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CHECK report for SNPRelate on celaya2

This page was generated on 2019-04-09 13:11:49 -0400 (Tue, 09 Apr 2019).

Package 1522/1703HostnameOS / ArchINSTALLBUILDCHECKBUILD BIN
SNPRelate 1.17.2
Xiuwen Zheng
Snapshot Date: 2019-04-08 17:01:18 -0400 (Mon, 08 Apr 2019)
URL: https://git.bioconductor.org/packages/SNPRelate
Branch: master
Last Commit: c79e4a2
Last Changed Date: 2019-03-29 16:56:14 -0400 (Fri, 29 Mar 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
merida2 OS X 10.11.6 El Capitan / x86_64  OK  OK  OK  OK 

Summary

Package: SNPRelate
Version: 1.17.2
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_1.17.2.tar.gz
StartedAt: 2019-04-09 05:39:00 -0400 (Tue, 09 Apr 2019)
EndedAt: 2019-04-09 05:41:47 -0400 (Tue, 09 Apr 2019)
EllapsedTime: 166.9 seconds
RetCode: 0
Status:  OK 
CheckDir: SNPRelate.Rcheck
Warnings: 0

Command output

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###
### 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_1.17.2.tar.gz
###
##############################################################################
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* using log directory ‘/Users/biocbuild/bbs-3.9-bioc/meat/SNPRelate.Rcheck’
* using R Under development (unstable) (2019-03-18 r76245)
* 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 ‘1.17.2’
* 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

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###
### 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" -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" -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" -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" -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" -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" -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" -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" -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" -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" -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" -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" -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" -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" -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" -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" -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 Under development (unstable) (2019-03-18 r76245) -- "Unsuffered Consequences"
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
Tue Apr  9 05:40:39 2019    (internal increment: 13960)

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

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed in 1s
Tue Apr  9 05:40:40 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
Tue Apr  9 05:40:40 2019    (internal increment: 13960)

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

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed in 1s
Tue Apr  9 05:40:41 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
Tue Apr  9 05:40:41 2019    (internal increment: 13960)

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

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed in 1s
Tue Apr  9 05:40:42 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 in 0s
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
Tue Apr  9 05:40:42 2019    (internal increment: 13960)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed in 1s
Tue Apr  9 05:40:43 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
Tue Apr  9 05:40:43 2019    (internal increment: 65536)

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

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed in 1s
Tue Apr  9 05:40:44 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
Tue Apr  9 05:40:44 2019    (internal increment: 65536)

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

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed in 0s
Tue Apr  9 05:40:44 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
Tue Apr  9 05:40:45 2019    (internal increment: 65536)

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

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed in 0s
Tue Apr  9 05:40:45 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 in 1s
Writing ...

