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9,641 to 9,650 of 12,512 Results

Discovery of variants in the parental lines grown in the hybrid crossing block using genotyping-by-sequencing Oct 3, 2018 - International Wheat Yield Partnership Research Data Baenziger, Stephen; Belamkar, Vikas, 2018, "Discovery of variants in the parental lines grown in the hybrid crossing block using genotyping-by-sequencing", https://hdl.handle.net/11529/10548065, CIMMYT Research Data & Software Repository Network, V1 Genotyping-by-sequencing (GBS) data, variant calls and Single Nucleotide Polymorphism (SNP) calls of parental lines grown in the hybrid crossing block in 2017.
GBS_KeyFile_v2.7z Oct 3, 2018 - Discovery of variants in the parental lines grown in the hybrid crossing block using genotyping-by-sequencing 7Z Archive - 139.0 KB - MD5: 0fd71d41f9dd50bbf4bfc7420aa3ecc4 Key file associated with the FASTQ files. To request access to this file or any information related to it, please contact the IWYP Data Coordintor or Stephen Baezinger (pstephen.baenziger@gmail.com).
HCB17_SNPs_Unfiltered.recode.vcf Oct 3, 2018 - Discovery of variants in the parental lines grown in the hybrid crossing block using genotyping-by-sequencing Virtual Contact File - 734.8 MB - MD5: 8333b52c7e4d0f2ff4236e238f756203 SNP Calls. To request access to this file or any information related to it, please contact the IWYP Data Coordintor or Stephen Baezinger (pstephen.baenziger@gmail.com).
HCB17_Variants_Unfiltered.recode.vcf Oct 3, 2018 - Discovery of variants in the parental lines grown in the hybrid crossing block using genotyping-by-sequencing Virtual Contact File - 751.9 MB - MD5: 502d9643d0f4ff83ecf612312489aca5 Variant Calls. To request access to this file or any information related to it, please contact the IWYP Data Coordintor or Stephen Baezinger (pstephen.baenziger@gmail.com).
Links to FASTQ files.txt Oct 3, 2018 - Discovery of variants in the parental lines grown in the hybrid crossing block using genotyping-by-sequencing Plain Text - 521 B - MD5: 74188e20b9df5cd003b57c59f6be3d41 Temporary links to three FASTQ files with GBS data for the parental samples, stored in the University of Nebraska-Lincoln Box. To request access to these links, please contact the IWYP Data Coordinator or send a request email directly to Stephen Baenziger (pstephen.baenziger@gmai...
Supplemental data for multi-trait, multi-environment deep learning modeling for genomic-enabled prediction of plant traits Sep 28, 2018 - CIMMYT Research Data Montesinos-López, Osval A.; Montesinos-López, Abelardo; Crossa, Jose; Gianola, Daniel; Hernández-Suarez, Carlos Moisés; Martín-Vallejo, Javier, 2018, "Supplemental data for multi-trait, multi-environment deep learning modeling for genomic-enabled prediction of plant traits", https://hdl.handle.net/11529/10548134, CIMMYT Research Data & Software Repository Network, V1 This study provides supplemental data to support an investigation of the power of multi-trait deep learning (MTDL) models in terms of genomic-enabled prediction accuracy.
DataSets_Multi_trait.rar Sep 28, 2018 - Supplemental data for multi-trait, multi-environment deep learning modeling for genomic-enabled prediction of plant traits RAR Archive - 41.9 MB - MD5: cdd5ff94aff34916a943fe27c4bb20a6 Supporting data
Supplemental data for hybrid wheat prediction using genomic, pedigree and environmental covariables interaction models Sep 21, 2018 - CIMMYT Research Data Basnet, Bhoja Raj; Crossa, Jose; Pérez-Rodríguez, Paulino; Manes, Yann; Singh, Ravi; Rosyara, Umesh; Camarillo-Castillo, Fatima; Murua, Mercedes, 2018, "Supplemental data for hybrid wheat prediction using genomic, pedigree and environmental covariables interaction models", https://hdl.handle.net/11529/10548129, CIMMYT Research Data & Software Repository Network, V1 Genomic prediction of hybrids unobserved in field evaluations is crucial. In this study, we used genomic G×E models for hybrid prediction, where similarity between lines was assessed by pedigree and molecular markers, and similarity between environments was accounted for by envir...
Supplemental_files.zip.gz Sep 21, 2018 - Supplemental data for hybrid wheat prediction using genomic, pedigree and environmental covariables interaction models Gzip Archive - 7.8 MB - MD5: 899ad733bc009f213bfdeed4df1cb4bd This zipped folder contains 4 supplemental files and one data dictionary to describe the variables contained in the other files.
36 ESWYT_EnvData.xls Aug 6, 2018 - 36th Elite Spring Wheat Yield Trial MS Excel Spreadsheet - 415.2 KB - MD5: e37c8ccea311bb0bf473a96840bc3378 IWIN Summarized Data Agronomic information by location

