A dimensionality-reduction genomic prediction method without direct inverse of the genomic relationship matrix for large genomic data
© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature..
KEY MESSAGE: A new genomic prediction method (RHPP) was developed via combining randomized Haseman-Elston regression (RHE-reg), PCR based on genomic information of core population, and preconditioned conjugate gradient (PCG) algorithm. Computational efficiency is becoming a hot issue in the practical application of genomic prediction due to the large number of data generated by the high-throughput genotyping technology. In this study, we developed a fast genomic prediction method RHPP via combining randomized Haseman-Elston regression (RHE-reg), PCR based on genomic information of core population, and preconditioned conjugate gradient (PCG) algorithm. The simulation results demonstrated similar prediction accuracy between RHPP and GBLUP, and significantly higher computational efficiency of the former with the increase of individuals. The results of real datasets of both bread wheat and loblolly pine demonstrated that RHPP had a similar or better predictive accuracy in most cases compared with GBLUP. In the future, RHPP may be an attractive choice for analyzing large-scale and high-dimensional data.
| Medienart: |
E-Artikel |
|---|
| Erscheinungsjahr: |
2023 |
|---|---|
| Erschienen: |
2023 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:42 |
|---|---|
| Enthalten in: |
Plant cell reports - 42(2023), 11 vom: 26. Nov., Seite 1825-1832 |
| Sprache: |
Englisch |
|---|
| Beteiligte Personen: |
Liu, Hailan [VerfasserIn] |
|---|
| Links: |
|---|
| Themen: |
GBLUP |
|---|
| Anmerkungen: |
Date Revised 09.10.2023 published: Print-Electronic Citation Status Publisher |
|---|
| doi: |
10.1007/s00299-023-03069-8 |
|---|
| funding: |
|
|---|---|
| Förderinstitution / Projekttitel: |
|
| PPN (Katalog-ID): |
NLM362472955 |
|---|
| LEADER | 01000naa a22002652 4500 | ||
|---|---|---|---|
| 001 | NLM362472955 | ||
| 003 | DE-627 | ||
| 005 | 20231226091321.0 | ||
| 007 | cr uuu---uuuuu | ||
| 008 | 231226s2023 xx |||||o 00| ||eng c | ||
| 024 | 7 | |a 10.1007/s00299-023-03069-8 |2 doi | |
| 028 | 5 | 2 | |a pubmed24n1208.xml |
| 035 | |a (DE-627)NLM362472955 | ||
| 035 | |a (NLM)37750948 | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
| 041 | |a eng | ||
| 100 | 1 | |a Liu, Hailan |e verfasserin |4 aut | |
| 245 | 1 | 2 | |a A dimensionality-reduction genomic prediction method without direct inverse of the genomic relationship matrix for large genomic data |
| 264 | 1 | |c 2023 | |
| 336 | |a Text |b txt |2 rdacontent | ||
| 337 | |a ƒaComputermedien |b c |2 rdamedia | ||
| 338 | |a ƒa Online-Ressource |b cr |2 rdacarrier | ||
| 500 | |a Date Revised 09.10.2023 | ||
| 500 | |a published: Print-Electronic | ||
| 500 | |a Citation Status Publisher | ||
| 520 | |a © 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature. | ||
| 520 | |a KEY MESSAGE: A new genomic prediction method (RHPP) was developed via combining randomized Haseman-Elston regression (RHE-reg), PCR based on genomic information of core population, and preconditioned conjugate gradient (PCG) algorithm. Computational efficiency is becoming a hot issue in the practical application of genomic prediction due to the large number of data generated by the high-throughput genotyping technology. In this study, we developed a fast genomic prediction method RHPP via combining randomized Haseman-Elston regression (RHE-reg), PCR based on genomic information of core population, and preconditioned conjugate gradient (PCG) algorithm. The simulation results demonstrated similar prediction accuracy between RHPP and GBLUP, and significantly higher computational efficiency of the former with the increase of individuals. The results of real datasets of both bread wheat and loblolly pine demonstrated that RHPP had a similar or better predictive accuracy in most cases compared with GBLUP. In the future, RHPP may be an attractive choice for analyzing large-scale and high-dimensional data | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a GBLUP | |
| 650 | 4 | |a Genomic prediction | |
| 650 | 4 | |a Preconditioned conjugate gradient algorithm | |
| 650 | 4 | |a Principal component regression | |
| 650 | 4 | |a Randomized Haseman–Elston regression | |
| 700 | 1 | |a Yu, Shizhou |e verfasserin |4 aut | |
| 773 | 0 | 8 | |i Enthalten in |t Plant cell reports |d 1981 |g 42(2023), 11 vom: 26. Nov., Seite 1825-1832 |w (DE-627)NLM098163868 |x 1432-203X |7 nnns |
| 773 | 1 | 8 | |g volume:42 |g year:2023 |g number:11 |g day:26 |g month:11 |g pages:1825-1832 |
| 856 | 4 | 0 | |u http://dx.doi.org/10.1007/s00299-023-03069-8 |3 Volltext |
| 912 | |a GBV_USEFLAG_A | ||
| 912 | |a GBV_NLM | ||
| 951 | |a AR | ||
| 952 | |d 42 |j 2023 |e 11 |b 26 |c 11 |h 1825-1832 | ||