CRAN Package Check Results for Package ACMEeqtl

Last updated on 2018-08-21 06:49:56 CEST.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 1.6 2.79 29.12 31.91 OK
r-devel-linux-x86_64-debian-gcc 1.6 2.22 23.46 25.68 OK
r-devel-linux-x86_64-fedora-clang 1.6 39.12 OK
r-devel-linux-x86_64-fedora-gcc 1.6 41.43 OK
r-devel-windows-ix86+x86_64 1.6 9.00 81.00 90.00 ERROR
r-patched-linux-x86_64 1.6 2.67 27.28 29.95 OK
r-patched-solaris-x86 1.6 56.60 OK
r-release-linux-x86_64 1.6 2.36 26.95 29.31 OK
r-release-windows-ix86+x86_64 1.6 9.00 55.00 64.00 OK
r-release-osx-x86_64 1.6 OK
r-oldrel-windows-ix86+x86_64 1.6 6.00 58.00 64.00 OK
r-oldrel-osx-x86_64 1.6 OK

Check Details

Version: 1.6
Check: running examples for arch ‘i386’
Result: ERROR
    Running examples in 'ACMEeqtl-Ex.R' failed
    The error most likely occurred in:
    
    > ### Name: multisnpACME
    > ### Title: Estimation of Multi-SNP ACME Model for Full-Tissue Genome and
    > ### All Local SNPs
    > ### Aliases: multisnpACME
    >
    > ### ** Examples
    >
    > # First we generate a eQTL dataset in filematrix format
    > tempdirectory = tempdir()
    > z = create_artificial_data(
    + nsample = 50,
    + ngene = 11,
    + nsnp = 51,
    + ncvrt = 1,
    + minMAF = 0.2,
    + saveDir = tempdirectory,
    + returnData = FALSE,
    + savefmat = TRUE,
    + savetxt = FALSE,
    + verbose = FALSE)
    >
    > # Then we run multithreadACME to obtain single-SNP estimates.
    > # In this example, we use 2 CPU cores (threads)
    > # for testing of all gene-SNP pairs within 100,000 bp.
    > multithreadACME(
    + genefm = "gene",
    + snpsfm = "snps",
    + glocfm = "gene_loc",
    + slocfm = "snps_loc",
    + cvrtfm = "cvrt",
    + acmefm = "ACME",
    + cisdist = 10e+06,
    + threads = 1, # Use more for faster run
    + workdir = file.path(tempdirectory, "filematrices"),
    + verbose = FALSE)
    Finished in 0 seconds
    Finished in 0 seconds
    Finished in 0 seconds
    Finished in 0 seconds
    Finished in 0 seconds
    Finished in 0 seconds
    Finished in 0 seconds
    Finished in 0 seconds
    Finished in 0 seconds
    Finished in 0 seconds
    Finished in 0 seconds
    >
    > # Now the filematrix `ACME` holds estimations for all local gene-SNP pairs.
    >
    > fm = fm.open(file.path(tempdirectory, "filematrices", "ACME"))
    > TenResults = fm[,1:10]
    > rownames(TenResults) = rownames(fm)
    > close(fm)
    >
    > show(t(TenResults))
     geneid snp_id beta0 beta1 nits SSE SST F
     [1,] 1 1 114.3747 164.298468 6 70.23063 84.16095 9.32249958
     [2,] 1 2 146.9906 104.708955 5 79.43809 84.16095 2.79430534
     [3,] 1 3 248.3731 -53.297432 8 82.07647 84.16095 1.19364576
     [4,] 2 4 152.5656 -28.712143 5 58.53136 59.45974 0.74547831
     [5,] 2 5 151.5951 -23.536547 5 58.78067 59.45974 0.54296895
     [6,] 2 6 137.9036 -3.493660 5 59.44054 59.45974 0.01518305
     [7,] 2 7 100.2717 56.258948 7 56.05362 59.45974 2.85597437
     [8,] 2 8 131.6374 4.338647 6 59.42598 59.45974 0.02669669
     [9,] 3 9 139.0213 12.939411 4 48.82208 48.97752 0.14963090
    [10,] 3 10 157.7305 -12.139848 11 48.78336 48.97752 0.18705783
     eta SE
     [1,] 1.43649302 0.7972499
     [2,] 0.71235131 0.5856060
     [3,] -0.21458613 0.1494263
     [4,] -0.18819542 0.1771115
     [5,] -0.15525930 0.1791377
     [6,] -0.02533408 0.2006827
     [7,] 0.56106530 0.4421209
     [8,] 0.03295908 0.2078457
     [9,] 0.09307500 0.2574778
    [10,] -0.07696576 0.1644957
    >
    > # Now we can estimate multi-SNP ACME models for each gene:
    > multisnpACME(
    + genefm = "gene",
    + snpsfm = "snps",
    + glocfm = "gene_loc",
    + slocfm = "snps_loc",
    + cvrtfm = "cvrt",
    + acmefm = "ACME",
    + workdir = file.path(tempdirectory, "filematrices"),
    + genecap = Inf,
    + verbose = TRUE)
    Loading and orthonormalizing covariates
    Loading gene/SNP locations
    Checking gene/SNP filematrices
    Creating output filematrix
    Scanning for gene 1
    ----Gene 1, added SNP 1 with AdjR2 0.1478
    ----Gene 1, added SNP 3 with AdjR2 0.1682
    Scanning for gene 2
    ----Gene 2, added SNP 4 with AdjR2 0.0372
    ----Gene 2, added SNP 5 with AdjR2 0.0399
    ----Gene 2, added SNP 1 with AdjR2 0.0819
    Scanning for gene 3
    ----Gene 3, added SNP 3 with AdjR2 0.0061
    ----Gene 3, added SNP 4 with AdjR2 0.0126
    ----Gene 3, added SNP 5 with AdjR2 0.0185
    >
    >
    >
    > cleanEx()
    Error: connections left open:
     D:\temp\RtmpQvsgaL\filematrices\snps.bmat (file)
     D:\temp\RtmpQvsgaL\filematrices\gene.bmat (file)
     D:\temp\RtmpQvsgaL\filematrices\ACME.bmat (file)
    Execution halted
Flavor: r-devel-windows-ix86+x86_64