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed in 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
Tue Apr  9 05:40:46 2019    (internal increment: 65536)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed in 0s
Tue Apr  9 05:40:46 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 snpgdsBED2GDS ...
	BED file: "/Library/Frameworks/R.framework/Versions/3.6/Resources/library/SNPRelate/extdata/plinkhapmap.bed.gz" in the SNP-major mode (Sample X SNP)
	FAM file: "/Library/Frameworks/R.framework/Versions/3.6/Resources/library/SNPRelate/extdata/plinkhapmap.fam.gz", DONE.
	BIM file: "/Library/Frameworks/R.framework/Versions/3.6/Resources/library/SNPRelate/extdata/plinkhapmap.bim.gz", DONE.
Tue Apr  9 05:40:51 2019 	store sample id, snp id, position, and chromosome.
	start writing: 60 samples, 5000 SNPs ...
 	Tue Apr  9 05:40:51 2019	0%
 	Tue Apr  9 05:40:51 2019	100%
Tue Apr  9 05:40:51 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
Tue Apr  9 05:40:51 2019    (internal increment: 64920)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed in 1s
Tue Apr  9 05:40:52 2019    Begin (eigenvalues and eigenvectors)
Tue Apr  9 05:40:52 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
Tue Apr  9 05:40:52 2019    (internal increment: 65536)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed in 0s
Tue Apr  9 05:40:52 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
Tue Apr  9 05:40:53 2019    (internal increment: 65536)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed in 0s
Tue Apr  9 05:40:53 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
Tue Apr  9 05:40:53 2019    (internal increment: 13960)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed in 1s
Tue Apr  9 05:40:54 2019    Begin (eigenvalues and eigenvectors)
Tue Apr  9 05:40:54 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
Tue Apr  9 05:40:54 2019    (internal increment: 13960)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed in 1s
Tue Apr  9 05:40:55 2019    Begin (eigenvalues and eigenvectors)
Tue Apr  9 05:40:55 2019    Done.
FUNCTION: snpgdsAlleleSwitch
Strand-switching at 50 SNP locus/loci.
Unable to determine switching at 10 SNP locus/loci.
FUNCTION: snpgdsApartSelection
Tue Apr  9 05:40:55 2019	Chromosome 1, # of SNPs: 367
Tue Apr  9 05:40:55 2019	Chromosome 2, # of SNPs: 367
Tue Apr  9 05:40:55 2019	Chromosome 3, # of SNPs: 317
Tue Apr  9 05:40:55 2019	Chromosome 4, # of SNPs: 295
Tue Apr  9 05:40:55 2019	Chromosome 5, # of SNPs: 295
Tue Apr  9 05:40:55 2019	Chromosome 6, # of SNPs: 283
Tue Apr  9 05:40:55 2019	Chromosome 7, # of SNPs: 245
Tue Apr  9 05:40:55 2019	Chromosome 8, # of SNPs: 234
Tue Apr  9 05:40:55 2019	Chromosome 9, # of SNPs: 202
Tue Apr  9 05:40:55 2019	Chromosome 10, # of SNPs: 224
Tue Apr  9 05:40:55 2019	Chromosome 11, # of SNPs: 223
Tue Apr  9 05:40:55 2019	Chromosome 12, # of SNPs: 208
Tue Apr  9 05:40:55 2019	Chromosome 13, # of SNPs: 172
Tue Apr  9 05:40:55 2019	Chromosome 14, # of SNPs: 147
Tue Apr  9 05:40:55 2019	Chromosome 15, # of SNPs: 121
Tue Apr  9 05:40:55 2019	Chromosome 16, # of SNPs: 129
Tue Apr  9 05:40:55 2019	Chromosome 17, # of SNPs: 116
Tue Apr  9 05:40:55 2019	Chromosome 18, # of SNPs: 129
Tue Apr  9 05:40:55 2019	Chromosome 19, # of SNPs: 73
Tue Apr  9 05:40:55 2019	Chromosome 20, # of SNPs: 106
Tue Apr  9 05:40:55 2019	Chromosome 21, # of SNPs: 62
Tue Apr  9 05:40:55 2019	Chromosome 22, # of SNPs: 51
Tue Apr  9 05:40:55 2019	Chromosome 23, # of SNPs: 204
Total # of SNPs selected:4570
FUNCTION: snpgdsBED2GDS
Start snpgdsBED2GDS ...
	BED file: "/Library/Frameworks/R.framework/Versions/3.6/Resources/library/SNPRelate/extdata/plinkhapmap.bed.gz" in the SNP-major mode (Sample X SNP)
	FAM file: "/Library/Frameworks/R.framework/Versions/3.6/Resources/library/SNPRelate/extdata/plinkhapmap.fam.gz", DONE.
	BIM file: "/Library/Frameworks/R.framework/Versions/3.6/Resources/library/SNPRelate/extdata/plinkhapmap.bim.gz", DONE.
Tue Apr  9 05:40:55 2019 	store sample id, snp id, position, and chromosome.
	start writing: 60 samples, 5000 SNPs ...
 	Tue Apr  9 05:40:55 2019	0%
 	Tue Apr  9 05:40:56 2019	100%
Tue Apr  9 05:40:56 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
Tue Apr  9 05:40:56 2019    (internal increment: 13960)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed in 1s
Tue Apr  9 05:40:57 2019    Begin (eigenvalues and eigenvectors)
Tue Apr  9 05:40:57 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:	Tue Apr  9 05:40:57 2019	0%
Dissimilarity:	Tue Apr  9 05:40:58 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:	Tue Apr  9 05:41:00 2019	0%
Dissimilarity:	Tue Apr  9 05:41:01 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:	Tue Apr  9 05:41:02 2019	0%
Dissimilarity:	Tue Apr  9 05:41:03 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
Tue Apr  9 05:41:04 2019    (internal increment: 13960)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed in 1s
Tue Apr  9 05:41:05 2019    Begin (eigenvalues and eigenvectors)
Tue Apr  9 05:41:05 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 ...
		Tue Apr  9 05:41:05 2019	0%
		Tue Apr  9 05:41:05 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: 	Tue Apr  9 05:41:05 2019	0%
	Output: 	Tue Apr  9 05:41:06 2019	100%
Done.
FUNCTION: snpgdsGDS2PED
Converting from GDS to PLINK PED:
	Output a MAP file DONE.
	Output a PED file ...
		Output: 	Tue Apr  9 05:41:06 2019	0%
		Output: 	Tue Apr  9 05:41:07 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
Tue Apr  9 05:41:07 2019    (internal increment: 13960)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed in 0s
Tue Apr  9 05:41:07 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
Tue Apr  9 05:41:08 2019    (internal increment: 13960)

