Last updated on 2024-12-23 12:49:47 CET.
| Package | ERROR | OK |
|---|---|---|
| SFSI | 3 | 10 |
| tensorEVD | 13 |
Current CRAN status: ERROR: 3, OK: 10
Version: 1.4.1
Check: examples
Result: ERROR
Running examples in 'SFSI-Ex.R' failed
The error most likely occurred in:
> ### Name: Reading and combining SGP outputs
> ### Title: Read and combine SGP outputs
> ### Aliases: read_SGP read_summary
>
> ### ** Examples
>
> require(SFSI)
> data(wheatHTP)
>
> index = which(Y$trial %in% 1:10) # Use only a subset of data
> Y = Y[index,]
> M = scale(M[index,])/sqrt(ncol(M)) # Subset and scale markers
> G = tcrossprod(M) # Genomic relationship matrix
> y = as.vector(scale(Y[,"E1"])) # Scale response variable
>
> # Training and testing sets
> tst = which(Y$trial %in% 1:3)
> trn = seq_along(y)[-tst]
>
> path = paste0(tempdir(),"/testSGP_")
>
> # Run the analysis into 4 subsets and save them at a given path
> SGP(y, K=G, trn=trn, tst=tst, subset=c(1,4), save.at=path)
Parameter estimation from a LMM within training data (nTRN = 194)
Variance components:
varU varE
1.5145659 0.1149247
Fixed effects:
(Intercept)
0.0009088514
Fitting a SGP model using nTST = 21 (subset 1/4) of 84 and nTRN = 194 records
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Results were saved at file:
'D:\temp\2024_12_18_01_50_01_11818\RtmpQ5XJJ7\testSGP_subset_1_of_4_SGP.RData'
> SGP(y, K=G, trn=trn, tst=tst, subset=c(2,4), save.at=path)
Parameter estimation from a LMM within training data (nTRN = 194)
Variance components:
varU varE
1.5145659 0.1149247
Fixed effects:
(Intercept)
0.0009088514
Fitting a SGP model using nTST = 21 (subset 2/4) of 84 and nTRN = 194 records
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Results were saved at file:
'D:\temp\2024_12_18_01_50_01_11818\RtmpQ5XJJ7\testSGP_subset_2_of_4_SGP.RData'
> SGP(y, K=G, trn=trn, tst=tst, subset=c(3,4), save.at=path)
Parameter estimation from a LMM within training data (nTRN = 194)
Variance components:
varU varE
1.5145659 0.1149247
Fixed effects:
(Intercept)
0.0009088514
Fitting a SGP model using nTST = 21 (subset 3/4) of 84 and nTRN = 194 records
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Results were saved at file:
'D:\temp\2024_12_18_01_50_01_11818\RtmpQ5XJJ7\testSGP_subset_3_of_4_SGP.RData'
> SGP(y, K=G, trn=trn, tst=tst, subset=c(4,4), save.at=path)
Parameter estimation from a LMM within training data (nTRN = 194)
Variance components:
varU varE
1.5145659 0.1149247
Fixed effects:
(Intercept)
0.0009088514
Fitting a SGP model using nTST = 21 (subset 4/4) of 84 and nTRN = 194 records
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Results were saved at file:
'D:\temp\2024_12_18_01_50_01_11818\RtmpQ5XJJ7\testSGP_subset_4_of_4_SGP.RData'
>
> # Collect all results after completion
> fm = read_SGP(path)
Warning in grep(pattern = paste0(fullpath, "$"), value = TRUE, x = list.files(infolder, :
TRE pattern compilation error 'Invalid back reference'
Error in grep(pattern = paste0(fullpath, "$"), value = TRUE, x = list.files(infolder, :
invalid regular expression 'D:\temp\2024_12_18_01_50_01_11818\RtmpQ5XJJ7\testSGP_.*SGP.RData$', reason 'Invalid back reference'
Calls: read_SGP -> lapply -> FUN -> basename -> grep
Execution halted
