the
16 assignments. |
posterior |
a vector with the posterior probability of each of
the 16 assignments. |
LOD |
a vector with the LOD Score for the 16 assignments -
the base 10 logarithm of the ratio of the maximum likelihood and the
likelihood under the null hypothesis of no linkage. |
Gabriel R A Margarido, gramarga@esalq.usp.br
Wu, R., Ma, C.-X., Painter, I. and Zeng, Z.-B. (2002) Simultaneous maximum likelihood estimation of linkage and linkage phases in outcrossing species. Theoretical Population Biology 61: 349-363.
est.rf.3pts
; for details concerning the types of
segregation, see mrktype
.
data(example_out) # getting values marker1 <- example_out$geno[,1] marker2 <- example_out$geno[,2] marker3 <- example_out$geno[,14] segr.type1 <- example_out$segr.type[1] segr.type2 <- example_out$segr.type[2] segr.type3 <- example_out$segr.type[14] # three-point analysis cr3pts(marker1,marker2,marker3,segr.type1,segr.type2,segr.type3)