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

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed in 0s
Tue Apr  9 05:41:08 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:	Tue Apr  9 05:41:09 2019	0%
Dissimilarity:	Tue Apr  9 05:41:10 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
Tue Apr  9 05:41:11 2019    (internal increment: 65536)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed in 0s
Tue Apr  9 05:41:11 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
Tue Apr  9 05:41:12 2019    (internal increment: 65536)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed in 0s
Tue Apr  9 05:41:12 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
Tue Apr  9 05:41:13 2019    (internal increment: 65536)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed in 0s
Tue Apr  9 05:41:13 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
Tue Apr  9 05:41:13 2019    (internal increment: 65536)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed in 1s
Tue Apr  9 05:41:14 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
Tue Apr  9 05:41:14 2019    (internal increment: 65536)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed in 0s
Tue Apr  9 05:41:14 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:	Tue Apr  9 05:41:14 2019	0%
MLE IBD:	Tue Apr  9 05:41:15 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:	Tue Apr  9 05:41:15 2019	0%
MLE IBD:	Tue Apr  9 05:41:15 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:	Tue Apr  9 05:41:15 2019	0%
MLE IBD:	Tue Apr  9 05:41:15 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:	Tue Apr  9 05:41:15 2019	0%
MLE IBD:	Tue Apr  9 05:41:16 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
Tue Apr  9 05:41:16 2019    (internal increment: 65536)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed in 0s
Tue Apr  9 05:41:16 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
Tue Apr  9 05:41:16 2019    (internal increment: 65536)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed in 0s
Tue Apr  9 05:41:16 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
Tue Apr  9 05:41:16 2019    (internal increment: 65536)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed in 0s
Tue Apr  9 05:41:16 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
Tue Apr  9 05:41:16 2019    (internal increment: 65536)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed in 0s
Tue Apr  9 05:41:16 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
Tue Apr  9 05:41:16 2019    (internal increment: 65536)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed in 0s
Tue Apr  9 05:41:16 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
Tue Apr  9 05:41:16 2019    (internal increment: 65536)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed in 0s
Tue Apr  9 05:41:16 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
Tue Apr  9 05:41:16 2019    (internal increment: 65536)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed in 1s
Tue Apr  9 05:41:17 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 in 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
Tue Apr  9 05:41:17 2019    (internal increment: 65536)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed in 0s
Tue Apr  9 05:41:17 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
Tue Apr  9 05:41:18 2019    (internal increment: 13960)

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Tue Apr  9 05:41:19 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
Tue Apr  9 05:41:19 2019    (internal increment: 13960)

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Saving to the GDS file:

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed in 1s
Tue Apr  9 05:41:20 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
Tue Apr  9 05:41:20 2019    (internal increment: 13960)

[..................................................]  0%, ETC: ---        
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Saving to the GDS file:

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed in 0s
Tue Apr  9 05:41:21 2019    Done.
GRM merging:
    open 'tmp1.gds' (3,400 variants)
    open 'tmp2.gds' (3,400 variants)
Weight: 0.5, 0.5
Output: tmp.gds

