Back to Multiple platform build/check report for BioC 3.9
ABCDEFGHIJKLMNOPQR[S]TUVWXYZ

CHECK report for SNPRelate on celaya2

This page was generated on 2019-10-16 12:53:54 -0400 (Wed, 16 Oct 2019).

Package 1552/1741HostnameOS / ArchINSTALLBUILDCHECKBUILD BIN
SNPRelate 1.18.1
Xiuwen Zheng
Snapshot Date: 2019-10-15 17:01:26 -0400 (Tue, 15 Oct 2019)
URL: https://git.bioconductor.org/packages/SNPRelate
Branch: RELEASE_3_9
Last Commit: 81c581b
Last Changed Date: 2019-07-03 14:00:19 -0400 (Wed, 03 Jul 2019)
malbec2 Linux (Ubuntu 18.04.2 LTS) / x86_64  OK  OK  OK UNNEEDED, same version exists in internal repository
tokay2 Windows Server 2012 R2 Standard / x64  OK  OK  OK  OK UNNEEDED, same version exists in internal repository
celaya2 OS X 10.11.6 El Capitan / x86_64  OK  OK [ OK ] OK UNNEEDED, same version exists in internal repository

Summary

Package: SNPRelate
Version: 1.18.1
Command: /Library/Frameworks/R.framework/Versions/Current/Resources/bin/R CMD check --install=check:SNPRelate.install-out.txt --library=/Library/Frameworks/R.framework/Versions/Current/Resources/library --no-vignettes --timings SNPRelate_1.18.1.tar.gz
StartedAt: 2019-10-16 07:01:34 -0400 (Wed, 16 Oct 2019)
EndedAt: 2019-10-16 07:04:20 -0400 (Wed, 16 Oct 2019)
EllapsedTime: 166.2 seconds
RetCode: 0
Status:  OK 
CheckDir: SNPRelate.Rcheck
Warnings: 0

Command output

##############################################################################
##############################################################################
###
### Running command:
###
###   /Library/Frameworks/R.framework/Versions/Current/Resources/bin/R CMD check --install=check:SNPRelate.install-out.txt --library=/Library/Frameworks/R.framework/Versions/Current/Resources/library --no-vignettes --timings SNPRelate_1.18.1.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/Users/biocbuild/bbs-3.9-bioc/meat/SNPRelate.Rcheck’
* using R version 3.6.1 (2019-07-05)
* using platform: x86_64-apple-darwin15.6.0 (64-bit)
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘SNPRelate/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘SNPRelate’ version ‘1.18.1’
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘SNPRelate’ can be installed ... OK
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... OK
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking R files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... OK
* checking Rd metadata ... OK
* checking Rd cross-references ... OK
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of ‘data’ directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking line endings in C/C++/Fortran sources/headers ... OK
* checking line endings in Makefiles ... OK
* checking compilation flags in Makevars ... OK
* checking for GNU extensions in Makefiles ... OK
* checking for portable use of $(BLAS_LIBS) and $(LAPACK_LIBS) ... OK
* checking compiled code ... NOTE
Note: information on .o files is not available
* checking files in ‘vignettes’ ... OK
* checking examples ... OK
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
  Running ‘runTests.R’
 OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes in ‘inst/doc’ ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE

Status: 1 NOTE
See
  ‘/Users/biocbuild/bbs-3.9-bioc/meat/SNPRelate.Rcheck/00check.log’
for details.



Installation output

SNPRelate.Rcheck/00install.out

##############################################################################
##############################################################################
###
### Running command:
###
###   /Library/Frameworks/R.framework/Versions/Current/Resources/bin/R CMD INSTALL SNPRelate
###
##############################################################################
##############################################################################


* installing to library ‘/Library/Frameworks/R.framework/Versions/3.6/Resources/library’
* installing *source* package ‘SNPRelate’ ...
** using staged installation
** libs
clang++ -std=gnu++11 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -DUSING_R -I. -I"/Library/Frameworks/R.framework/Versions/3.6/Resources/library/gdsfmt/include" -isysroot /Library/Developer/CommandLineTools/SDKs/MacOSX.sdk -I/usr/local/include  -fPIC  -Wall -g -O2  -c ConvToGDS.cpp -o ConvToGDS.o
clang -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -DUSING_R -I. -I"/Library/Frameworks/R.framework/Versions/3.6/Resources/library/gdsfmt/include" -isysroot /Library/Developer/CommandLineTools/SDKs/MacOSX.sdk -I/usr/local/include  -fPIC  -Wall -g -O2  -c R_SNPRelate.c -o R_SNPRelate.o
clang++ -std=gnu++11 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -DUSING_R -I. -I"/Library/Frameworks/R.framework/Versions/3.6/Resources/library/gdsfmt/include" -isysroot /Library/Developer/CommandLineTools/SDKs/MacOSX.sdk -I/usr/local/include  -fPIC  -Wall -g -O2  -c SNPRelate.cpp -o SNPRelate.o
clang++ -std=gnu++11 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -DUSING_R -I. -I"/Library/Frameworks/R.framework/Versions/3.6/Resources/library/gdsfmt/include" -isysroot /Library/Developer/CommandLineTools/SDKs/MacOSX.sdk -I/usr/local/include  -fPIC  -Wall -g -O2  -c ThreadPool.cpp -o ThreadPool.o
clang++ -std=gnu++11 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -DUSING_R -I. -I"/Library/Frameworks/R.framework/Versions/3.6/Resources/library/gdsfmt/include" -isysroot /Library/Developer/CommandLineTools/SDKs/MacOSX.sdk -I/usr/local/include  -fPIC  -Wall -g -O2  -c dGenGWAS.cpp -o dGenGWAS.o
clang++ -std=gnu++11 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -DUSING_R -I. -I"/Library/Frameworks/R.framework/Versions/3.6/Resources/library/gdsfmt/include" -isysroot /Library/Developer/CommandLineTools/SDKs/MacOSX.sdk -I/usr/local/include  -fPIC  -Wall -g -O2  -c dVect.cpp -o dVect.o
clang++ -std=gnu++11 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -DUSING_R -I. -I"/Library/Frameworks/R.framework/Versions/3.6/Resources/library/gdsfmt/include" -isysroot /Library/Developer/CommandLineTools/SDKs/MacOSX.sdk -I/usr/local/include  -fPIC  -Wall -g -O2  -c genBeta.cpp -o genBeta.o
clang++ -std=gnu++11 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -DUSING_R -I. -I"/Library/Frameworks/R.framework/Versions/3.6/Resources/library/gdsfmt/include" -isysroot /Library/Developer/CommandLineTools/SDKs/MacOSX.sdk -I/usr/local/include  -fPIC  -Wall -g -O2  -c genEIGMIX.cpp -o genEIGMIX.o
clang++ -std=gnu++11 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -DUSING_R -I. -I"/Library/Frameworks/R.framework/Versions/3.6/Resources/library/gdsfmt/include" -isysroot /Library/Developer/CommandLineTools/SDKs/MacOSX.sdk -I/usr/local/include  -fPIC  -Wall -g -O2  -c genFst.cpp -o genFst.o
clang++ -std=gnu++11 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -DUSING_R -I. -I"/Library/Frameworks/R.framework/Versions/3.6/Resources/library/gdsfmt/include" -isysroot /Library/Developer/CommandLineTools/SDKs/MacOSX.sdk -I/usr/local/include  -fPIC  -Wall -g -O2  -c genHWE.cpp -o genHWE.o
clang++ -std=gnu++11 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -DUSING_R -I. -I"/Library/Frameworks/R.framework/Versions/3.6/Resources/library/gdsfmt/include" -isysroot /Library/Developer/CommandLineTools/SDKs/MacOSX.sdk -I/usr/local/include  -fPIC  -Wall -g -O2  -c genIBD.cpp -o genIBD.o
clang++ -std=gnu++11 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -DUSING_R -I. -I"/Library/Frameworks/R.framework/Versions/3.6/Resources/library/gdsfmt/include" -isysroot /Library/Developer/CommandLineTools/SDKs/MacOSX.sdk -I/usr/local/include  -fPIC  -Wall -g -O2  -c genIBS.cpp -o genIBS.o
clang++ -std=gnu++11 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -DUSING_R -I. -I"/Library/Frameworks/R.framework/Versions/3.6/Resources/library/gdsfmt/include" -isysroot /Library/Developer/CommandLineTools/SDKs/MacOSX.sdk -I/usr/local/include  -fPIC  -Wall -g -O2  -c genKING.cpp -o genKING.o
clang++ -std=gnu++11 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -DUSING_R -I. -I"/Library/Frameworks/R.framework/Versions/3.6/Resources/library/gdsfmt/include" -isysroot /Library/Developer/CommandLineTools/SDKs/MacOSX.sdk -I/usr/local/include  -fPIC  -Wall -g -O2  -c genLD.cpp -o genLD.o
clang++ -std=gnu++11 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -DUSING_R -I. -I"/Library/Frameworks/R.framework/Versions/3.6/Resources/library/gdsfmt/include" -isysroot /Library/Developer/CommandLineTools/SDKs/MacOSX.sdk -I/usr/local/include  -fPIC  -Wall -g -O2  -c genPCA.cpp -o genPCA.o
clang++ -std=gnu++11 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -DUSING_R -I. -I"/Library/Frameworks/R.framework/Versions/3.6/Resources/library/gdsfmt/include" -isysroot /Library/Developer/CommandLineTools/SDKs/MacOSX.sdk -I/usr/local/include  -fPIC  -Wall -g -O2  -c genSlideWin.cpp -o genSlideWin.o
clang++ -std=gnu++11 -dynamiclib -Wl,-headerpad_max_install_names -undefined dynamic_lookup -single_module -multiply_defined suppress -L/Library/Frameworks/R.framework/Resources/lib -L/usr/local/lib -o SNPRelate.so ConvToGDS.o R_SNPRelate.o SNPRelate.o ThreadPool.o dGenGWAS.o dVect.o genBeta.o genEIGMIX.o genFst.o genHWE.o genIBD.o genIBS.o genKING.o genLD.o genPCA.o genSlideWin.o -lpthread -L/Library/Frameworks/R.framework/Resources/lib -lRlapack -L/Library/Frameworks/R.framework/Resources/lib -lRblas -L/usr/local/gfortran/lib/gcc/x86_64-apple-darwin15/6.1.0 -L/usr/local/gfortran/lib -lgfortran -lquadmath -lm -F/Library/Frameworks/R.framework/.. -framework R -Wl,-framework -Wl,CoreFoundation
installing to /Library/Frameworks/R.framework/Versions/3.6/Resources/library/00LOCK-SNPRelate/00new/SNPRelate/libs
** R
** data
** inst
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** checking absolute paths in shared objects and dynamic libraries
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (SNPRelate)