Version: 1.6
Check: running examples for arch ‘x64’
Result: ERROR
    Running examples in 'ACMEeqtl-Ex.R' failed
    The error most likely occurred in:
    
    > ### Name: multisnpACME
    > ### Title: Estimation of Multi-SNP ACME Model for Full-Tissue Genome and
    > ### All Local SNPs
    > ### Aliases: multisnpACME
    >
    > ### ** Examples
    >
    > # First we generate a eQTL dataset in filematrix format
    > tempdirectory = tempdir()
    > z = create_artificial_data(
    + nsample = 50,
    + ngene = 11,
    + nsnp = 51,
    + ncvrt = 1,
    + minMAF = 0.2,
    + saveDir = tempdirectory,
    + returnData = FALSE,
    + savefmat = TRUE,
    + savetxt = FALSE,
    + verbose = FALSE)
    >
    > # Then we run multithreadACME to obtain single-SNP estimates.
    > # In this example, we use 2 CPU cores (threads)
    > # for testing of all gene-SNP pairs within 100,000 bp.
    > multithreadACME(
    + genefm = "gene",
    + snpsfm = "snps",
    + glocfm = "gene_loc",
    + slocfm = "snps_loc",
    + cvrtfm = "cvrt",
    + acmefm = "ACME",
    + cisdist = 10e+06,
    + threads = 1, # Use more for faster run
    + workdir = file.path(tempdirectory, "filematrices"),
    + verbose = FALSE)
    Finished in 0 seconds
    Finished in 0 seconds
    Finished in 0 seconds
    Finished in 0 seconds
    Finished in 0 seconds
    Finished in 0 seconds
    Finished in 0 seconds
    Finished in 0 seconds
    Finished in 0 seconds
    Finished in 0 seconds
    Finished in 0 seconds
    >
    > # Now the filematrix `ACME` holds estimations for all local gene-SNP pairs.
    >
    > fm = fm.open(file.path(tempdirectory, "filematrices", "ACME"))
    > TenResults = fm[,1:10]
    > rownames(TenResults) = rownames(fm)
    > close(fm)
    >
    > show(t(TenResults))
     geneid snp_id beta0 beta1 nits SSE SST F
     [1,] 1 1 114.3747 164.298468 6 70.23063 84.16095 9.32249958
     [2,] 1 2 146.9906 104.708955 5 79.43809 84.16095 2.79430534
     [3,] 1 3 248.3731 -53.297432 8 82.07647 84.16095 1.19364576
     [4,] 2 4 152.5656 -28.712143 5 58.53136 59.45974 0.74547831
     [5,] 2 5 151.5951 -23.536547 5 58.78067 59.45974 0.54296895
     [6,] 2 6 137.9036 -3.493660 5 59.44054 59.45974 0.01518305
     [7,] 2 7 100.2717 56.258948 7 56.05362 59.45974 2.85597437
     [8,] 2 8 131.6374 4.338647 6 59.42598 59.45974 0.02669669
     [9,] 3 9 139.0213 12.939411 4 48.82208 48.97752 0.14963090
    [10,] 3 10 157.7305 -12.139848 11 48.78336 48.97752 0.18705783
     eta SE
     [1,] 1.43649302 0.7972499
     [2,] 0.71235131 0.5856060
     [3,] -0.21458613 0.1494263
     [4,] -0.18819542 0.1771115
     [5,] -0.15525930 0.1791377
     [6,] -0.02533408 0.2006827
     [7,] 0.56106530 0.4421209
     [8,] 0.03295908 0.2078457
     [9,] 0.09307500 0.2574778
    [10,] -0.07696576 0.1644957
    >
    > # Now we can estimate multi-SNP ACME models for each gene:
    > multisnpACME(
    + genefm = "gene",
    + snpsfm = "snps",
    + glocfm = "gene_loc",
    + slocfm = "snps_loc",
    + cvrtfm = "cvrt",
    + acmefm = "ACME",
    + workdir = file.path(tempdirectory, "filematrices"),
    + genecap = Inf,
    + verbose = TRUE)
    Loading and orthonormalizing covariates
    Loading gene/SNP locations
    Checking gene/SNP filematrices
    Creating output filematrix
    Scanning for gene 1
    ----Gene 1, added SNP 1 with AdjR2 0.1478
    ----Gene 1, added SNP 3 with AdjR2 0.1682
    Scanning for gene 2
    ----Gene 2, added SNP 4 with AdjR2 0.0372
    ----Gene 2, added SNP 5 with AdjR2 0.0399
    ----Gene 2, added SNP 1 with AdjR2 0.0819
    Scanning for gene 3
    ----Gene 3, added SNP 3 with AdjR2 0.0061
    ----Gene 3, added SNP 4 with AdjR2 0.0126
    ----Gene 3, added SNP 5 with AdjR2 0.0185
    >
    >
    >
    > cleanEx()
    Error: connections left open:
     D:\temp\Rtmps3VCft\filematrices\snps.bmat (file)
     D:\temp\Rtmps3VCft\filematrices\gene.bmat (file)
     D:\temp\Rtmps3VCft\filematrices\ACME.bmat (file)
    Execution halted
Flavor: r-devel-windows-ix86+x86_64