Discovery of variants in the parental lines grown in the hybrid crossing block using genotyping-by-sequencing

Oct 3, 2018 - International Wheat Yield Partnership Research Data

Baenziger, Stephen; Belamkar, Vikas, 2018, "Discovery of variants in the parental lines grown in the hybrid crossing block using genotyping-by-sequencing", https://hdl.handle.net/11529/10548065, CIMMYT Research Data & Software Repository Network, V1

Genotyping-by-sequencing (GBS) data, variant calls and Single Nucleotide Polymorphism (SNP) calls of parental lines grown in the hybrid crossing block in 2017.

GBS_KeyFile_v2.7z

Oct 3, 2018 - Discovery of variants in the parental lines grown in the hybrid crossing block using genotyping-by-sequencing

7Z Archive - 139.0 KB -

Key file associated with the FASTQ files. To request access to this file or any information related to it, please contact the IWYP Data Coordintor or Stephen Baezinger (pstephen.baenziger@gmail.com).

HCB17_SNPs_Unfiltered.recode.vcf

Oct 3, 2018 - Discovery of variants in the parental lines grown in the hybrid crossing block using genotyping-by-sequencing

Virtual Contact File - 734.8 MB -

SNP Calls. To request access to this file or any information related to it, please contact the IWYP Data Coordintor or Stephen Baezinger (pstephen.baenziger@gmail.com).

HCB17_Variants_Unfiltered.recode.vcf

Oct 3, 2018 - Discovery of variants in the parental lines grown in the hybrid crossing block using genotyping-by-sequencing

Virtual Contact File - 751.9 MB -

Variant Calls. To request access to this file or any information related to it, please contact the IWYP Data Coordintor or Stephen Baezinger (pstephen.baenziger@gmail.com).

Links to FASTQ files.txt

Oct 3, 2018 - Discovery of variants in the parental lines grown in the hybrid crossing block using genotyping-by-sequencing

Plain Text - 521 B -

Temporary links to three FASTQ files with GBS data for the parental samples, stored in the University of Nebraska-Lincoln Box. To request access to these links, please contact the IWYP Data Coordinator or send a request email directly to Stephen Baenziger (pstephen.baenziger@gmai...

Supplemental data for multi-trait, multi-environment deep learning modeling for genomic-enabled prediction of plant traits

Sep 28, 2018 - CIMMYT Research Data

Montesinos-López, Osval A.; Montesinos-López, Abelardo; Crossa, Jose; Gianola, Daniel; Hernández-Suarez, Carlos Moisés; Martín-Vallejo, Javier, 2018, "Supplemental data for multi-trait, multi-environment deep learning modeling for genomic-enabled prediction of plant traits", https://hdl.handle.net/11529/10548134, CIMMYT Research Data & Software Repository Network, V1

This study provides supplemental data to support an investigation of the power of multi-trait deep learning (MTDL) models in terms of genomic-enabled prediction accuracy.

DataSets_Multi_trait.rar

Sep 28, 2018 - Supplemental data for multi-trait, multi-environment deep learning modeling for genomic-enabled prediction of plant traits

RAR Archive - 41.9 MB -

Supporting data

Supplemental data for hybrid wheat prediction using genomic, pedigree and environmental covariables interaction models

Sep 21, 2018 - CIMMYT Research Data

Basnet, Bhoja Raj; Crossa, Jose; Pérez-Rodríguez, Paulino; Manes, Yann; Singh, Ravi; Rosyara, Umesh; Camarillo-Castillo, Fatima; Murua, Mercedes, 2018, "Supplemental data for hybrid wheat prediction using genomic, pedigree and environmental covariables interaction models", https://hdl.handle.net/11529/10548129, CIMMYT Research Data & Software Repository Network, V1

Genomic prediction of hybrids unobserved in field evaluations is crucial. In this study, we used genomic G×E models for hybrid prediction, where similarity between lines was assessed by pedigree and molecular markers, and similarity between environments was accounted for by envir...

Supplemental_files.zip.gz

Sep 21, 2018 - Supplemental data for hybrid wheat prediction using genomic, pedigree and environmental covariables interaction models

Gzip Archive - 7.8 MB -

This zipped folder contains 4 supplemental files and one data dictionary to describe the variables contained in the other files.

36 ESWYT_EnvData.xls

Aug 6, 2018 - 36th Elite Spring Wheat Yield Trial

MS Excel Spreadsheet - 415.2 KB -

IWIN Summarized Data

Agronomic information by location

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