Tests output

SNPRelate.Rcheck/tests/runTests.Rout


R version 3.6.1 (2019-07-05) -- "Action of the Toes"
Copyright (C) 2019 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin15.6.0 (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> BiocGenerics:::testPackage("SNPRelate")
SNPRelate -- supported by Streaming SIMD Extensions 2 (SSE2)
Genetic Relationship Matrix (GRM, GCTA):
Excluding 8,088 SNPs (non-autosomes or non-selection)
Excluding 0 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 279 samples, 1,000 SNPs
    using 1 (CPU) core
GRM Calculation:    the sum of all selected genotypes (0,1,2) = 282597
CPU capabilities: Double-Precision SSE2
Wed Oct 16 07:03:11 2019    (internal increment: 13960)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 1s
Saving to the GDS file:

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Wed Oct 16 07:03:12 2019    Done.
Genetic Relationship Matrix (GRM, GCTA):
Excluding 7,088 SNPs (non-autosomes or non-selection)
Excluding 0 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 279 samples, 2,000 SNPs
    using 1 (CPU) core
GRM Calculation:    the sum of all selected genotypes (0,1,2) = 559412
CPU capabilities: Double-Precision SSE2
Wed Oct 16 07:03:12 2019    (internal increment: 13960)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 1s
Saving to the GDS file:

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Wed Oct 16 07:03:13 2019    Done.
Genetic Relationship Matrix (GRM, GCTA):
Excluding 5,288 SNPs (non-autosomes or non-selection)
Excluding 0 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 279 samples, 3,800 SNPs
    using 1 (CPU) core
GRM Calculation:    the sum of all selected genotypes (0,1,2) = 1066957
CPU capabilities: Double-Precision SSE2
Wed Oct 16 07:03:13 2019    (internal increment: 13960)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 1s
Saving to the GDS file:

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Wed Oct 16 07:03:14 2019    Done.
GRM merging:
    open 'tmp1.gds' (1,000 variants)
    open 'tmp2.gds' (2,000 variants)
    open 'tmp3.gds' (3,800 variants)
Weight: 0.147059, 0.294118, 0.558824
Output: tmp.gds

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 1s
Genetic Relationship Matrix (GRM, GCTA):
Excluding 2,288 SNPs (non-autosomes or non-selection)
Excluding 0 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 279 samples, 6,800 SNPs
    using 1 (CPU) core
GRM Calculation:    the sum of all selected genotypes (0,1,2) = 1908966
CPU capabilities: Double-Precision SSE2
Wed Oct 16 07:03:15 2019    (internal increment: 13960)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Wed Oct 16 07:03:15 2019    Done.
Genetic Relationship Matrix (GRM, IndivBeta):
Excluding 8,088 SNPs (non-autosomes or non-selection)
Excluding 0 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 279 samples, 1,000 SNPs
    using 1 (CPU) core
GRM Calculation:    the sum of all selected genotypes (0,1,2) = 282597
CPU capabilities: Double-Precision SSE2
Wed Oct 16 07:03:15 2019    (internal increment: 65536)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 1s
Saving to the GDS file:

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Wed Oct 16 07:03:16 2019    Done.
Genetic Relationship Matrix (GRM, IndivBeta):
Excluding 7,088 SNPs (non-autosomes or non-selection)
Excluding 0 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 279 samples, 2,000 SNPs
    using 1 (CPU) core
GRM Calculation:    the sum of all selected genotypes (0,1,2) = 559412
CPU capabilities: Double-Precision SSE2
Wed Oct 16 07:03:16 2019    (internal increment: 65536)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 1s
Saving to the GDS file:

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Wed Oct 16 07:03:17 2019    Done.
Genetic Relationship Matrix (GRM, IndivBeta):
Excluding 5,288 SNPs (non-autosomes or non-selection)
Excluding 0 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 279 samples, 3,800 SNPs
    using 1 (CPU) core
GRM Calculation:    the sum of all selected genotypes (0,1,2) = 1066957
CPU capabilities: Double-Precision SSE2
Wed Oct 16 07:03:17 2019    (internal increment: 65536)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Saving to the GDS file:

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 1s
Wed Oct 16 07:03:18 2019    Done.
GRM merging:
    open 'tmp1.gds' (1,000 variants)
    open 'tmp2.gds' (2,000 variants)
    open 'tmp3.gds' (3,800 variants)
Weight: 0.147059, 0.294118, 0.558824
Output: tmp.gds

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Writing ...

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Genetic Relationship Matrix (GRM, IndivBeta):
Excluding 2,288 SNPs (non-autosomes or non-selection)
Excluding 0 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 279 samples, 6,800 SNPs
    using 1 (CPU) core
GRM Calculation:    the sum of all selected genotypes (0,1,2) = 1908966
CPU capabilities: Double-Precision SSE2
Wed Oct 16 07:03:18 2019    (internal increment: 65536)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 1s
Wed Oct 16 07:03:19 2019    Done.
Linkage Disequilibrium (LD) estimation on genotypes:
Working space: 279 samples, 1000 SNPs
    using 1 (CPU) core.
    method: covariance
LD matrix:    the sum of all selected genotypes (0,1,2) = 283058
Linkage Disequilibrium (LD) estimation on genotypes:
Working space: 279 samples, 1000 SNPs
    using 1 (CPU) core.
    method: correlation
LD matrix:    the sum of all selected genotypes (0,1,2) = 283058
FUNCTION: SNPGDSFileClass
FUNCTION: SNPRelate-package
Start file conversion from PLINK BED to SNP GDS ...
    BED file: '/Library/Frameworks/R.framework/Versions/3.6/Resources/library/SNPRelate/extdata/plinkhapmap.bed.gz'
        SNP-major mode (Sample X SNP), 45.7K
    FAM file: '/Library/Frameworks/R.framework/Versions/3.6/Resources/library/SNPRelate/extdata/plinkhapmap.fam.gz'
    BIM file: '/Library/Frameworks/R.framework/Versions/3.6/Resources/library/SNPRelate/extdata/plinkhapmap.bim.gz'
Wed Oct 16 07:03:24 2019     (store sample id, snp id, position, and chromosome)
    start writing: 60 samples, 5000 SNPs ...

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Wed Oct 16 07:03:24 2019 	Done.
Optimize the access efficiency ...
Clean up the fragments of GDS file:
    open the file 'HapMap.gds' (98.1K)
    # of fragments: 38
    save to 'HapMap.gds.tmp'
    rename 'HapMap.gds.tmp' (97.8K, reduced: 240B)
    # of fragments: 18
Principal Component Analysis (PCA) on genotypes:
Excluding 203 SNPs on non-autosomes
Excluding 28 SNPs (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 60 samples, 4,769 SNPs
    using 1 (CPU) core
PCA:    the sum of all selected genotypes (0,1,2) = 124273
CPU capabilities: Double-Precision SSE2
Wed Oct 16 07:03:24 2019    (internal increment: 64920)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Wed Oct 16 07:03:24 2019    Begin (eigenvalues and eigenvectors)
Wed Oct 16 07:03:24 2019    Done.
IBD analysis (PLINK method of moment) on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 1 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 279 samples, 8,722 SNPs
    using 1 (CPU) core
PLINK IBD:    the sum of all selected genotypes (0,1,2) = 2446510
Wed Oct 16 07:03:24 2019    (internal increment: 65536)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 1s
Wed Oct 16 07:03:25 2019    Done.
Identity-By-State (IBS) analysis on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 1 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 279 samples, 8,722 SNPs
    using 1 (CPU) core
IBS:    the sum of all selected genotypes (0,1,2) = 2446510
Wed Oct 16 07:03:25 2019    (internal increment: 65536)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 1s
Wed Oct 16 07:03:26 2019    Done.
Linkage Disequilibrium (LD) estimation on genotypes:
Working space: 279 samples, 200 SNPs
    using 1 (CPU) core.
    method: composite
LD matrix:    the sum of all selected genotypes (0,1,2) = 55417
FUNCTION: hapmap_geno
FUNCTION: snpgdsAdmixPlot
Eigen-analysis on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 1 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 279 samples, 8,722 SNPs
    using 1 (CPU) core
Eigen-analysis:    the sum of all selected genotypes (0,1,2) = 2446510
CPU capabilities: Double-Precision SSE2
Wed Oct 16 07:03:26 2019    (internal increment: 13960)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 1s
Wed Oct 16 07:03:27 2019    Begin (eigenvalues and eigenvectors)
Wed Oct 16 07:03:27 2019    Done.
FUNCTION: snpgdsAdmixProp
Eigen-analysis on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 1 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 279 samples, 8,722 SNPs
    using 1 (CPU) core
Eigen-analysis:    the sum of all selected genotypes (0,1,2) = 2446510
CPU capabilities: Double-Precision SSE2
Wed Oct 16 07:03:27 2019    (internal increment: 13960)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 1s
Wed Oct 16 07:03:28 2019    Begin (eigenvalues and eigenvectors)
Wed Oct 16 07:03:28 2019    Done.
FUNCTION: snpgdsAlleleSwitch
Strand-switching at 50 SNP locus/loci.
Unable to determine switching at 10 SNP locus/loci.
FUNCTION: snpgdsApartSelection
Wed Oct 16 07:03:28 2019	Chromosome 1, # of SNPs: 367
Wed Oct 16 07:03:28 2019	Chromosome 2, # of SNPs: 367
Wed Oct 16 07:03:28 2019	Chromosome 3, # of SNPs: 317
Wed Oct 16 07:03:28 2019	Chromosome 4, # of SNPs: 295
Wed Oct 16 07:03:28 2019	Chromosome 5, # of SNPs: 295
Wed Oct 16 07:03:28 2019	Chromosome 6, # of SNPs: 283
Wed Oct 16 07:03:28 2019	Chromosome 7, # of SNPs: 245
Wed Oct 16 07:03:28 2019	Chromosome 8, # of SNPs: 234
Wed Oct 16 07:03:28 2019	Chromosome 9, # of SNPs: 202
Wed Oct 16 07:03:28 2019	Chromosome 10, # of SNPs: 224
Wed Oct 16 07:03:28 2019	Chromosome 11, # of SNPs: 223
Wed Oct 16 07:03:28 2019	Chromosome 12, # of SNPs: 208
Wed Oct 16 07:03:28 2019	Chromosome 13, # of SNPs: 172
Wed Oct 16 07:03:28 2019	Chromosome 14, # of SNPs: 147
Wed Oct 16 07:03:28 2019	Chromosome 15, # of SNPs: 121
Wed Oct 16 07:03:28 2019	Chromosome 16, # of SNPs: 129
Wed Oct 16 07:03:28 2019	Chromosome 17, # of SNPs: 116
Wed Oct 16 07:03:28 2019	Chromosome 18, # of SNPs: 129
Wed Oct 16 07:03:28 2019	Chromosome 19, # of SNPs: 73
Wed Oct 16 07:03:28 2019	Chromosome 20, # of SNPs: 106
Wed Oct 16 07:03:28 2019	Chromosome 21, # of SNPs: 62
Wed Oct 16 07:03:28 2019	Chromosome 22, # of SNPs: 51
Wed Oct 16 07:03:28 2019	Chromosome 23, # of SNPs: 204
Total # of SNPs selected:4570
FUNCTION: snpgdsBED2GDS
Start file conversion from PLINK BED to SNP GDS ...
    BED file: '/Library/Frameworks/R.framework/Versions/3.6/Resources/library/SNPRelate/extdata/plinkhapmap.bed.gz'
        SNP-major mode (Sample X SNP), 45.7K
    FAM file: '/Library/Frameworks/R.framework/Versions/3.6/Resources/library/SNPRelate/extdata/plinkhapmap.fam.gz'
    BIM file: '/Library/Frameworks/R.framework/Versions/3.6/Resources/library/SNPRelate/extdata/plinkhapmap.bim.gz'
Wed Oct 16 07:03:28 2019     (store sample id, snp id, position, and chromosome)
    start writing: 60 samples, 5000 SNPs ...

