Re: "Traint" term can be as the fixed factor defautly?

Dear Luansheng,

I am not familiar with the frog data set.

'Trait' is defined in the ASReml guide (table 6.1 and 6.2) as an
internally defined factor idicating the traits
in a multivariate analysis.

You need to read up the !ASUV qualifier which allows you to fit alterative
R vriance structure to the standard multivariate one.

In this example, you have fitted Frog.Species.Temp
but Species and Temp just classify Frog so it is sufficient just to fit
Frog (with 18 levels)

The model therefore assumes common variance for 'Rest' and 'Exercise' and
'Frog' supplies the covariance.

So the alternative model has multivariate residual (although the data is
too small to show that the variances differ).

You should compare these models to make sure nyou understand them.

 !DOPART $1
Oxygen consumption of frogs
 Frog *
 Species * !I
 Temp * !A
 Rest !*100 # Resting oxygen consumption
 Exercise !*100 # Exercise oxygen consumption
frogs.txt !SKIP 1
!PART 2
  !ASUV # !MAXIT 100 !EXTRA 5
Rest Exercise ~ Trait Species*Temp*Trait !r Frog#.Species.Temp
0
!PART 1

Rest Exercise ~ Trait Species*Temp*Trait #!r Frog#.Species.Temp
1 2
0
2 0 US
.47 .33 .47


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Mixed model regression mapping for QTL detection in experimental crosses.
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luansheng <luansheng_at_GMAIL.COM>
Sent by: ASReml users discussion group <ASREML-L_at_DPI.NSW.GOV.AU>
17/11/2008 03:20 PM
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Subject
"Traint" term can be as the fixed factor defautly?






Dear all:
I am studying the frog Oxygen Consumption example from Dr. Stephen
D.Kachman's manual. I find that if you write the " Species*Temp*Trait " in
the model, then the "Trait" term can be automatically as fixed factor, but
in fact I can't find this defined factor in the data file. While "Rest
Exercise" are two variants, but in the model they can be transformed as on
dependent variant. Anyone can explain this for me? Thanks!


Luan sheng

Job file:
Oxygen consumption of frogs
 Frog *
 Species * !I
 Temp * !A
 Rest # Resting oxygen consumption
 Exercise # Exercise oxygen consumption
frogs.txt !SKIP 1 !ASUV # !MAXIT 100 !EXTRA 5
Rest Exercise ~ Trait Species*Temp*Trait !r Frog.Species.Temp
0 0 1
Frog.Species.Temp 1
0 0 I 1

Data file:
Subject Species Temperature Rest
Exercise
1 1 Low 0.107 0.152
2 1 Low 0.114 0.163
3 1 High 0.133 0.194
4 1 High 0.14 0.198
5 2 Low 0.098 0.144
6 2 Low 0.093 0.136
7 2 High 0.118 0.171
8 2 High 0.11 0.165
9 3 Low 0.126 0.182
10 3 Low 0.138 0.196
11 3 High 0.159 0.196
12 3 High 0.166 0.204
13 4 Low 0.154 0.207
14 4 Low 0.141 0.191
15 4 High 0.184 0.244
16 4 High 0.192 0.232

Asr file:
ASReml 2.00a [01 Jul 2006] Oxygen consumption of frogs
     Build: v [27 Feb 2007] 32 bit
 17 Nov 2008 11:42:22.328 32.00 Mbyte Windows frogs
 Licensed to: Yellow Sea Fisheries Research Institute Chinese Ac
 ***********************************************************
 * SYNTAX change: A/B now means A A.B *
 * *
 * Contact support_at_asreml.co.uk for licensing and support *
 ***************************************************** ARG *
 Folder: D:\luansheng\我的文档\学习资料区\育种分析软件教程\Asreml教程
\asreml
例子
  Species * !I
  Temp * !A
 QUALIFIERS: !SKIP 1 !ASUV
 Reading frogs.txt FREE FORMAT skipping 1 lines

 Bivariate analysis of Rest and Exercise

 Warning: The default action with missing values in multivariate data
          treated as univariate is to drop the missing values.
          You should instead include the mv model term if different
          residual variances are fitted.
 Using 16 records of 16 read

  Model term Size #miss #zero MinNon0 Mean
MaxNon0
   1 Frog 16 0 0 1 8.5000 16
   2 Species 4 0 0 1 2.5000 4
   3 Temp 2 0 0 1 1.5000 2
   4 Rest Variate 0 0 0.9300E-01 0.1358 0.1920

   5 Exercise Variate 0 0 0.1360 0.1859 0.2440

   6 Trait 2
   7 Species.Temp 8 2 Species : 4 3 Temp :
2
   8 Species.Trait 8 2 Species : 4 6 Trait :
2
   9 Temp.Trait 4 3 Temp : 2 6 Trait :
2
  10 Species.Temp.Trait 16 2 Species : 4 9 Temp.Trait :
4
  11 Frog.Species.Temp 128 1 Frog : 16 7 Species.Temp :
8
    128 identity 0.5000
 Structure for Frog.Species.Temp has 128 levels defined
 Forming 172 equations: 44 dense.
 Initial updates will be shrunk by factor 0.316
 Notice: 28 singularities detected in design matrix.
   1 LogL= 67.8027 S2= 0.27125E-04 16 df 1.000 0.5000
   2 LogL= 68.3496 S2= 0.21460E-04 16 df 1.000 0.8935
   3 LogL= 68.7240 S2= 0.17094E-04 16 df 1.000 1.500
   4 LogL= 68.8445 S2= 0.14448E-04 16 df 1.000 2.216
   5 LogL= 68.8465 S2= 0.14132E-04 16 df 1.000 2.338
   6 LogL= 68.8465 S2= 0.14125E-04 16 df 1.000 2.341
   7 LogL= 68.8465 S2= 0.14125E-04 16 df 1.000 2.341
 Final parameter values 1.0000 2.3407

 Source Model terms Gamma Component Comp/SE %
C
 Variance 32 16 1.00000 0.141250E-04 2.00 0
P

 Frog.Species.Temp identity 128 2.34071 0.330625E-04 1.62 0
U


 Analysis of Variance NumDF DenDF F_inc Prob
   6 Trait 2 10.0 5508.18 <.001
   2 Species 3 8.0 74.70 <.001
   3 Temp 1 8.0 83.84 <.001

   7 Species.Temp 3 8.0 1.89 0.210
   8 Species.Trait 3 8.0 0.91 0.480
   9 Temp.Trait 1 8.0 0.01 0.927
  10 Species.Temp.Trait 3 8.0 7.42 0.011
 Notice: The DenDF values are calculated ignoring fixed/boundary/singular
             variance parameters using algebraic derivatives.
  11 Frog.Species.Temp 128 effects fitted ( 112 are
zero)
 SLOPES FOR LOG(ABS(RES)) on LOG(PV) for Section 1
   2.24
 Finished: 17 Nov 2008 11:42:23.046 LogL Converged



Received on Sat Nov 20 2008 - 11:34:00 EST