CIMMYT Research Software

Free, open access repository of research software produced and developed by CIMMYT scientists.

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61 to 70 of 82 Results

README_BGLR-R.txt Jul 11, 2018 - BGLRR - Bayesian Generalized Linear Regression in R. V 2.1 Plain Text - 3.7 KB - MD5: 3e8e22f64b1e4600fe17e1b6694c223a
MAIZEDIALLEL-2LOCS-2YEARS.tab May 5, 2018 - Program and sample data for SASHAYDIALL: A SAS Program for Hayman’s Diallel Analysis Tabular Data - 10.3 KB - 6 Variables, 728 Observations - UNF:6:qb2UIHULo/KZ3V04rm33PA== Sample Dataset
An informational view of accession rarity and allele specificity in germplasm banks for management and conservation Feb 14, 2018 Reyes-Valdés, M Humberto; Burgueño, Juan; Martínez, Octavio; Sansaloni, Carolina Paola, 2018, "An informational view of accession rarity and allele specificity in germplasm banks for management and conservation", https://hdl.handle.net/11529/10547952, CIMMYT Research Data & Software Repository Network, V2, UNF:6:v+RWYoZQ/W6oh+hfVGd6uQ== [fileUNF] Repository of the data set used in the paper "An informational view of accession rarity and allele specificity in germplasm banks for management and conservation" M. Humberto Reyes-Valdés 1, Juan Burgueño-Ferreira 2, Octavio Martínez 3, Carolina Paola Sansaloni 2. 1 Department of...
AllDataHexaploid.bin Feb 14, 2018 - An informational view of accession rarity and allele specificity in germplasm banks for management and conservation R Data - 81.7 MB - MD5: ffec764128374e86a73b31e57a33a533 AllDataHexaploid.bin. A table in RData format, readable by R through the function load. It has a dimension 41052 x 7987. The column allele_id is the SNP allele id, and the remaining 7986 columns are hexaploid wheat accessions. The numbers in the cells are allele frequencies. Th...
sampleLowNaGID_Trim.bin Feb 14, 2018 - An informational view of accession rarity and allele specificity in germplasm banks for management and conservation Unknown - 5.8 MB - MD5: 256a7c0e69ebd16cc88b80d6fea8e6cb
sampleLowNaGID_Trim.tab Feb 14, 2018 - An informational view of accession rarity and allele specificity in germplasm banks for management and conservation Tabular Data - 64.1 MB - 7988 Variables, 4126 Observations - UNF:6:v+RWYoZQ/W6oh+hfVGd6uQ==
Use of High-Resolution Image Data Outperforms Vegetation Indices in Prediction of Maize Yield: Supplementary Methods Jun 27, 2017 Fernando Aguate; Samuel Trachsel; Lorena González-Pérez; Juan Burgueño; José Crossa; Mónica Balzarini; David Gouache; Matthieu Bogard; Gustavo de los Campos, 2017, "Use of High-Resolution Image Data Outperforms Vegetation Indices in Prediction of Maize Yield: Supplementary Methods", https://hdl.handle.net/11529/10972, CIMMYT Research Data & Software Repository Network, V1 This is the supplementary methods of "Use of High-Resolution Image Data Outperforms Vegetation Indices in Prediction of Maize Yield" published in Crop Science · May 2017, DOI: 10.2135/cropsci2017.01.0007. It includes the raw data in R format and the R-code for the analysis.
dataAguateCropSci2017.RData Jun 27, 2017 - Use of High-Resolution Image Data Outperforms Vegetation Indices in Prediction of Maize Yield: Supplementary Methods Unknown - 695.0 KB - MD5: ad2a90490e7c619747d1690bddd1cd04 Raw data in R format
getResults.html Jun 27, 2017 - Use of High-Resolution Image Data Outperforms Vegetation Indices in Prediction of Maize Yield: Supplementary Methods HTML - 2.0 MB - MD5: 6ec2dfc08226ef6b760d0b76c2040591 R- code to analyze data step by step
SI-R Codes for Computing Selection Indices in R Jan 7, 2017 Alvarado, Gregorio; Pérez-Elizalde, Sergio; Cerón, Jesús, 2015, "SI-R Codes for Computing Selection Indices in R", https://hdl.handle.net/11529/10352, CIMMYT Research Data & Software Repository Network, V4 SI is a collection of R codes to compute several selection indices. It comes together a powerpoint explanation of the indices and one example.