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Wed Oct 16 07:03:28 2019 	Done.
Optimize the access efficiency ...
Clean up the fragments of GDS file:
    open the file 'HapMap.gds' (98.1K)
    # of fragments: 38
    save to 'HapMap.gds.tmp'
    rename 'HapMap.gds.tmp' (97.8K, reduced: 240B)
    # of fragments: 18
FUNCTION: snpgdsClose
FUNCTION: snpgdsCombineGeno
Create a GDS genotype file:
The new dataset consists of 10 samples and 3000 SNPs
    write sample.id
    write snp.id
    write snp.rs.id
    write snp.position
    write snp.chromosome
    write snp.allele
SNP genotypes are stored in SNP-major mode (Sample X SNP).
Create a GDS genotype file:
The new dataset consists of 20 samples and 3000 SNPs
    write sample.id
    write snp.id
    write snp.rs.id
    write snp.position
    write snp.chromosome
    write snp.allele
SNP genotypes are stored in SNP-major mode (Sample X SNP).
Merge SNP GDS files:
    open 't1.gds' ...
        10 samples, 3000 SNPs
    open 't2.gds' ...
        20 samples, 3000 SNPs
Concatenating samples (mapping to the first GDS file) ...
    reference: 3000 SNPs (100.0%)
    file 2: 0 allele flips, 0 ambiguous locus/loci
        [no flip]: 3000
    create 'test.gds': 30 samples, 3000 SNPs
    FileFormat = SNP_ARRAY
    writing genotypes ...
Clean up the fragments of GDS file:
    open the file 'test.gds' (46.2K)
    # of fragments: 32
    save to 'test.gds.tmp'
    rename 'test.gds.tmp' (46.0K, reduced: 204B)
    # of fragments: 15
Done.
Create a GDS genotype file:
The new dataset consists of 279 samples and 100 SNPs
    write sample.id
    write snp.id
    write snp.rs.id
    write snp.position
    write snp.chromosome
    write snp.allele
SNP genotypes are stored in SNP-major mode (Sample X SNP).
Create a GDS genotype file:
The new dataset consists of 279 samples and 200 SNPs
    write sample.id
    write snp.id
    write snp.rs.id
    write snp.position
    write snp.chromosome
    write snp.allele
SNP genotypes are stored in SNP-major mode (Sample X SNP).
Merge SNP GDS files:
    open 't1.gds' ...
        279 samples, 100 SNPs
    open 't2.gds' ...
        279 samples, 200 SNPs
Concatenating SNPs ...
    create 'test.gds': 279 samples, 300 SNPs
    FileFormat = SNP_ARRAY
    writing genotypes ...
Clean up the fragments of GDS file:
    open the file 'test.gds' (19.1K)
    # of fragments: 32
    save to 'test.gds.tmp'
    rename 'test.gds.tmp' (18.9K, reduced: 204B)
    # of fragments: 15
Done.
FUNCTION: snpgdsCreateGeno
Principal Component Analysis (PCA) on genotypes:
Excluding 42 SNPs on non-autosomes
Excluding 0 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 279 samples, 958 SNPs
    using 1 (CPU) core
PCA:    the sum of all selected genotypes (0,1,2) = 264760
CPU capabilities: Double-Precision SSE2
Wed Oct 16 07:03:29 2019    (internal increment: 13960)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Wed Oct 16 07:03:29 2019    Begin (eigenvalues and eigenvectors)
Wed Oct 16 07:03:29 2019    Done.
FUNCTION: snpgdsCreateGenoSet
SNP pruning based on LD:
Excluding 365 SNPs on non-autosomes
Excluding 1 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 279 samples, 8,722 SNPs
    using 1 (CPU) core
    sliding window: 500,000 basepairs, Inf SNPs
    |LD| threshold: 0.2
    method: composite
Chromosome 1: 76.12%, 545/716
Chromosome 2: 72.78%, 540/742
Chromosome 3: 74.71%, 455/609
Chromosome 4: 73.49%, 413/562
Chromosome 5: 76.86%, 435/566
Chromosome 6: 75.75%, 428/565
Chromosome 7: 75.42%, 356/472
Chromosome 8: 71.11%, 347/488
Chromosome 9: 77.88%, 324/416
Chromosome 10: 74.12%, 358/483
Chromosome 11: 77.85%, 348/447
Chromosome 12: 76.81%, 328/427
Chromosome 13: 76.16%, 262/344
Chromosome 14: 76.60%, 216/282
Chromosome 15: 76.34%, 200/262
Chromosome 16: 72.66%, 202/278
Chromosome 17: 73.91%, 153/207
Chromosome 18: 73.68%, 196/266
Chromosome 19: 85.00%, 102/120
Chromosome 20: 71.62%, 164/229
Chromosome 21: 76.98%, 97/126
Chromosome 22: 75.86%, 88/116
6,557 markers are selected in total.
Create a GDS genotype file:
The new dataset consists of 279 samples and 6557 SNPs
    write sample.id
    write snp.id
    write snp.rs.id
    write snp.position
    write snp.chromosome
    write snp.allele
SNP genotypes are stored in SNP-major mode (Sample X SNP).
FUNCTION: snpgdsCutTree
Individual dissimilarity analysis on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 1 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 279 samples, 8,722 SNPs
    using 1 (CPU) core
Dissimilarity:    the sum of all selected genotypes (0,1,2) = 2446510
Dissimilarity:	Wed Oct 16 07:03:30 2019	0%
Dissimilarity:	Wed Oct 16 07:03:31 2019	100%
Determine groups by permutation (Z threshold: 15, outlier threshold: 5):
Create 3 groups.
Create 4 groups.
FUNCTION: snpgdsDiss
Individual dissimilarity analysis on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 1 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 279 samples, 8,722 SNPs
    using 1 (CPU) core
Dissimilarity:    the sum of all selected genotypes (0,1,2) = 2446510
Dissimilarity:	Wed Oct 16 07:03:33 2019	0%
Dissimilarity:	Wed Oct 16 07:03:34 2019	100%
Determine groups by permutation (Z threshold: 15, outlier threshold: 5):
Create 3 groups.
FUNCTION: snpgdsDrawTree
Individual dissimilarity analysis on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 1 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 279 samples, 8,722 SNPs
    using 1 (CPU) core
Dissimilarity:    the sum of all selected genotypes (0,1,2) = 2446510
Dissimilarity:	Wed Oct 16 07:03:35 2019	0%
Dissimilarity:	Wed Oct 16 07:03:36 2019	100%
Determine groups by permutation (Z threshold: 15, outlier threshold: 5):
Create 3 groups.
FUNCTION: snpgdsEIGMIX
Eigen-analysis on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 1 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 279 samples, 8,722 SNPs
    using 1 (CPU) core
Eigen-analysis:    the sum of all selected genotypes (0,1,2) = 2446510
CPU capabilities: Double-Precision SSE2
Wed Oct 16 07:03:37 2019    (internal increment: 13960)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 1s
Wed Oct 16 07:03:38 2019    Begin (eigenvalues and eigenvectors)
Wed Oct 16 07:03:38 2019    Done.
FUNCTION: snpgdsErrMsg
FUNCTION: snpgdsExampleFileName
FUNCTION: snpgdsFst
Fst estimation on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 1 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 279 samples, 8,722 SNPs
Method: Weir & Cockerham, 1984
# of Populations: 4
    CEU (92), HCB (47), JPT (47), YRI (93)
Fst estimation on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 1 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 279 samples, 8,722 SNPs
Method: Weir & Hill, 2002
# of Populations: 4
    CEU (92), HCB (47), JPT (47), YRI (93)
FUNCTION: snpgdsGDS2BED
Excluding 365 SNPs on non-autosomes
Excluding 1 SNP (monomorphic: TRUE, MAF: NaN, missing rate: 0.95)
Converting from GDS to PLINK binary PED:
Working space: 279 samples, 8722 SNPs
Output a BIM file.
Output a BED file ...
		Wed Oct 16 07:03:38 2019	0%
		Wed Oct 16 07:03:38 2019	100%
Done.
FUNCTION: snpgdsGDS2Eigen
Excluding 365 SNPs on non-autosomes
Excluding 1 SNP (monomorphic: TRUE, MAF: NaN, missing rate: 0.95)
Converting from GDS to EIGENSOFT:
	save to *.snp: 8722 snps
	save to *.ind: 279 samples
	Output: 	Wed Oct 16 07:03:38 2019	0%
	Output: 	Wed Oct 16 07:03:39 2019	100%
Done.
FUNCTION: snpgdsGDS2PED
Converting from GDS to PLINK PED:
	Output a MAP file DONE.
	Output a PED file ...
		Output: 	Wed Oct 16 07:03:39 2019	0%
		Output: 	Wed Oct 16 07:03:40 2019	100%
FUNCTION: snpgdsGEN2GDS
running snpgdsGEN2GDS ...
FUNCTION: snpgdsGRM
Genetic Relationship Matrix (GRM, GCTA):
Excluding 365 SNPs on non-autosomes
Excluding 1 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 279 samples, 8,722 SNPs
    using 1 (CPU) core
GRM Calculation:    the sum of all selected genotypes (0,1,2) = 2446510
CPU capabilities: Double-Precision SSE2
Wed Oct 16 07:03:40 2019    (internal increment: 13960)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 1s
Wed Oct 16 07:03:41 2019    Done.
Genetic Relationship Matrix (GRM, GCTA):
Excluding 365 SNPs on non-autosomes
Excluding 1 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 279 samples, 8,722 SNPs
    using 1 (CPU) core
GRM Calculation:    the sum of all selected genotypes (0,1,2) = 2446510
CPU capabilities: Double-Precision SSE2
Wed Oct 16 07:03:41 2019    (internal increment: 13960)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Saving to the GDS file:

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 1s
Wed Oct 16 07:03:42 2019    Done.
FUNCTION: snpgdsGetGeno
Genotype matrix: 1000 SNPs X 279 samples
Genotype matrix: 279 samples X 1000 SNPs
FUNCTION: snpgdsHCluster
Individual dissimilarity analysis on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 1 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 279 samples, 8,722 SNPs
    using 1 (CPU) core
Dissimilarity:    the sum of all selected genotypes (0,1,2) = 2446510
Dissimilarity:	Wed Oct 16 07:03:42 2019	0%
Dissimilarity:	Wed Oct 16 07:03:43 2019	100%
Determine groups by permutation (Z threshold: 15, outlier threshold: 5):
Create 3 groups.
FUNCTION: snpgdsHWE
Keeping 716 SNPs according to chromosome 1
Excluding 160 SNPs (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
FUNCTION: snpgdsIBDKING
IBD analysis (KING method of moment) on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 1,217 SNPs (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 92 samples, 7,506 SNPs
    using 1 (CPU) core
No family is specified, and all individuals are treated as singletons.
Relationship inference in the presence of population stratification.
KING IBD:    the sum of all selected genotypes (0,1,2) = 702139
CPU capabilities: Double-Precision SSE2
Wed Oct 16 07:03:45 2019    (internal increment: 65536)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Wed Oct 16 07:03:45 2019    Done.
IBD analysis (KING method of moment) on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 1,217 SNPs (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 92 samples, 7,506 SNPs
    using 1 (CPU) core
No family is specified, and all individuals are treated as singletons.
Relationship inference in the presence of population stratification.
KING IBD:    the sum of all selected genotypes (0,1,2) = 702139
CPU capabilities: Double-Precision SSE2
Wed Oct 16 07:03:45 2019    (internal increment: 65536)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Wed Oct 16 07:03:45 2019    Done.
IBD analysis (KING method of moment) on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 1,217 SNPs (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 92 samples, 7,506 SNPs
    using 1 (CPU) core
# of families: 20, and within- and between-family relationship are estimated differently.
Relationship inference in the presence of population stratification.
KING IBD:    the sum of all selected genotypes (0,1,2) = 702139
CPU capabilities: Double-Precision SSE2
Wed Oct 16 07:03:46 2019    (internal increment: 65536)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Wed Oct 16 07:03:46 2019    Done.
IBD analysis (KING method of moment) on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 1,217 SNPs (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 92 samples, 7,506 SNPs
    using 1 (CPU) core
Relationship inference in a homogeneous population.
KING IBD:    the sum of all selected genotypes (0,1,2) = 702139
Wed Oct 16 07:03:46 2019    (internal increment: 65536)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 1s
Wed Oct 16 07:03:47 2019    Done.
IBD analysis (KING method of moment) on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 1,217 SNPs (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 92 samples, 7,506 SNPs
    using 1 (CPU) core
Relationship inference in a homogeneous population.
KING IBD:    the sum of all selected genotypes (0,1,2) = 702139
Wed Oct 16 07:03:47 2019    (internal increment: 65536)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Wed Oct 16 07:03:47 2019    Done.
FUNCTION: snpgdsIBDMLE
SNP pruning based on LD:
Excluding 365 SNPs on non-autosomes
Excluding 1,581 SNPs (monomorphic: TRUE, MAF: 0.05, missing rate: 0.05)
Working space: 30 samples, 7,142 SNPs
    using 1 (CPU) core
    sliding window: 500,000 basepairs, Inf SNPs
    |LD| threshold: 0.2
    method: composite
Chromosome 1: 54.75%, 392/716
Chromosome 2: 54.31%, 403/742
Chromosome 3: 55.99%, 341/609
Chromosome 4: 56.58%, 318/562
Chromosome 5: 56.36%, 319/566
Chromosome 6: 52.74%, 298/565
Chromosome 7: 56.14%, 265/472
Chromosome 8: 51.84%, 253/488
Chromosome 9: 54.81%, 228/416
Chromosome 10: 49.90%, 241/483
Chromosome 11: 54.81%, 245/447
Chromosome 12: 54.57%, 233/427
Chromosome 13: 53.49%, 184/344
Chromosome 14: 56.03%, 158/282
Chromosome 15: 54.58%, 143/262
Chromosome 16: 54.68%, 152/278
Chromosome 17: 55.56%, 115/207
Chromosome 18: 55.64%, 148/266
Chromosome 19: 66.67%, 80/120
Chromosome 20: 53.28%, 122/229
Chromosome 21: 50.79%, 64/126
Chromosome 22: 51.72%, 60/116
4,762 markers are selected in total.
Identity-By-Descent analysis (MLE) on genotypes:
Excluding 8,838 SNPs (non-autosomes or non-selection)
Excluding 0 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 30 samples, 250 SNPs
    using 1 (CPU) core
MLE IBD:    the sum of all selected genotypes (0,1,2) = 7859
MLE IBD:	Wed Oct 16 07:03:47 2019	0%
MLE IBD:	Wed Oct 16 07:03:48 2019	100%
Identity-By-Descent analysis (MLE) on genotypes:
Excluding 8,838 SNPs (non-autosomes or non-selection)
Excluding 0 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 25 samples, 250 SNPs
    using 1 (CPU) core
Specifying allele frequencies, mean: 0.525, sd: 0.288
MLE IBD:    the sum of all selected genotypes (0,1,2) = 6545
MLE IBD:	Wed Oct 16 07:03:48 2019	0%
MLE IBD:	Wed Oct 16 07:03:48 2019	100%
FUNCTION: snpgdsIBDMLELogLik
SNP pruning based on LD:
Excluding 365 SNPs on non-autosomes
Excluding 1,581 SNPs (monomorphic: TRUE, MAF: 0.05, missing rate: 0.05)
Working space: 30 samples, 7,142 SNPs
    using 1 (CPU) core
    sliding window: 500,000 basepairs, Inf SNPs
    |LD| threshold: 0.2
    method: composite
Chromosome 1: 54.75%, 392/716
Chromosome 2: 54.31%, 403/742
Chromosome 3: 55.99%, 341/609
Chromosome 4: 56.58%, 318/562
Chromosome 5: 56.36%, 319/566
Chromosome 6: 52.74%, 298/565
Chromosome 7: 56.14%, 265/472
Chromosome 8: 51.84%, 253/488
Chromosome 9: 54.81%, 228/416
Chromosome 10: 49.90%, 241/483
Chromosome 11: 54.81%, 245/447
Chromosome 12: 54.57%, 233/427
Chromosome 13: 53.49%, 184/344
Chromosome 14: 56.03%, 158/282
Chromosome 15: 54.58%, 143/262
Chromosome 16: 54.68%, 152/278
Chromosome 17: 55.56%, 115/207
Chromosome 18: 55.64%, 148/266
Chromosome 19: 66.67%, 80/120
Chromosome 20: 53.28%, 122/229
Chromosome 21: 50.79%, 64/126
Chromosome 22: 51.72%, 60/116
4,762 markers are selected in total.
Identity-By-Descent analysis (MLE) on genotypes:
Excluding 8,838 SNPs (non-autosomes or non-selection)
Excluding 0 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 30 samples, 250 SNPs
    using 1 (CPU) core
MLE IBD:    the sum of all selected genotypes (0,1,2) = 7859
MLE IBD:	Wed Oct 16 07:03:48 2019	0%
MLE IBD:	Wed Oct 16 07:03:48 2019	100%
Identity-By-Descent analysis (MLE) on genotypes:
Excluding 8,838 SNPs (non-autosomes or non-selection)
Excluding 0 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 25 samples, 250 SNPs
    using 1 (CPU) core
Specifying allele frequencies, mean: 0.525, sd: 0.288
MLE IBD:    the sum of all selected genotypes (0,1,2) = 6545
MLE IBD:	Wed Oct 16 07:03:48 2019	0%
MLE IBD:	Wed Oct 16 07:03:49 2019	100%
FUNCTION: snpgdsIBDMoM
IBD analysis (PLINK method of moment) on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 1,217 SNPs (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 92 samples, 7,506 SNPs
    using 1 (CPU) core
PLINK IBD:    the sum of all selected genotypes (0,1,2) = 702139
Wed Oct 16 07:03:49 2019    (internal increment: 65536)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Wed Oct 16 07:03:49 2019    Done.
IBD analysis (PLINK method of moment) on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 563 SNPs (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 93 samples, 8,160 SNPs
    using 1 (CPU) core
PLINK IBD:    the sum of all selected genotypes (0,1,2) = 755648
Wed Oct 16 07:03:49 2019    (internal increment: 65536)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Wed Oct 16 07:03:49 2019    Done.
IBD analysis (PLINK method of moment) on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 563 SNPs (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 93 samples, 8,160 SNPs
    using 1 (CPU) core
Specifying allele frequencies, mean: 0.500, sd: 0.315
*** A correction factor based on allele count is not used, since the allele frequencies are specified.
PLINK IBD:    the sum of all selected genotypes (0,1,2) = 755648
Wed Oct 16 07:03:49 2019    (internal increment: 65536)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Wed Oct 16 07:03:49 2019    Done.
IBD analysis (PLINK method of moment) on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 563 SNPs (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 25 samples, 8,160 SNPs
    using 1 (CPU) core
Specifying allele frequencies, mean: 0.500, sd: 0.315
*** A correction factor based on allele count is not used, since the allele frequencies are specified.
PLINK IBD:    the sum of all selected genotypes (0,1,2) = 203285
Wed Oct 16 07:03:49 2019    (internal increment: 65536)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Wed Oct 16 07:03:49 2019    Done.
FUNCTION: snpgdsIBDSelection
IBD analysis (PLINK method of moment) on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 563 SNPs (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 93 samples, 8,160 SNPs
    using 1 (CPU) core
PLINK IBD:    the sum of all selected genotypes (0,1,2) = 755648
Wed Oct 16 07:03:49 2019    (internal increment: 65536)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Wed Oct 16 07:03:49 2019    Done.
FUNCTION: snpgdsIBS
Identity-By-State (IBS) analysis on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 1 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 279 samples, 8,722 SNPs
    using 1 (CPU) core
IBS:    the sum of all selected genotypes (0,1,2) = 2446510
Wed Oct 16 07:03:49 2019    (internal increment: 65536)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Wed Oct 16 07:03:49 2019    Done.
FUNCTION: snpgdsIBSNum
Identity-By-State (IBS) analysis on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 1 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 279 samples, 8,722 SNPs
    using 1 (CPU) core
IBS:    the sum of all selected genotypes (0,1,2) = 2446510
Wed Oct 16 07:03:50 2019    (internal increment: 65536)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Wed Oct 16 07:03:50 2019    Done.
FUNCTION: snpgdsIndInb
Estimating individual inbreeding coefficients:
Excluding 365 SNPs on non-autosomes
Excluding 1 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 279 samples, 8,722 SNPs
    using 1 (CPU) core