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GRM merging:
    open 'tmp1.gds' (3,400 variants)
    open 'tmp2.gds' (3,400 variants)
Weight: 0.5, 0.5

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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
Tue Apr  9 05:41:22 2019    (internal increment: 13960)

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Tue Apr  9 05:41:22 2019    Begin (eigenvalues and eigenvectors)
Tue Apr  9 05:41:22 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
Tue Apr  9 05:41:23 2019    (internal increment: 13960)

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[==================================================] 100%, completed in 0s
Tue Apr  9 05:41:23 2019    Begin (eigenvalues and eigenvectors)
Tue Apr  9 05:41:23 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
Tue Apr  9 05:41:23 2019    (internal increment: 65536)

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Tue Apr  9 05:41:23 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
Tue Apr  9 05:41:23 2019

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Tue Apr  9 05:41:23 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
Tue Apr  9 05:41:23 2019    (internal increment: 13960)

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[==================================================] 100%, completed in 1s
Tue Apr  9 05:41:24 2019    Begin (eigenvalues and eigenvectors)
Tue Apr  9 05:41:24 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
Tue Apr  9 05:41:24 2019    (internal increment: 65536)

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Tue Apr  9 05:41:24 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
Tue Apr  9 05:41:24 2019    (internal increment: 13960)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed in 1s
Tue Apr  9 05:41:25 2019    Begin (eigenvalues and eigenvectors)
Tue Apr  9 05:41:25 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
Tue Apr  9 05:41:25 2019    (internal increment: 65536)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed in 0s
Tue Apr  9 05:41:25 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
Tue Apr  9 05:41:25 2019    (internal increment: 65536)

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Tue Apr  9 05:41:25 2019    Done.
FUNCTION: snpgdsPED2GDS
Converting from GDS to PLINK PED:
	Output a MAP file DONE.
	Output a PED file ...
		Output: 	Tue Apr  9 05:41:25 2019	0%
		Output: 	Tue Apr  9 05:41:26 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:	Tue Apr  9 05:41:27 2019	0%
MLE IBD:	Tue Apr  9 05:41:27 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
Tue Apr  9 05:41:27 2019    (internal increment: 65536)

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[==================================================] 100%, completed in 0s
Tue Apr  9 05:41:27 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:	Tue Apr  9 05:41:27 2019	0%
MLE IBD:	Tue Apr  9 05:41:28 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:	Tue Apr  9 05:41:28 2019	0%
MLE IBD:	Tue Apr  9 05:41:29 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
Tue Apr  9 05:41:29 2019    (internal increment: 65536)

