ASMap是一个对测序或者芯片数据进行分析及遗传作图的软件,程序包见附件,含程序包,软件说明书及测试数据,可在安装程序包栏在线获取。
mstmap.data.frame(object, pop.type = "DH", dist.fun = "kosambi",
objective.fun = "COUNT", p.value = 1e-06, noMap.dist = 15, noMap.size = 0,
miss.thresh = 1, mvest.bc = FALSE, detectBadData = FALSE, as.cross = TRUE,
return.imputed = TRUE, trace = FALSE, ...)
It must have markers in rows and
genotypes in columns. Marker names are required to be in the rownames component of
the object with genotype names residing in the names. Spaces in any of the marker or
genotype names should be avoided but will be replaced with a “-” if found. Each of the
columns of the data frame must be of class "character" (not factors). If converting from
a matrix, this can easily be achieved by using the stringAsFactors = FALSE argument
for any data.frame method.
The available populations that can be passed to pop.type are "BC" Backcross, "DH"
Doubled Haploid, "ARIL" Advanced Recombinant Inbred and "RILn" Recombinant Inbred
with n levels of selfing. The allelic content of the markers in the object must be explicitly
adhered to. For pop.type "BC", "DH" or "ARIL" the two allele types should be represented
as ("A" or "a") and ("B" or "b"). Thus for pop.type = "ARIL" it is assumed the minimal
number of heterozygotes have been set to missing. For non-advanced RIL populations
(pop.type = "RILn") phase unknown heterozygotes should be represented as "X". For
all populations, missing marker scores should be represented as ("U" or "-").
mstmap.cross(object, chr, id = "Genotype", bychr = TRUE, suffix =
"numeric", anchor = FALSE, dist.fun = "kosambi", objective.fun = "COUNT",
p.value = 1e-06, noMap.dist = 15, noMap.size = 0, miss.thresh = 1,
mvest.bc = FALSE, detectBadData = FALSE, return.imputed = FALSE, trace =
FALSE, ...)
The cross object needs to inherit from one of the allowable classes available in the
R/qtl package, namely "bc","dh","riself","bcsft" where "bc" is a Backcross "dh"
is Doubled Haploid, "riself" is an advanced Recombinant Inbred and "bcsft" is a
Backcross/Self。
使用测试数据的时候就是不知道怎么输入,数据转换为csv文件,可以使用下面的方法读入,但是也许这个
语句有问题,写mstmap.data.frame;mstmap.cross的时候出错。
object <-read.table("datasample.csv",header=T,sep=",",stringsAsFactors=FALSE,row.names = "X")