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
FUNCTION: snpgdsIndInbCoef
FUNCTION: snpgdsIndivBeta
Individual Inbreeding and Relatedness (beta estimator):
Excluding 365 SNPs on non-autosomes
Excluding 1 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 279 samples, 8,722 SNPs
    using 1 (CPU) core
Individual Beta:    the sum of all selected genotypes (0,1,2) = 2446510
CPU capabilities: Double-Precision SSE2
Wed Oct 16 07:03:50 2019    (internal increment: 65536)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 1s
Wed Oct 16 07:03:51 2019    Done.
FUNCTION: snpgdsLDMat
Linkage Disequilibrium (LD) estimation on genotypes:
Working space: 279 samples, 203 SNPs
    using 1 (CPU) core.
    method: composite
LD matrix:    the sum of all selected genotypes (0,1,2) = 56582
Linkage Disequilibrium (LD) estimation on genotypes:
Working space: 279 samples, 203 SNPs
    using 1 (CPU) core.
    sliding window size: 203 
    method: composite
LD matrix:    the sum of all selected genotypes (0,1,2) = 56582
FUNCTION: snpgdsLDpair
FUNCTION: snpgdsLDpruning
SNP pruning based on LD:
Excluding 365 SNPs on non-autosomes
Excluding 1 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 279 samples, 8,722 SNPs
    using 1 (CPU) core
    sliding window: 500,000 basepairs, Inf SNPs
    |LD| threshold: 0.2
    method: composite
Chromosome 1: 76.12%, 545/716
Chromosome 2: 72.78%, 540/742
Chromosome 3: 74.71%, 455/609
Chromosome 4: 73.49%, 413/562
Chromosome 5: 76.86%, 435/566
Chromosome 6: 75.75%, 428/565
Chromosome 7: 75.42%, 356/472
Chromosome 8: 71.11%, 347/488
Chromosome 9: 77.88%, 324/416
Chromosome 10: 74.12%, 358/483
Chromosome 11: 77.85%, 348/447
Chromosome 12: 76.81%, 328/427
Chromosome 13: 76.16%, 262/344
Chromosome 14: 76.60%, 216/282
Chromosome 15: 76.34%, 200/262
Chromosome 16: 72.66%, 202/278
Chromosome 17: 73.91%, 153/207
Chromosome 18: 73.68%, 196/266
Chromosome 19: 85.00%, 102/120
Chromosome 20: 71.62%, 164/229
Chromosome 21: 76.98%, 97/126
Chromosome 22: 75.86%, 88/116
6,557 markers are selected in total.
FUNCTION: snpgdsMergeGRM
Genetic Relationship Matrix (GRM, GCTA):
Excluding 2,288 SNPs (non-autosomes or non-selection)
Excluding 0 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 279 samples, 6,800 SNPs
    using 1 (CPU) core
GRM Calculation:    the sum of all selected genotypes (0,1,2) = 1908966
CPU capabilities: Double-Precision SSE2
Wed Oct 16 07:03:51 2019    (internal increment: 13960)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 1s
Wed Oct 16 07:03:52 2019    Done.
Genetic Relationship Matrix (GRM, GCTA):
Excluding 5,688 SNPs (non-autosomes or non-selection)
Excluding 0 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 279 samples, 3,400 SNPs
    using 1 (CPU) core
GRM Calculation:    the sum of all selected genotypes (0,1,2) = 951558
CPU capabilities: Double-Precision SSE2
Wed Oct 16 07:03:52 2019    (internal increment: 13960)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 1s
Saving to the GDS file:

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Wed Oct 16 07:03:53 2019    Done.
Genetic Relationship Matrix (GRM, GCTA):
Excluding 5,688 SNPs (non-autosomes or non-selection)
Excluding 0 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 279 samples, 3,400 SNPs
    using 1 (CPU) core
GRM Calculation:    the sum of all selected genotypes (0,1,2) = 957408
CPU capabilities: Double-Precision SSE2
Wed Oct 16 07:03:53 2019    (internal increment: 13960)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 1s
Saving to the GDS file:

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Wed Oct 16 07:03:54 2019    Done.
GRM merging:
    open 'tmp1.gds' (3,400 variants)
    open 'tmp2.gds' (3,400 variants)
Weight: 0.5, 0.5
Output: tmp.gds

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 1s
GRM merging:
    open 'tmp1.gds' (3,400 variants)
    open 'tmp2.gds' (3,400 variants)
Weight: 0.5, 0.5

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
FUNCTION: snpgdsOpen
FUNCTION: snpgdsOption
FUNCTION: snpgdsPCA
Principal Component Analysis (PCA) on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 1 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 279 samples, 8,722 SNPs
    using 1 (CPU) core
PCA:    the sum of all selected genotypes (0,1,2) = 2446510
CPU capabilities: Double-Precision SSE2
Wed Oct 16 07:03:55 2019    (internal increment: 13960)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 1s
Wed Oct 16 07:03:56 2019    Begin (eigenvalues and eigenvectors)
Wed Oct 16 07:03:56 2019    Done.
FUNCTION: snpgdsPCACorr
Principal Component Analysis (PCA) on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 1 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 279 samples, 8,722 SNPs
    using 1 (CPU) core
PCA:    the sum of all selected genotypes (0,1,2) = 2446510
CPU capabilities: Double-Precision SSE2
Wed Oct 16 07:03:56 2019    (internal increment: 13960)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Wed Oct 16 07:03:56 2019    Begin (eigenvalues and eigenvectors)
Wed Oct 16 07:03:56 2019    Done.
SNP Correlation:
Working space: 279 samples, 9088 SNPs
    using 1 (CPU) core
    using the top 4 eigenvectors
Correlation:    the sum of all selected genotypes (0,1,2) = 2553065
Wed Oct 16 07:03:57 2019    (internal increment: 65536)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Wed Oct 16 07:03:57 2019    Done.
SNP Correlation:
Working space: 279 samples, 9088 SNPs
    using 1 (CPU) core
    using the top 4 eigenvectors
Creating 'test.gds' ...
Correlation:    the sum of all selected genotypes (0,1,2) = 2553065
Wed Oct 16 07:03:57 2019