Flavor: r-devel-windows-x86_64
Version: 1.4.1
Check: examples
Result: ERROR
Running examples in 'SFSI-Ex.R' failed
The error most likely occurred in:
> ### Name: Reading and combining SGP outputs
> ### Title: Read and combine SGP outputs
> ### Aliases: read_SGP read_summary
>
> ### ** Examples
>
> require(SFSI)
> data(wheatHTP)
>
> index = which(Y$trial %in% 1:10) # Use only a subset of data
> Y = Y[index,]
> M = scale(M[index,])/sqrt(ncol(M)) # Subset and scale markers
> G = tcrossprod(M) # Genomic relationship matrix
> y = as.vector(scale(Y[,"E1"])) # Scale response variable
>
> # Training and testing sets
> tst = which(Y$trial %in% 1:3)
> trn = seq_along(y)[-tst]
>
> path = paste0(tempdir(),"/testSGP_")
>
> # Run the analysis into 4 subsets and save them at a given path
> SGP(y, K=G, trn=trn, tst=tst, subset=c(1,4), save.at=path)
Parameter estimation from a LMM within training data (nTRN = 194)
Variance components:
varU varE
1.5145659 0.1149247
Fixed effects:
(Intercept)
0.0009088514
Fitting a SGP model using nTST = 21 (subset 1/4) of 84 and nTRN = 194 records
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|======================================================================| 100%
Results were saved at file:
'D:\temp\2024_12_08_01_50_01_8405\RtmpwjiLqZ\testSGP_subset_1_of_4_SGP.RData'
> SGP(y, K=G, trn=trn, tst=tst, subset=c(2,4), save.at=path)
Parameter estimation from a LMM within training data (nTRN = 194)
Variance components:
varU varE
1.5145659 0.1149247
Fixed effects:
(Intercept)
0.0009088514
Fitting a SGP model using nTST = 21 (subset 2/4) of 84 and nTRN = 194 records
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Results were saved at file:
'D:\temp\2024_12_08_01_50_01_8405\RtmpwjiLqZ\testSGP_subset_2_of_4_SGP.RData'
> SGP(y, K=G, trn=trn, tst=tst, subset=c(3,4), save.at=path)
Parameter estimation from a LMM within training data (nTRN = 194)
Variance components:
varU varE
1.5145659 0.1149247
Fixed effects:
(Intercept)
0.0009088514
Fitting a SGP model using nTST = 21 (subset 3/4) of 84 and nTRN = 194 records
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Results were saved at file:
'D:\temp\2024_12_08_01_50_01_8405\RtmpwjiLqZ\testSGP_subset_3_of_4_SGP.RData'
> SGP(y, K=G, trn=trn, tst=tst, subset=c(4,4), save.at=path)
Parameter estimation from a LMM within training data (nTRN = 194)
Variance components:
varU varE
1.5145659 0.1149247
Fixed effects:
(Intercept)
0.0009088514
Fitting a SGP model using nTST = 21 (subset 4/4) of 84 and nTRN = 194 records
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Results were saved at file:
'D:\temp\2024_12_08_01_50_01_8405\RtmpwjiLqZ\testSGP_subset_4_of_4_SGP.RData'
>
> # Collect all results after completion
> fm = read_SGP(path)
Warning in grep(pattern = paste0(fullpath, "$"), value = TRUE, x = list.files(infolder, :
TRE pattern compilation error 'Invalid back reference'
Error in grep(pattern = paste0(fullpath, "$"), value = TRUE, x = list.files(infolder, :
invalid regular expression 'D:\temp\2024_12_08_01_50_01_8405\RtmpwjiLqZ\testSGP_.*SGP.RData$', reason 'Invalid back reference'
Calls: read_SGP -> lapply -> FUN -> basename -> grep
Execution halted
Flavor: r-release-windows-x86_64
Version: 1.4.1
Check: examples
Result: ERROR
