This preprint is under consideration at Soft Computing. A preprint is a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Learn more about In Review
A new preprint design is coming!
We have improved readability, clarity, accessibility, and opportunities for engagement.
Research Article
Ozge Karadag Atas
Hacettepe University: Hacettepe Universitesi
Corresponding Author
ORCiD: https://orcid.org/0000-0002-2650-1458
License:
This work is licensed under a CC BY 4.0 License. Read Full License
In this paper a multivariate heterogeneous variance components model is developed, which allows for determining location specific variance components in the analysis of multiple related traits. In addition to spatial heterogeneity, genetic similarities are also considered by assigning genetic variance components. The performance of the developed model is evaluated through an extensive simulation study and comparison of models are conducted by heritability estimations. Simulation study reveals that the developed method can well control the locational heterogeneity and under the developed model the heritability estimations are close to desired proportions. A real plant breeding data set is used for illustration.
Keywords
multivariate variance components, mixed modelling, genetic variance components, location effect, heritability
Figure 1
Figure 2
The full text of this article is available to read as a PDF.
Loading...
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
Peer Review Timeline
CURRENT STATUS: Under Review
Version 1
Posted 07 May, 2021
No community comments so far
Reviews received
Received 30 Apr, 2021
Reviewers invited
Invitations sent on 30 Apr, 2021
Editor assigned
On 14 Feb, 2021
First submitted
On 14 Feb, 2021
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
Subject Areas
Theoretical Computer Science
Learn more about our company.
A new preprint design is coming!
We have improved readability, clarity, accessibility, and opportunities for engagement.
This preprint is under consideration at Soft Computing. A preprint is a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Learn more about In Review
Research Article
Ozge Karadag Atas
Hacettepe University: Hacettepe Universitesi
Corresponding Author
ORCiD: https://orcid.org/0000-0002-2650-1458
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
Peer Review Timeline
CURRENT STATUS: Under Review
Version 1
Posted 07 May, 2021
No community comments so far
Reviews received
Received 30 Apr, 2021
Reviewers invited
Invitations sent on 30 Apr, 2021
Editor assigned
On 14 Feb, 2021
First submitted
On 14 Feb, 2021
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
Subject Areas
Theoretical Computer Science
License:
This work is licensed under a CC BY 4.0 License. Read Full License
In this paper a multivariate heterogeneous variance components model is developed, which allows for determining location specific variance components in the analysis of multiple related traits. In addition to spatial heterogeneity, genetic similarities are also considered by assigning genetic variance components. The performance of the developed model is evaluated through an extensive simulation study and comparison of models are conducted by heritability estimations. Simulation study reveals that the developed method can well control the locational heterogeneity and under the developed model the heritability estimations are close to desired proportions. A real plant breeding data set is used for illustration.
Figure 1
Figure 2
The full text of this article is available to read as a PDF.
Loading...