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Wed Oct 16 07:03:57 2019    Done.
FUNCTION: snpgdsPCASNPLoading
Principal Component Analysis (PCA) on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 1 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 279 samples, 8,722 SNPs
    using 1 (CPU) core
PCA:    the sum of all selected genotypes (0,1,2) = 2446510
CPU capabilities: Double-Precision SSE2
Wed Oct 16 07:03:57 2019    (internal increment: 13960)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Wed Oct 16 07:03:57 2019    Begin (eigenvalues and eigenvectors)
Wed Oct 16 07:03:57 2019    Done.
SNP loading:
Working space: 279 samples, 8722 SNPs
    using 1 (CPU) core
    using the top 8 eigenvectors
SNP Loading:    the sum of all selected genotypes (0,1,2) = 2446510
Wed Oct 16 07:03:57 2019    (internal increment: 65536)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 1s
Wed Oct 16 07:03:58 2019    Done.
FUNCTION: snpgdsPCASampLoading
Principal Component Analysis (PCA) on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 1 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 279 samples, 8,722 SNPs
    using 1 (CPU) core
PCA:    the sum of all selected genotypes (0,1,2) = 2446510
CPU capabilities: Double-Precision SSE2
Wed Oct 16 07:03:58 2019    (internal increment: 13960)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Wed Oct 16 07:03:58 2019    Begin (eigenvalues and eigenvectors)
Wed Oct 16 07:03:58 2019    Done.
SNP loading:
Working space: 279 samples, 8722 SNPs
    using 1 (CPU) core
    using the top 8 eigenvectors
SNP Loading:    the sum of all selected genotypes (0,1,2) = 2446510
Wed Oct 16 07:03:58 2019    (internal increment: 65536)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Wed Oct 16 07:03:58 2019    Done.
Sample loading:
Working space: 100 samples, 8722 SNPs
    using 1 (CPU) core
    using the top 8 eigenvectors
Sample Loading:    the sum of all selected genotypes (0,1,2) = 878146
Wed Oct 16 07:03:58 2019    (internal increment: 65536)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Wed Oct 16 07:03:58 2019    Done.
FUNCTION: snpgdsPED2GDS
Converting from GDS to PLINK PED:
	Output a MAP file DONE.
	Output a PED file ...
		Output: 	Wed Oct 16 07:03:58 2019	0%
		Output: 	Wed Oct 16 07:03:59 2019	100%
PLINK PED/MAP to GDS Format:
Import 9088 variants from 'tmp.map'
Chromosome:
  1  10  11  12  13  14  15  16  17  18  19   2  20  21  22   3   4   5   6   7 
716 483 447 427 344 282 262 278 207 266 120 742 229 126 116 609 562 566 565 472 
  8   9   X 
488 416 365 
Reading 'tmp.ped'
Output: 'test.gds'
Import 279 samples
Transpose the genotypic matrix ...
Done.
Optimize the access efficiency ...
Clean up the fragments of GDS file:
    open the file 'test.gds' (1.3M)
    # of fragments: 50
    save to 'test.gds.tmp'
    rename 'test.gds.tmp' (711.4K, reduced: 618.7K)
    # of fragments: 26
FUNCTION: snpgdsPairIBD
SNP pruning based on LD:
Excluding 365 SNPs on non-autosomes
Excluding 1,646 SNPs (monomorphic: TRUE, MAF: 0.05, missing rate: 0.05)
Working space: 93 samples, 7,077 SNPs
    using 1 (CPU) core
    sliding window: 500,000 basepairs, Inf SNPs
    |LD| threshold: 0.2
    method: composite
Chromosome 1: 62.29%, 446/716
Chromosome 2: 62.67%, 465/742
Chromosome 3: 59.93%, 365/609
Chromosome 4: 64.23%, 361/562
Chromosome 5: 62.37%, 353/566
Chromosome 6: 59.82%, 338/565
Chromosome 7: 63.14%, 298/472
Chromosome 8: 57.58%, 281/488
Chromosome 9: 62.98%, 262/416
Chromosome 10: 60.46%, 292/483
Chromosome 11: 63.09%, 282/447
Chromosome 12: 62.76%, 268/427
Chromosome 13: 63.08%, 217/344
Chromosome 14: 63.83%, 180/282
Chromosome 15: 63.74%, 167/262
Chromosome 16: 62.23%, 173/278
Chromosome 17: 65.70%, 136/207
Chromosome 18: 59.40%, 158/266
Chromosome 19: 68.33%, 82/120
Chromosome 20: 66.38%, 152/229
Chromosome 21: 61.11%, 77/126
Chromosome 22: 57.76%, 67/116
5,420 markers are selected in total.
Identity-By-Descent analysis (MLE) on genotypes:
Excluding 8,838 SNPs (non-autosomes or non-selection)
Excluding 0 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 25 samples, 250 SNPs
    using 1 (CPU) core
Specifying allele frequencies, mean: 0.486, sd: 0.284
MLE IBD:    the sum of all selected genotypes (0,1,2) = 6112
MLE IBD:	Wed Oct 16 07:04:00 2019	0%
MLE IBD:	Wed Oct 16 07:04:01 2019	100%
IBD analysis (PLINK method of moment) on genotypes:
Excluding 8,838 SNPs (non-autosomes or non-selection)
Excluding 0 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 25 samples, 250 SNPs
    using 1 (CPU) core
Specifying allele frequencies, mean: 0.486, sd: 0.284
*** A correction factor based on allele count is not used, since the allele frequencies are specified.
PLINK IBD:    the sum of all selected genotypes (0,1,2) = 6112
Wed Oct 16 07:04:01 2019    (internal increment: 65536)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Wed Oct 16 07:04:01 2019    Done.
Identity-By-Descent analysis (MLE) on genotypes:
Excluding 8,838 SNPs (non-autosomes or non-selection)
Excluding 0 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 25 samples, 250 SNPs
    using 1 (CPU) core
Specifying allele frequencies, mean: 0.486, sd: 0.284
MLE IBD:    the sum of all selected genotypes (0,1,2) = 6112
MLE IBD:	Wed Oct 16 07:04:01 2019	0%
MLE IBD:	Wed Oct 16 07:04:01 2019	100%
Genotype matrix: 250 SNPs X 25 samples
[1] -370.7482
[1] -402.2141
[1] -383.7897
[1] -377.9084
[1] -381.3139
[1] -397.5581
[1] -378.3344
[1] -370.703
[1] -376.103
[1] -377.7911
[1] -375.5425
[1] -373.13
[1] -383.6992
[1] -393.5194
[1] -371.9843
[1] -369.6468
[1] -374.5139
[1] -377.841
[1] -387.5622
[1] -377.1646
[1] -377.4659
[1] -375.2204
[1] -372.0639
[1] -379.816
FUNCTION: snpgdsPairIBDMLELogLik
SNP pruning based on LD:
Excluding 365 SNPs on non-autosomes
Excluding 1,646 SNPs (monomorphic: TRUE, MAF: 0.05, missing rate: 0.05)
Working space: 93 samples, 7,077 SNPs
    using 1 (CPU) core
    sliding window: 500,000 basepairs, Inf SNPs
    |LD| threshold: 0.2
    method: composite
Chromosome 1: 62.29%, 446/716
Chromosome 2: 62.67%, 465/742
Chromosome 3: 59.93%, 365/609
Chromosome 4: 64.23%, 361/562
Chromosome 5: 62.37%, 353/566
Chromosome 6: 59.82%, 338/565
Chromosome 7: 63.14%, 298/472
Chromosome 8: 57.58%, 281/488
Chromosome 9: 62.98%, 262/416
Chromosome 10: 60.46%, 292/483
Chromosome 11: 63.09%, 282/447
Chromosome 12: 62.76%, 268/427
Chromosome 13: 63.08%, 217/344
Chromosome 14: 63.83%, 180/282
Chromosome 15: 63.74%, 167/262
Chromosome 16: 62.23%, 173/278
Chromosome 17: 65.70%, 136/207
Chromosome 18: 59.40%, 158/266
Chromosome 19: 68.33%, 82/120
Chromosome 20: 66.38%, 152/229
Chromosome 21: 61.11%, 77/126
Chromosome 22: 57.76%, 67/116
5,420 markers are selected in total.
Identity-By-Descent analysis (MLE) on genotypes:
Excluding 8,838 SNPs (non-autosomes or non-selection)
Excluding 0 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 25 samples, 250 SNPs
    using 1 (CPU) core
Specifying allele frequencies, mean: 0.486, sd: 0.284
MLE IBD:    the sum of all selected genotypes (0,1,2) = 6112
MLE IBD:	Wed Oct 16 07:04:02 2019	0%
MLE IBD:	Wed Oct 16 07:04:02 2019	100%
IBD analysis (PLINK method of moment) on genotypes:
Excluding 8,838 SNPs (non-autosomes or non-selection)
Excluding 0 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 25 samples, 250 SNPs
    using 1 (CPU) core
Specifying allele frequencies, mean: 0.486, sd: 0.284
*** A correction factor based on allele count is not used, since the allele frequencies are specified.
PLINK IBD:    the sum of all selected genotypes (0,1,2) = 6112
Wed Oct 16 07:04:02 2019    (internal increment: 65536)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Wed Oct 16 07:04:02 2019    Done.
Genotype matrix: 250 SNPs X 25 samples
[1] -370.7482
[1] -402.2141
[1] -383.7897
[1] -377.9084
[1] -381.3139
[1] -397.5581
[1] -378.3344
[1] -370.703
[1] -376.103
[1] -377.7911
[1] -375.5425
[1] -373.13
[1] -383.6992
[1] -393.5194
[1] -371.9843
[1] -369.6468
[1] -374.5139
[1] -377.841
[1] -387.5622
[1] -377.1646
[1] -377.4659
[1] -375.2204
[1] -372.0639
[1] -379.816
FUNCTION: snpgdsPairScore
Excluding 365 SNPs on non-autosomes
Working space: 120 samples, 8723 SNPs
Method: IBS
Genotype Score:    the sum of all selected genotypes (0,1,2) = 1050236
Working space: 120 samples, 8723 SNPs
Method: IBS
Genotype Score:    the sum of all selected genotypes (0,1,2) = 1050236
Working space: 120 samples, 8723 SNPs
Method: IBS
Genotype Score:    the sum of all selected genotypes (0,1,2) = 1050236
Working space: 120 samples, 8723 SNPs
Method: IBS
Genotype Score:    the sum of all selected genotypes (0,1,2) = 1050236
Working space: 120 samples, 8723 SNPs
Method: IBS
Output: /Users/biocbuild/bbs-3.9-bioc/meat/SNPRelate.Rcheck/tests/tmp.gds
Genotype Score:    the sum of all selected genotypes (0,1,2) = 1050236
FUNCTION: snpgdsSNPList
FUNCTION: snpgdsSNPListClass
FUNCTION: snpgdsSNPListIntersect
FUNCTION: snpgdsSNPRateFreq
FUNCTION: snpgdsSampMissRate
FUNCTION: snpgdsSelectSNP
Excluding 365 SNPs on non-autosomes
Excluding 1,221 SNPs (monomorphic: TRUE, MAF: 0.05, missing rate: 0.95)
FUNCTION: snpgdsSlidingWindow
Sliding Window Analysis:
Excluding 8 SNPs (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 279 samples, 9,080 SNPs
    using 1 (CPU) core
    window size: 500000, shift: 100000 (basepair)
Chromosome Set: 1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23
Wed Oct 16 07:04:03 2019, Chromosome 1 (716 SNPs), 2448 windows
Wed Oct 16 07:04:03 2019, Chromosome 2 (742 SNPs), 2416 windows
Wed Oct 16 07:04:04 2019, Chromosome 3 (609 SNPs), 1985 windows
Wed Oct 16 07:04:04 2019, Chromosome 4 (562 SNPs), 1894 windows
Wed Oct 16 07:04:04 2019, Chromosome 5 (566 SNPs), 1797 windows
Wed Oct 16 07:04:04 2019, Chromosome 6 (565 SNPs), 1694 windows
Wed Oct 16 07:04:04 2019, Chromosome 7 (472 SNPs), 1573 windows
Wed Oct 16 07:04:04 2019, Chromosome 8 (488 SNPs), 1445 windows
Wed Oct 16 07:04:05 2019, Chromosome 9 (416 SNPs), 1393 windows
Wed Oct 16 07:04:05 2019, Chromosome 10 (483 SNPs), 1343 windows
Wed Oct 16 07:04:05 2019, Chromosome 11 (447 SNPs), 1338 windows
Wed Oct 16 07:04:05 2019, Chromosome 12 (427 SNPs), 1316 windows
Wed Oct 16 07:04:05 2019, Chromosome 13 (344 SNPs), 948 windows
Wed Oct 16 07:04:05 2019, Chromosome 14 (281 SNPs), 847 windows
Wed Oct 16 07:04:05 2019, Chromosome 15 (262 SNPs), 774 windows
Wed Oct 16 07:04:05 2019, Chromosome 16 (278 SNPs), 873 windows
Wed Oct 16 07:04:05 2019, Chromosome 17 (207 SNPs), 773 windows
Wed Oct 16 07:04:05 2019, Chromosome 18 (266 SNPs), 753 windows
Wed Oct 16 07:04:05 2019, Chromosome 19 (120 SNPs), 627 windows
Wed Oct 16 07:04:05 2019, Chromosome 20 (229 SNPs), 602 windows
Wed Oct 16 07:04:05 2019, Chromosome 21 (126 SNPs), 311 windows
Wed Oct 16 07:04:05 2019, Chromosome 22 (116 SNPs), 312 windows
Wed Oct 16 07:04:05 2019, Chromosome 23 (358 SNPs), 1507 windows
Wed Oct 16 07:04:05 2019 	Done.
FUNCTION: snpgdsSummary
The file name: /Library/Frameworks/R.framework/Versions/3.6/Resources/library/SNPRelate/extdata/hapmap_geno.gds 
The total number of samples: 279 
The total number of SNPs: 9088 
SNP genotypes are stored in SNP-major mode (Sample X SNP).
FUNCTION: snpgdsTranspose
The file name: /Users/biocbuild/bbs-3.9-bioc/meat/SNPRelate.Rcheck/tests/test.gds 
The total number of samples: 279 
The total number of SNPs: 9088 
SNP genotypes are stored in SNP-major mode (Sample X SNP).
SNP genotypes: 279 samples, 9088 SNPs
Genotype matrix is being transposed ...
Clean up the fragments of GDS file:
    open the file 'test.gds' (1.3M)
    # of fragments: 28
    save to 'test.gds.tmp'
    rename 'test.gds.tmp' (709.6K, reduced: 619.1K)
    # of fragments: 26
The file name: /Users/biocbuild/bbs-3.9-bioc/meat/SNPRelate.Rcheck/tests/test.gds 
The total number of samples: 279 
The total number of SNPs: 9088 
SNP genotypes are stored in individual-major mode (SNP X Sample).
FUNCTION: snpgdsVCF2GDS
##fileformat=VCFv4.1
##fileDate=20090805
##source=myImputationProgramV3.1
##reference=file:///seq/references/1000GenomesPilot-NCBI36.fasta
##contig=
##phasing=partial
##INFO=
##INFO=
##INFO=
##INFO=
##INFO=
##INFO=
##FILTER=
##FILTER=
##FORMAT=
##FORMAT=
##FORMAT=
##FORMAT=
#CHROM	POS	ID	REF	ALT	QUAL	FILTER	INFO	FORMAT	NA00001	NA00002	NA00003
20	14370	rs6054257	G	A	29	PASS	NS=3;DP=14;AF=0.5;DB;H2	GT:GQ:DP:HQ	0|0:48:1:51,51	1|0:48:8:51,51	1/1:43:5:.,.
20	17330	.	T	A	3	q10	NS=3;DP=11;AF=0.017	GT:GQ:DP:HQ	0|0:49:3:58,50	0|1:3:5:65,3	0/0:41:3
20	1110696	rs6040355	A	G,T	67	PASS	NS=2;DP=10;AF=0.333,0.667;AA=T;DB	GT:GQ:DP:HQ	1|2:21:6:23,27	2|1:2:0:18,2	2/2:35:4
20	1230237	.	T	.	47	PASS	NS=3;DP=13;AA=T	GT:GQ:DP:HQ	0|0:54:7:56,60	0|0:48:4:51,51	0/0:61:2
20	1234567	microsat1	GTC	G,GTCT	50	PASS	NS=3;DP=9;AA=G	GT:GQ:DP	0/1:35:4	0/2:17:2	1/1:40:3
Start file conversion from VCF to SNP GDS ...
Method: exacting biallelic SNPs
Number of samples: 3
Parsing "/Library/Frameworks/R.framework/Versions/3.6/Resources/library/SNPRelate/extdata/sequence.vcf" ...
	import 2 variants.
+ genotype   { Bit2 3x2, 2B } *
Optimize the access efficiency ...
Clean up the fragments of GDS file:
    open the file 'test1.gds' (2.9K)
    # of fragments: 46
    save to 'test1.gds.tmp'
    rename 'test1.gds.tmp' (2.6K, reduced: 312B)
    # of fragments: 20
The file name: /Users/biocbuild/bbs-3.9-bioc/meat/SNPRelate.Rcheck/tests/test1.gds 
The total number of samples: 3 
The total number of SNPs: 2 
SNP genotypes are stored in SNP-major mode (Sample X SNP).
Start file conversion from VCF to SNP GDS ...
Method: exacting biallelic SNPs
Number of samples: 3
Parsing "/Library/Frameworks/R.framework/Versions/3.6/Resources/library/SNPRelate/extdata/sequence.vcf" ...
	import 2 variants.
+ genotype   { Bit2 3x2, 2B } *
SNP genotypes: 3 samples, 2 SNPs
Genotype matrix is being transposed ...
Optimize the access efficiency ...
Clean up the fragments of GDS file:
    open the file 'test2.gds' (3.0K)
    # of fragments: 48
    save to 'test2.gds.tmp'
    rename 'test2.gds.tmp' (2.6K, reduced: 417B)
    # of fragments: 20
The file name: /Users/biocbuild/bbs-3.9-bioc/meat/SNPRelate.Rcheck/tests/test2.gds 
The total number of samples: 3 
The total number of SNPs: 2 
SNP genotypes are stored in individual-major mode (SNP X Sample).
Start file conversion from VCF to SNP GDS ...
Method: dosage (0,1,2) of reference allele for all variant sites
Number of samples: 3
Parsing "/Library/Frameworks/R.framework/Versions/3.6/Resources/library/SNPRelate/extdata/sequence.vcf" ...
	import 5 variants.
+ genotype   { Bit2 3x5, 4B } *
SNP genotypes: 3 samples, 5 SNPs
Genotype matrix is being transposed ...
Optimize the access efficiency ...
Clean up the fragments of GDS file:
    open the file 'test3.gds' (3.1K)
    # of fragments: 48
    save to 'test3.gds.tmp'
    rename 'test3.gds.tmp' (2.7K, reduced: 419B)
    # of fragments: 20
Some of 'snp.allele' are not standard (e.g., A/G,T).
The file name: /Users/biocbuild/bbs-3.9-bioc/meat/SNPRelate.Rcheck/tests/test3.gds 
The total number of samples: 3 
The total number of SNPs: 5 
SNP genotypes are stored in individual-major mode (SNP X Sample).
The number of valid samples: 3 
The number of biallelic unique SNPs: 2 
Start file conversion from VCF to SNP GDS ...
Method: dosage (0,1,2) of reference allele for all variant sites
Number of samples: 3
Parsing "/Library/Frameworks/R.framework/Versions/3.6/Resources/library/SNPRelate/extdata/sequence.vcf" ...
	import 5 variants.
+ genotype   { Bit2 3x5, 4B } *
Optimize the access efficiency ...
Clean up the fragments of GDS file:
    open the file 'test4.gds' (3.0K)
    # of fragments: 46
    save to 'test4.gds.tmp'
    rename 'test4.gds.tmp' (2.7K, reduced: 312B)
    # of fragments: 20
Some of 'snp.allele' are not standard (e.g., A/G,T).
The file name: /Users/biocbuild/bbs-3.9-bioc/meat/SNPRelate.Rcheck/tests/test4.gds 
The total number of samples: 3 
The total number of SNPs: 5 
SNP genotypes are stored in SNP-major mode (Sample X SNP).
The number of valid samples: 3 
The number of biallelic unique SNPs: 2 
Start file conversion from VCF to SNP GDS ...
Method: dosage (0,1,2) of reference allele for all variant sites
Number of samples: 3
Parsing "/Library/Frameworks/R.framework/Versions/3.6/Resources/library/SNPRelate/extdata/sequence.vcf" ...
	import 5 variants.
+ genotype   { Bit2 3x5, 4B } *
Optimize the access efficiency ...
Clean up the fragments of GDS file:
    open the file 'test5.gds' (3.0K)
    # of fragments: 46
    save to 'test5.gds.tmp'
    rename 'test5.gds.tmp' (2.7K, reduced: 312B)
    # of fragments: 20
Some of 'snp.allele' are not standard (e.g., T/A,G).
The file name: /Users/biocbuild/bbs-3.9-bioc/meat/SNPRelate.Rcheck/tests/test5.gds 
The total number of samples: 3 
The total number of SNPs: 5 
SNP genotypes are stored in SNP-major mode (Sample X SNP).
The number of valid samples: 3 
The number of biallelic unique SNPs: 2 
FUNCTION: snpgdsVCF2GDS_R
##fileformat=VCFv4.1
##fileDate=20090805
##source=myImputationProgramV3.1
##reference=file:///seq/references/1000GenomesPilot-NCBI36.fasta
##contig=
##phasing=partial
##INFO=
##INFO=
##INFO=
##INFO=
##INFO=
##INFO=
##FILTER=
##FILTER=
##FORMAT=
##FORMAT=
##FORMAT=
##FORMAT=
#CHROM	POS	ID	REF	ALT	QUAL	FILTER	INFO	FORMAT	NA00001	NA00002	NA00003
20	14370	rs6054257	G	A	29	PASS	NS=3;DP=14;AF=0.5;DB;H2	GT:GQ:DP:HQ	0|0:48:1:51,51	1|0:48:8:51,51	1/1:43:5:.,.
20	17330	.	T	A	3	q10	NS=3;DP=11;AF=0.017	GT:GQ:DP:HQ	0|0:49:3:58,50	0|1:3:5:65,3	0/0:41:3
20	1110696	rs6040355	A	G,T	67	PASS	NS=2;DP=10;AF=0.333,0.667;AA=T;DB	GT:GQ:DP:HQ	1|2:21:6:23,27	2|1:2:0:18,2	2/2:35:4
20	1230237	.	T	.	47	PASS	NS=3;DP=13;AA=T	GT:GQ:DP:HQ	0|0:54:7:56,60	0|0:48:4:51,51	0/0:61:2
20	1234567	microsat1	GTC	G,GTCT	50	PASS	NS=3;DP=9;AA=G	GT:GQ:DP	0/1:35:4	0/2:17:2	1/1:40:3
Start snpgdsVCF2GDS ...
	Extracting bi-allelic and polymorhpic SNPs.
	Scanning ...
	file: /Library/Frameworks/R.framework/Versions/3.6/Resources/library/SNPRelate/extdata/sequence.vcf
	content: 5 rows x 12 columns
Wed Oct 16 07:04:07 2019 	store sample id, snp id, position, and chromosome.
	start writing: 3 samples, 2 SNPs ...
	file: /Library/Frameworks/R.framework/Versions/3.6/Resources/library/SNPRelate/extdata/sequence.vcf
[1] 1
Wed Oct 16 07:04:07 2019 	Done.
The file name: /Users/biocbuild/bbs-3.9-bioc/meat/SNPRelate.Rcheck/tests/test1.gds 
The total number of samples: 3 
The total number of SNPs: 2 
SNP genotypes are stored in SNP-major mode (Sample X SNP).
Start snpgdsVCF2GDS ...
	Extracting bi-allelic and polymorhpic SNPs.
	Scanning ...
	file: /Library/Frameworks/R.framework/Versions/3.6/Resources/library/SNPRelate/extdata/sequence.vcf
	content: 5 rows x 12 columns
Wed Oct 16 07:04:07 2019 	store sample id, snp id, position, and chromosome.
	start writing: 3 samples, 2 SNPs ...
	file: /Library/Frameworks/R.framework/Versions/3.6/Resources/library/SNPRelate/extdata/sequence.vcf
[1] 1
Wed Oct 16 07:04:07 2019 	Done.
The file name: /Users/biocbuild/bbs-3.9-bioc/meat/SNPRelate.Rcheck/tests/test2.gds 
The total number of samples: 3 
The total number of SNPs: 2 
SNP genotypes are stored in SNP-major mode (Sample X SNP).
Start snpgdsVCF2GDS ...
	Storing dosage of the reference allele for all variant sites, including bi-allelic SNPs, multi-allelic SNPs, indels and structural variants.
	Scanning ...
	file: /Library/Frameworks/R.framework/Versions/3.6/Resources/library/SNPRelate/extdata/sequence.vcf
	content: 5 rows x 12 columns
Wed Oct 16 07:04:07 2019 	store sample id, snp id, position, and chromosome.
	start writing: 3 samples, 5 SNPs ...
	file: /Library/Frameworks/R.framework/Versions/3.6/Resources/library/SNPRelate/extdata/sequence.vcf
Wed Oct 16 07:04:07 2019 	Done.
Some of 'snp.allele' are not standard (e.g., A/G,T).
The file name: /Users/biocbuild/bbs-3.9-bioc/meat/SNPRelate.Rcheck/tests/test3.gds 
The total number of samples: 3 
The total number of SNPs: 5 
SNP genotypes are stored in SNP-major mode (Sample X SNP).
The number of valid samples: 3 
The number of biallelic unique SNPs: 2 
Start snpgdsVCF2GDS ...
	Storing dosage of the reference allele for all variant sites, including bi-allelic SNPs, multi-allelic SNPs, indels and structural variants.
	Scanning ...
	file: /Library/Frameworks/R.framework/Versions/3.6/Resources/library/SNPRelate/extdata/sequence.vcf
	content: 5 rows x 12 columns
Wed Oct 16 07:04:07 2019 	store sample id, snp id, position, and chromosome.
	start writing: 3 samples, 5 SNPs ...
	file: /Library/Frameworks/R.framework/Versions/3.6/Resources/library/SNPRelate/extdata/sequence.vcf
Wed Oct 16 07:04:07 2019 	Done.
Some of 'snp.allele' are not standard (e.g., A/G,T).
The file name: /Users/biocbuild/bbs-3.9-bioc/meat/SNPRelate.Rcheck/tests/test4.gds 
The total number of samples: 3 
The total number of SNPs: 5 
SNP genotypes are stored in SNP-major mode (Sample X SNP).
The number of valid samples: 3 
The number of biallelic unique SNPs: 2 
SNP Correlation:
Working space: 90 samples, 9088 SNPs
    using 1 (CPU) core
    using the top 2 eigenvectors
Correlation:    the sum of all selected genotypes (0,1,2) = 824424
Wed Oct 16 07:04:09 2019    (internal increment: 65536)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Wed Oct 16 07:04:09 2019    Done.
SNP Correlation:
Working space: 90 samples, 9088 SNPs
    using 1 (CPU) core
    using the top 2 eigenvectors
Creating 'test.gds' ...
Correlation:    the sum of all selected genotypes (0,1,2) = 824424
Wed Oct 16 07:04:09 2019