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[==================================================] 100%, completed in 0s
Tue Apr  9 05:41:29 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
Tue Apr  9 05:41:30 2019, Chromosome 1 (716 SNPs), 2448 windows
Tue Apr  9 05:41:30 2019, Chromosome 2 (742 SNPs), 2416 windows
Tue Apr  9 05:41:30 2019, Chromosome 3 (609 SNPs), 1985 windows
Tue Apr  9 05:41:30 2019, Chromosome 4 (562 SNPs), 1894 windows
Tue Apr  9 05:41:30 2019, Chromosome 5 (566 SNPs), 1797 windows
Tue Apr  9 05:41:31 2019, Chromosome 6 (565 SNPs), 1694 windows
Tue Apr  9 05:41:31 2019, Chromosome 7 (472 SNPs), 1573 windows
Tue Apr  9 05:41:31 2019, Chromosome 8 (488 SNPs), 1445 windows
Tue Apr  9 05:41:31 2019, Chromosome 9 (416 SNPs), 1393 windows
Tue Apr  9 05:41:31 2019, Chromosome 10 (483 SNPs), 1343 windows
Tue Apr  9 05:41:31 2019, Chromosome 11 (447 SNPs), 1338 windows
Tue Apr  9 05:41:31 2019, Chromosome 12 (427 SNPs), 1316 windows
Tue Apr  9 05:41:31 2019, Chromosome 13 (344 SNPs), 948 windows
Tue Apr  9 05:41:31 2019, Chromosome 14 (281 SNPs), 847 windows
Tue Apr  9 05:41:31 2019, Chromosome 15 (262 SNPs), 774 windows
Tue Apr  9 05:41:31 2019, Chromosome 16 (278 SNPs), 873 windows
Tue Apr  9 05:41:32 2019, Chromosome 17 (207 SNPs), 773 windows
Tue Apr  9 05:41:32 2019, Chromosome 18 (266 SNPs), 753 windows
Tue Apr  9 05:41:32 2019, Chromosome 19 (120 SNPs), 627 windows
Tue Apr  9 05:41:32 2019, Chromosome 20 (229 SNPs), 602 windows
Tue Apr  9 05:41:32 2019, Chromosome 21 (126 SNPs), 311 windows
Tue Apr  9 05:41:32 2019, Chromosome 22 (116 SNPs), 312 windows
Tue Apr  9 05:41:32 2019, Chromosome 23 (358 SNPs), 1507 windows
Tue Apr  9 05:41:32 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=<ID=20,length=62435964,assembly=B36,md5=f126cdf8a6e0c7f379d618ff66beb2da,species="Homo sapiens",taxonomy=x>
##phasing=partial
##INFO=<ID=NS,Number=1,Type=Integer,Description="Number of Samples With Data">
##INFO=<ID=DP,Number=1,Type=Integer,Description="Total Depth">
##INFO=<ID=AF,Number=A,Type=Float,Description="Allele Frequency">
##INFO=<ID=AA,Number=1,Type=String,Description="Ancestral Allele">
##INFO=<ID=DB,Number=0,Type=Flag,Description="dbSNP membership, build 129">
##INFO=<ID=H2,Number=0,Type=Flag,Description="HapMap2 membership">
##FILTER=<ID=q10,Description="Quality below 10">
##FILTER=<ID=s50,Description="Less than 50% of samples have data">
##FORMAT=<ID=GT,Number=1,Type=String,Description="Genotype">
##FORMAT=<ID=GQ,Number=1,Type=Integer,Description="Genotype Quality">
##FORMAT=<ID=DP,Number=1,Type=Integer,Description="Read Depth">
##FORMAT=<ID=HQ,Number=2,Type=Integer,Description="Haplotype Quality">
#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
VCF Format ==> SNP GDS Format
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).
VCF Format ==> SNP GDS Format
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).
VCF Format ==> SNP GDS Format
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 
VCF Format ==> SNP GDS Format
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 
VCF Format ==> SNP GDS Format
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=<ID=20,length=62435964,assembly=B36,md5=f126cdf8a6e0c7f379d618ff66beb2da,species="Homo sapiens",taxonomy=x>
##phasing=partial
##INFO=<ID=NS,Number=1,Type=Integer,Description="Number of Samples With Data">
##INFO=<ID=DP,Number=1,Type=Integer,Description="Total Depth">
##INFO=<ID=AF,Number=A,Type=Float,Description="Allele Frequency">
##INFO=<ID=AA,Number=1,Type=String,Description="Ancestral Allele">
##INFO=<ID=DB,Number=0,Type=Flag,Description="dbSNP membership, build 129">
##INFO=<ID=H2,Number=0,Type=Flag,Description="HapMap2 membership">
##FILTER=<ID=q10,Description="Quality below 10">
##FILTER=<ID=s50,Description="Less than 50% of samples have data">
##FORMAT=<ID=GT,Number=1,Type=String,Description="Genotype">
##FORMAT=<ID=GQ,Number=1,Type=Integer,Description="Genotype Quality">
##FORMAT=<ID=DP,Number=1,Type=Integer,Description="Read Depth">
##FORMAT=<ID=HQ,Number=2,Type=Integer,Description="Haplotype Quality">
#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
Tue Apr  9 05:41:33 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
Tue Apr  9 05:41:33 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
Tue Apr  9 05:41:33 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
Tue Apr  9 05:41:33 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
Tue Apr  9 05:41:33 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
Tue Apr  9 05:41:34 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
Tue Apr  9 05:41:34 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
Tue Apr  9 05:41:34 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
Tue Apr  9 05:41:36 2019    (internal increment: 65536)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed in 0s
Tue Apr  9 05:41:36 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
Tue Apr  9 05:41:36 2019

