1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
|
######################################################################
#
# est.map.R
#
# copyright (c) 2001-8, Karl W Broman
# last modified Jan, 2008
# first written Apr, 2001
# Licensed under the GNU General Public License version 2 (June, 1991)
#
# Part of the R/qtl package
# Contains: est.map
#
######################################################################
######################################################################
#
# est.map: re-estimate the genetic map for an experimental cross
#
######################################################################
est.map <-
function(cross, error.prob=0.0001, map.function=c("haldane","kosambi","c-f","morgan"),
m=0, p=0, maxit=10000, tol=1e-6, sex.sp=TRUE, verbose=FALSE,
omit.noninformative=TRUE)
{
if(!any(class(cross) == "cross"))
stop("Input should have class \"cross\".")
type <- class(cross)[1]
if(m < 0 || p < 0 || p > 1)
stop("Must have m >=0 and 0 <= p <= 1")
if(m > 0 && p < 1 && type != "bc" && type != "f2") {
warning("m and p currently used only for backcrosses and intercrosses.")
m <- p <- 0
}
if(m > 0 && p < 1 && !missing(map.function))
warning("Map function not used with interference model.")
if(m > 0 && p < 1) interf.model <- TRUE
else interf.model <- FALSE
# map function
map.function <- match.arg(map.function)
if(map.function=="kosambi") {
mf <- mf.k; imf <- imf.k
}
else if(map.function=="c-f") {
mf <- mf.cf; imf <- imf.cf
}
else if(map.function=="morgan") {
mf <- mf.m; imf <- imf.m
}
else {
mf <- mf.h; imf <- imf.h
}
# don't let error.prob be exactly zero (or >1)
if(error.prob < 1e-50) error.prob <- 1e-50
if(error.prob > 1) {
error.prob <- 1-1e-50
warning("error.prob shouldn't be > 1!")
}
n.ind <- nind(cross)
n.mar <- nmar(cross)
n.chr <- nchr(cross)
newmap <- vector("list",n.chr)
names(newmap) <- names(cross$geno)
chrtype <- sapply(cross$geno, class)
# calculate genotype probabilities one chromosome at a time
for(i in 1:n.chr) {
if(n.mar[i] < 2) {
newmap[[i]] <- cross$geno[[i]]$map
next
}
# which type of cross is this?
if(type == "f2") {
one.map <- TRUE
if(chrtype[i] == "A") # autosomal
cfunc <- "est_map_f2"
else # X chromsome
cfunc <- "est_map_bc"
}
else if(type == "bc" || type=="riself" || type=="risib") {
one.map <- TRUE
cfunc <- "est_map_bc"
}
else if(type == "4way") {
one.map <- FALSE
cfunc <- "est_map_4way"
}
else
stop("est.map not available for cross type ", type, ".")
# genotype data
gen <- cross$geno[[i]]$data
gen[is.na(gen)] <- 0
# remove individuals that have less than two typed markers
if(omit.noninformative) {
o <- apply(gen,1,function(a) sum(a!=0)>1)
gen <- gen[o,,drop=FALSE]
}
# recombination fractions
if(one.map) {
# recombination fractions
rf <- mf(diff(cross$geno[[i]]$map))
if(type=="risib" || type=="riself")
rf <- adjust.rf.ri(rf,substr(type,3,nchar(type)),chrtype[i])
rf[rf < 1e-14] <- 1e-14
}
else {
# randomize the maps a bit
orig <- cross$geno[[i]]$map
cross$geno[[i]]$map <- cross$geno[[i]]$map +
runif(length(cross$geno[[i]]$map), -0.2, 0.2)
rf <- mf(diff(cross$geno[[i]]$map[1,]))
rf[rf < 1e-14] <- 1e-14
rf2 <- mf(diff(cross$geno[[i]]$map[2,]))
rf2[rf2 < 1e-14] <- 1e-14
if(!sex.sp && chrtype[i]=="X")
temp.sex.sp <- TRUE
else temp.sex.sp <- sex.sp
}
if(interf.model)
d <- diff(cross$geno[[i]]$map)
if(verbose) cat(paste("Chr ", names(cross$geno)[i], ":\n",sep=""))
# call the C function
if(one.map && !interf.model) {
z <- .C(cfunc,
as.integer(nrow(gen)), # number of individuals
as.integer(n.mar[i]), # number of markers
as.integer(gen), # genotype data
rf=as.double(rf), # recombination fractions
as.double(error.prob),
loglik=as.double(0), # log likelihood
as.integer(maxit),
as.double(tol),
as.integer(verbose),
PACKAGE="qtl")
if(type=="riself" || type=="risib")
z$rf <- adjust.rf.ri(z$rf, substr(type, 3, nchar(type)),
chrtype[i], expand=FALSE)
newmap[[i]] <- cumsum(c(min(cross$geno[[i]]$map),imf(z$rf)))
names(newmap[[i]]) <- names(cross$geno[[i]]$map)
attr(newmap[[i]],"loglik") <- z$loglik
}
else if(interf.model) { # Chi-square / Stahl model
if(type=="bc" || (type=="f2" && chrtype[i]=="X")) {
z <- .C("R_est_map_bci",
as.integer(nrow(gen)), # number of individuals
as.integer(n.mar[i]), # number of markers
as.integer(gen), # genotype data
d=as.double(d), # cM distances
as.integer(m),
as.double(p),
as.double(error.prob),
loglik=as.double(0), # log likelihood
as.integer(maxit),
as.double(tol),
as.integer(verbose),
PACKAGE="qtl")
} else {
z <- .C("R_est_map_f2i",
as.integer(nrow(gen)), # number of individuals
as.integer(n.mar[i]), # number of markers
as.integer(gen), # genotype data
d=as.double(d), # cM distances
as.integer(m),
as.double(p),
as.double(error.prob),
loglik=as.double(0), # log likelihood
as.integer(maxit),
as.double(tol),
as.integer(verbose),
PACKAGE="qtl")
}
newmap[[i]] <- cumsum(c(min(cross$geno[[i]]$map),z$d))
names(newmap[[i]]) <- names(cross$geno[[i]]$map)
attr(newmap[[i]], "loglik") <- z$loglik
attr(newmap[[i]], "m") <- m
attr(newmap[[i]], "p") <- p
}
else {
z <- .C(cfunc,
as.integer(nrow(gen)), # number of individuals
as.integer(n.mar[i]), # number of markers
as.integer(gen), # genotype data
rf=as.double(rf), # recombination fractions
rf2=as.double(rf2), # recombination fractions
as.double(error.prob),
loglik=as.double(0), # log likelihood
as.integer(maxit),
as.double(tol),
as.integer(temp.sex.sp),
as.integer(verbose),
PACKAGE="qtl")
if(!temp.sex.sp) z$rf2 <- z$rf
newmap[[i]] <- rbind(cumsum(c(min(orig[1,]),imf(z$rf))),
cumsum(c(min(orig[2,]),imf(z$rf2))))
dimnames(newmap[[i]]) <- dimnames(cross$geno[[i]]$map)
attr(newmap[[i]],"loglik") <- z$loglik
}
} # end loop over chromosomes
class(newmap) <- "map"
newmap
}
# end of est.map.R
|