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Wed Oct 16 07:04:09 2019    Done.
SNP loading:
Working space: 90 samples, 8695 SNPs
    using 1 (CPU) core
    using the top 8 eigenvectors
SNP Loading:    the sum of all selected genotypes (0,1,2) = 787449
Wed Oct 16 07:04:09 2019    (internal increment: 65536)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Wed Oct 16 07:04:09 2019    Done.
Sample loading:
Working space: 100 samples, 8695 SNPs
    using 1 (CPU) core
    using the top 8 eigenvectors
Sample Loading:    the sum of all selected genotypes (0,1,2) = 875255
Wed Oct 16 07:04:09 2019    (internal increment: 65536)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Wed Oct 16 07:04:09 2019    Done.
SNP Correlation:
Working space: 90 samples, 9088 SNPs
    using 2 (CPU) cores
    using the top 2 eigenvectors
Correlation:    the sum of all selected genotypes (0,1,2) = 824424
Wed Oct 16 07:04:09 2019    (internal increment: 65536)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Wed Oct 16 07:04:09 2019    Done.
SNP Correlation:
Working space: 90 samples, 9088 SNPs
    using 2 (CPU) cores
    using the top 2 eigenvectors
Creating 'test.gds' ...
Correlation:    the sum of all selected genotypes (0,1,2) = 824424
Wed Oct 16 07:04:09 2019