Running examples in 'SFSI-Ex.R' failed
The error most likely occurred in:
> ### Name: Reading and combining SGP outputs
> ### Title: Read and combine SGP outputs
> ### Aliases: read_SGP read_summary
>
> ### ** Examples
>
> require(SFSI)
> data(wheatHTP)
>
> index = which(Y$trial %in% 1:10) # Use only a subset of data
> Y = Y[index,]
> M = scale(M[index,])/sqrt(ncol(M)) # Subset and scale markers
> G = tcrossprod(M) # Genomic relationship matrix
> y = as.vector(scale(Y[,"E1"])) # Scale response variable
>
> # Training and testing sets
> tst = which(Y$trial %in% 1:3)
> trn = seq_along(y)[-tst]
>
> path = paste0(tempdir(),"/testSGP_")
>
> # Run the analysis into 4 subsets and save them at a given path
> SGP(y, K=G, trn=trn, tst=tst, subset=c(1,4), save.at=path)
Parameter estimation from a LMM within training data (nTRN = 194)
Variance components:
varU varE
1.5145659 0.1149247
Fixed effects:
(Intercept)
0.0009088514
Fitting a SGP model using nTST = 21 (subset 1/4) of 84 and nTRN = 194 records
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|======================================================================| 100%
Results were saved at file:
'D:\temp\2024_12_20_01_50_00_19051\Rtmp2vdAVO\testSGP_subset_1_of_4_SGP.RData'
> SGP(y, K=G, trn=trn, tst=tst, subset=c(2,4), save.at=path)
Parameter estimation from a LMM within training data (nTRN = 194)
Variance components:
varU varE
1.5145659 0.1149247
Fixed effects:
(Intercept)
0.0009088514
Fitting a SGP model using nTST = 21 (subset 2/4) of 84 and nTRN = 194 records
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Results were saved at file:
'D:\temp\2024_12_20_01_50_00_19051\Rtmp2vdAVO\testSGP_subset_2_of_4_SGP.RData'
> SGP(y, K=G, trn=trn, tst=tst, subset=c(3,4), save.at=path)
Parameter estimation from a LMM within training data (nTRN = 194)
Variance components:
varU varE
1.5145659 0.1149247
Fixed effects:
(Intercept)
0.0009088514
Fitting a SGP model using nTST = 21 (subset 3/4) of 84 and nTRN = 194 records
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Results were saved at file:
'D:\temp\2024_12_20_01_50_00_19051\Rtmp2vdAVO\testSGP_subset_3_of_4_SGP.RData'
> SGP(y, K=G, trn=trn, tst=tst, subset=c(4,4), save.at=path)
Parameter estimation from a LMM within training data (nTRN = 194)
Variance components:
varU varE
1.5145659 0.1149247
Fixed effects:
(Intercept)
0.0009088514
Fitting a SGP model using nTST = 21 (subset 4/4) of 84 and nTRN = 194 records
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|======================================================================| 100%
Results were saved at file:
'D:\temp\2024_12_20_01_50_00_19051\Rtmp2vdAVO\testSGP_subset_4_of_4_SGP.RData'
>
> # Collect all results after completion
> fm = read_SGP(path)
Warning in grep(pattern = paste0(fullpath, "$"), value = TRUE, x = list.files(infolder, :
TRE pattern compilation error 'Invalid back reference'
Error in grep(pattern = paste0(fullpath, "$"), value = TRUE, x = list.files(infolder, :
invalid regular expression 'D:\temp\2024_12_20_01_50_00_19051\Rtmp2vdAVO\testSGP_.*SGP.RData$', reason 'Invalid back reference'
Calls: read_SGP -> lapply -> FUN -> basename -> grep
Execution halted
Flavor: r-oldrel-windows-x86_64
Current CRAN status: OK: 13