Slots
Objects of class IBDsegmentList
have the following slots:
IBDsegments
:- List of IBD segments.
lengthList
:- Number of IBD segments in the list.
statistics
:- Statistics of IBD segments like
average length, average number of individuals belonging to
an IBD segment, average number of tagSNVs of an IBD segment, etc.
Constructor
Constructor of class IBDsegmentList. IBDsegmentList(IBDsegments=list(),lengthList=0,statistics=list())
Accessors
In the following x
denotes an IBDsegmentList object. -
IBDsegments(x)
, IBDsegments(x) <- value
:
Returns or sets IBDsegments
, where the return value and
value
are both a list.
-
lengthList(x)
, lengthList(x) <- value
:
Returns or sets lengthList
, where the return value and
value
are both a number.
-
statistics(x)
, statistics(x) <- value
:
Returns or sets statistics
, where the return value and
value
are both a list.
-
x[[i]]
, x[[i]] <- value
:
Returns or sets an entry in the list x
,
where the return value and
value
are both an instance of the class IBDsegment
.
-
x[i]
, x[i] <- value
:
Returns or sets a sublist of the list x
,
where the return value and
value
are both an instance of the class IBDsegmentList
.
Signatures
- plot
signature(x = "IBDsegmentList", y = "missing")
Plotting all IBD segments of the list using an interactive command. - summary
signature(object = "IBDsegmentList")
Summary
of a list of IBD segments, where the number of clusters and a
statistics are given.
Functions that return objects of this class
IBDsegmentList objects are returned by fabia
, fabias
, fabiap
,
fabiasp
, mfsc
, nmfsc
,
nmfdiv
, and nmfeu
.Extension to store results of other methods
The class IBDsegmentList
may contain the result of different matrix factorization
methods. The methods may be generative or not. Methods my be "singular value decomposition" (M contains singular values
as well as avini, L and Z are orthonormal matrices),
"independent component analysis" (Z contains the projection/sources, L is the
mixing matrix, M is unity), "factor analysis" (Z contains factors, L the loadings,
M is unity, U the noise, Psi the noise covariance, lapla is a
variational parameter for non-Gaussian factors, avini and ini are the
information the factors convey about the observations).