README_BGLR-R.txt

Jul 11, 2018 - BGLRR - Bayesian Generalized Linear Regression in R. V 2.1

Plain Text - 3.7 KB -

MAIZEDIALLEL-2LOCS-2YEARS.tab

May 5, 2018 - Program and sample data for SASHAYDIALL: A SAS Program for Hayman’s Diallel Analysis

Tabular Data - 10.3 KB - 6 Variables, 728 Observations -

Sample Dataset

An informational view of accession rarity and allele specificity in germplasm banks for management and conservation

Feb 14, 2018

Reyes-Valdés, M Humberto; Burgueño, Juan; Martínez, Octavio; Sansaloni, Carolina Paola, 2018, "An informational view of accession rarity and allele specificity in germplasm banks for management and conservation", https://hdl.handle.net/11529/10547952, CIMMYT Research Data & Software Repository Network, V2, UNF:6:v+RWYoZQ/W6oh+hfVGd6uQ== [fileUNF]

Repository of the data set used in the paper "An informational view of accession rarity and allele specificity in germplasm banks for management and conservation" M. Humberto Reyes-Valdés 1, Juan Burgueño-Ferreira 2, Octavio Martínez 3, Carolina Paola Sansaloni 2. 1 Department of...

AllDataHexaploid.bin

Feb 14, 2018 - An informational view of accession rarity and allele specificity in germplasm banks for management and conservation

R Data - 81.7 MB -

AllDataHexaploid.bin. A table in RData format, readable by R through the function *load*. It has a dimension 41052 x 7987. The column allele_id is the SNP allele id, and the remaining 7986 columns are hexaploid wheat accessions. The numbers in the cells are allele frequencies. Th...

sampleLowNaGID_Trim.bin

Feb 14, 2018 - An informational view of accession rarity and allele specificity in germplasm banks for management and conservation

Unknown - 5.8 MB -

sampleLowNaGID_Trim.tab

Feb 14, 2018 - An informational view of accession rarity and allele specificity in germplasm banks for management and conservation

Tabular Data - 64.1 MB - 7988 Variables, 4126 Observations -

Use of High-Resolution Image Data Outperforms Vegetation Indices in Prediction of Maize Yield: Supplementary Methods

Jun 27, 2017

Fernando Aguate; Samuel Trachsel; Lorena González-Pérez; Juan Burgueño; José Crossa; Mónica Balzarini; David Gouache; Matthieu Bogard; Gustavo de los Campos, 2017, "Use of High-Resolution Image Data Outperforms Vegetation Indices in Prediction of Maize Yield: Supplementary Methods", https://hdl.handle.net/11529/10972, CIMMYT Research Data & Software Repository Network, V1

This is the supplementary methods of "Use of High-Resolution Image Data Outperforms Vegetation Indices in Prediction of Maize Yield" published in Crop Science · May 2017, DOI: 10.2135/cropsci2017.01.0007. It includes the raw data in R format and the R-code for the analysis.

dataAguateCropSci2017.RData

Jun 27, 2017 - Use of High-Resolution Image Data Outperforms Vegetation Indices in Prediction of Maize Yield: Supplementary Methods

Unknown - 695.0 KB -

Raw data in R format

getResults.html

Jun 27, 2017 - Use of High-Resolution Image Data Outperforms Vegetation Indices in Prediction of Maize Yield: Supplementary Methods

HTML - 2.0 MB -

R- code to analyze data step by step

SI-R Codes for Computing Selection Indices in R

Jan 7, 2017

Alvarado, Gregorio; Pérez-Elizalde, Sergio; Cerón, Jesús, 2015, "SI-R Codes for Computing Selection Indices in R", https://hdl.handle.net/11529/10352, CIMMYT Research Data & Software Repository Network, V4

SI is a collection of R codes to compute several selection indices. It comes together a powerpoint explanation of the indices and one example.

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