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Wed Oct 16 07:04:09 2019    Done.
SNP loading:
Working space: 90 samples, 8695 SNPs
    using 1 (CPU) core
    using the top 8 eigenvectors
SNP Loading:    the sum of all selected genotypes (0,1,2) = 787449
Wed Oct 16 07:04:09 2019    (internal increment: 65536)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Wed Oct 16 07:04:09 2019    Done.
Sample loading:
Working space: 100 samples, 8695 SNPs
    using 1 (CPU) core
    using the top 8 eigenvectors
Sample Loading:    the sum of all selected genotypes (0,1,2) = 875255
Wed Oct 16 07:04:09 2019    (internal increment: 65536)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Wed Oct 16 07:04:09 2019    Done.


RUNIT TEST PROTOCOL -- Wed Oct 16 07:04:10 2019 
*********************************************** 
Number of test functions: 13 
Number of errors: 0 
Number of failures: 0 

 
1 Test Suite : 
SNPRelate RUnit Tests - 13 test functions, 0 errors, 0 failures
Number of test functions: 13 
Number of errors: 0 
Number of failures: 0 
> 
> proc.time()
   user  system elapsed 
 54.269   6.081  60.075 

Example timings

SNPRelate.Rcheck/SNPRelate-Ex.timings

nameusersystemelapsed
SNPGDSFileClass-class0.0390.0040.042
SNPRelate-package1.9230.2632.196
snpgdsAdmixPlot0.8360.0660.903
snpgdsAdmixProp0.7660.0300.796
snpgdsAlleleSwitch0.1080.0240.134
snpgdsApartSelection0.1400.0320.173
snpgdsBED2GDS0.1900.0600.251
snpgdsClose0.0250.0020.028
snpgdsCombineGeno0.1810.0580.239
snpgdsCreateGeno0.7090.0740.782
snpgdsCreateGenoSet0.2170.0350.252
snpgdsCutTree2.7930.2543.049
snpgdsDiss1.8850.0111.896
snpgdsDrawTree1.9490.0191.969
snpgdsEIGMIX0.7210.0420.764
snpgdsErrMsg000
snpgdsExampleFileName0.0010.0010.001
snpgdsFst0.0510.0100.060
snpgdsGDS2BED0.1200.0310.150
snpgdsGDS2Eigen1.0010.1401.141
snpgdsGDS2PED0.4770.1040.586
snpgdsGEN2GDS0.0010.0010.001
snpgdsGRM1.8310.1181.948
snpgdsGetGeno0.1000.0710.171
snpgdsHCluster2.3250.0522.377
snpgdsHWE0.0200.0060.026
snpgdsIBDKING2.6360.1902.826
snpgdsIBDMLE0.8750.0320.907
snpgdsIBDMLELogLik0.7270.0280.756
snpgdsIBDMoM0.2440.0380.283
snpgdsIBDSelection0.0720.0100.083
snpgdsIBS0.4470.0230.471
snpgdsIBSNum0.5130.0250.539
snpgdsIndInb0.0460.0050.052
snpgdsIndInbCoef0.0110.0040.016
snpgdsIndivBeta0.3390.0130.353
snpgdsLDMat0.2870.0300.320
snpgdsLDpair0.0050.0030.007
snpgdsLDpruning0.0570.0160.074
snpgdsMergeGRM2.9370.3603.297
snpgdsOpen0.0160.0010.017
snpgdsOption0.0020.0010.004
snpgdsPCA0.7780.0470.826
snpgdsPCACorr0.9320.0540.989
snpgdsPCASNPLoading0.8020.0190.822
snpgdsPCASampLoading0.7980.0150.812
snpgdsPED2GDS1.5610.2491.817
snpgdsPairIBD1.3430.0461.390
snpgdsPairIBDMLELogLik0.9170.0300.948
snpgdsPairScore0.3010.3390.641
snpgdsSNPList0.0150.0050.020
snpgdsSNPListIntersect0.0850.0130.098
snpgdsSNPRateFreq0.0230.0040.028
snpgdsSampMissRate0.0090.0030.011
snpgdsSelectSNP0.0080.0020.009
snpgdsSlidingWindow1.5910.3021.893
snpgdsSummary0.1120.0420.154
snpgdsTranspose0.2090.0230.233
snpgdsVCF2GDS0.4350.7811.217
snpgdsVCF2GDS_R0.1650.0540.219