Whats New in Release 3
These notes relating to ASReml 3 are intended
for those familiar with ASReml 2 and describe
additions to the syntax. New users should read the
ASReml User Guide
which provides a comprehensive
to fitting mixed models in ASReml.
An ASReml Forum is hosted by VSN. Users are urged to join the forum
and participate in the discussion among ASReml users.
Critical Changes to Behaviour
Generally we seek to maintain upward compatability so that ASReml 1 code
will continue to run. However, to deliver improved facilities,
some changes to behaviour are unavoidable.
allows a string to be defined early in the job, and
substituted in repeated further down.
Expanded testing of fixed effects.
The table of Wald F statistics has been expanded to
allow the user to specify the exact conditional
to be tested.
Factor definition: !AS declaration
Diallel experiments are common in some species. The usual way
of fitting these in ASReml is to declare the two parents in two factors
say Male and Female, and to fit the general combining effect
in the model as Male and(Female) so that the design matrix for
Female is overlaid on (or added to) the design matrix for Male.
This requires that the two factors be coded conformable so that the
ith 'male' is the same individual as the ith female.
If they are not directly coded that way, a pedigree file can be used,
but the new !AS qualifier is more convenient. It is used as
in the following example:
Female !AS Male
works internally by using a common list of factor level labels
the two factors.
Paths and loops in the .as file
!CYCLE statement has been modified and extended.
It can operated in association with PARTs. It no longer
needs !JOIN and it expands a integer sequence like 1:100.
The !D transformation conditionally discards records depending on the value
of its argument and the value in the test field. \rev It drops
the record if the test generates TRUE or the the test field
is missing. A new form !DV has been implemented which
does not drop the the record when the test field is missing
unless the test value is *. That is !D >99 is
equivalent to !DV * !DV >99.
!DV * to discard records with a missing value in the test field,
!DV v to discard records with a v in the test field,
!DV<v to discard records when the test field has a value <v,
!DV<=v to discard records when the test field has a value <= v,
!DV<>v to discard records when the test field has a value not equal to v,
!DV>=v to discard records when the test field has a value >= v,
!DV>v to discard records when the test field has a value >v.
Setting the TARGET field
A previous ambiguity with setting the TARGET field has been resolved
with the introduction of an explicit
The !NA v transformation has been extended to allow v
to refer to another field instead of just being a value.
This facilitates copying a value from another field when the current field
has a missing value.
e.g. WT1 WT2 WT !=WT2 !NA WT1 defines WT with values of
WT2, or WT1 if WT2 is missing.
Pedigree and GIV files
Pedigree file line qualifiers
requests an inverse NRM based on the X chromosome
be formed along with the usual additive inverse NRM.
requests formation of the additive inverse NRM assuming specified levels of
An alternative to group constraints
described above is to shrink the group effects by adding the constant o
to the diagonal elements of A-1 pertaining to groups.
When a constant is added, no adjustment of the degrees of freedom is made for
Use !Goffset -1 to suppress adding of constraints
where empty groups appear. The empty groups are then
not counted in the DF adjustment.
There is also extended information on constraints applied to
GIV file qualifiers.
has been added to associate fixed degrees of freedom to the GIV matrix.
The GIV and GRM matrices may be read in in a DENSE form as well as the
previous sparse form. ASReml can now handle singular GRM matrices.
Combining columns from separate files
is a replacement to the former
Datafile line qualifiers
qualifier has been added to facilitate setting path to the folder
containing data files.
Factor level combination.
!GROUP and !FAMILY
qualifers allows formation of a new factor defined by grouping
levels of an existing data factor. The !FAMILY
qualifier takes the redefinition from a file.
Holding variance components fixed.
qualifier can be used to stop ASReml updating certain variance parameters
in a temporary manner.
My Basis Function
directive has several new options
which facilitate its use to read in QTL marker data.
Linear Model Specification
More than 20 dependent variables
The dependent variable can now be a set of variables
grouped by the !G factor definition qualifier.
Trait dependent covariates
model term has been added to allow traits specific covariates
to be fitted for !G grouped variables.
Generalized Linear Models
allows the fitting of multiple threshold categorical trait
Direct sum variance structures
facilitates the definition of a direct sum variance model for example
a series of independent time series with common variance and
Constraining variance parameters.
The manner of setting constraints under the
qualifier has been extended so as to make it easier to specify
a large number of simple constraints.
Factor Analytic updates.
The updates of loadings in factor analytic models has been
revised in association with the
in an attempt to make it easier to get convergence.
The format of the predict header has been modified in an attempt
to make it easier to understand.
Several users have had difficulty getting sensible predictions when they have
large factors which have a hierachical or nested, treelike
association among the levels, for example 1000 genetic lines in 30 families.
facilitates defining these relationships for the PREDICT
statement and for multilevel nesting, averaging
in various ways.
Calculating derived Variance parameters.
The .pin file postprocessing option has
been linked into the main .as file processing with the
A new procedure has been implemented for examining the size
of random effects, including the residuals. It is invoked by the
A new file type has been added when residuals are saved to a binary file.
The .vll file holds level labels so that this information
can be assiciated with the factor variables in the binary file
if the data is read back for further processing.
invokes an iterative process of fitting a large
model by cycling between two simpler submodels.
invokes an experimental method of fitting singlar variance
matrices through a Cholesky factorization.
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