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed in 0s
Tue Apr  9 05:41:36 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
Tue Apr  9 05:41:36 2019    (internal increment: 65536)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed in 0s
Tue Apr  9 05:41:36 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
Tue Apr  9 05:41:36 2019    (internal increment: 65536)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed in 0s
Tue Apr  9 05:41:36 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
Tue Apr  9 05:41:36 2019    (internal increment: 65536)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed in 0s
Tue Apr  9 05:41:36 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
Tue Apr  9 05:41:36 2019

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed in 0s
Tue Apr  9 05:41:36 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
Tue Apr  9 05:41:36 2019    (internal increment: 65536)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed in 0s
Tue Apr  9 05:41:36 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
Tue Apr  9 05:41:36 2019    (internal increment: 65536)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed in 0s
Tue Apr  9 05:41:36 2019    Done.


RUNIT TEST PROTOCOL -- Tue Apr  9 05:41:36 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 
 53.212   5.893  58.954

Example timings

SNPRelate.Rcheck/SNPRelate-Ex.timings

nameusersystemelapsed
SNPGDSFileClass-class0.0410.0070.048
SNPRelate-package1.9850.2612.251
snpgdsAdmixPlot0.8040.0580.865
snpgdsAdmixProp0.7140.0280.743
snpgdsAlleleSwitch0.1440.0230.168
snpgdsApartSelection0.2020.0640.267
snpgdsBED2GDS0.2070.0700.277
snpgdsClose0.0200.0010.020
snpgdsCombineGeno0.1780.0530.232
snpgdsCreateGeno0.7390.0790.817
snpgdsCreateGenoSet0.2240.0360.261
snpgdsCutTree2.8450.3163.163
snpgdsDiss2.1620.0162.183
snpgdsDrawTree2.1630.0232.187
snpgdsEIGMIX0.7010.0520.765
snpgdsErrMsg0.0010.0000.001
snpgdsExampleFileName0.0010.0010.002
snpgdsFst0.0540.0100.064
snpgdsGDS2BED0.1180.0290.164
snpgdsGDS2Eigen0.8900.1321.024
snpgdsGDS2PED0.5340.0860.680
snpgdsGEN2GDS0.0010.0000.001
snpgdsGRM1.8360.1091.958
snpgdsGetGeno0.0980.0680.166
snpgdsHCluster2.5710.0482.621
snpgdsHWE0.0160.0060.022
snpgdsIBDKING2.5490.2082.759
snpgdsIBDMLE0.8610.0300.900
snpgdsIBDMLELogLik0.8220.0270.849
snpgdsIBDMoM0.2580.0450.306
snpgdsIBDSelection0.0930.0140.107
snpgdsIBS0.3630.0200.384
snpgdsIBSNum0.4960.0290.525
snpgdsIndInb0.0350.0040.039
snpgdsIndInbCoef0.0100.0040.014
snpgdsIndivBeta0.3460.0130.359
snpgdsLDMat0.3950.0410.440
snpgdsLDpair0.0070.0050.012
snpgdsLDpruning0.0610.0110.072
snpgdsMergeGRM2.9760.3913.367
snpgdsOpen0.0250.0030.028
snpgdsOption0.0040.0020.006
snpgdsPCA0.8400.0460.888
snpgdsPCACorr0.8590.0590.919
snpgdsPCASNPLoading0.6700.0130.684
snpgdsPCASampLoading0.8060.0200.826
snpgdsPED2GDS1.8010.2082.057
snpgdsPairIBD1.3950.0551.450
snpgdsPairIBDMLELogLik0.7170.0420.760
snpgdsPairScore0.2890.3250.614
snpgdsSNPList0.0120.0030.016
snpgdsSNPListIntersect0.0830.0140.097
snpgdsSNPRateFreq0.0240.0070.033
snpgdsSampMissRate0.0090.0030.012
snpgdsSelectSNP0.0130.0030.016
snpgdsSlidingWindow1.6820.5112.203
snpgdsSummary0.0880.0080.095
snpgdsTranspose0.2250.0530.279
snpgdsVCF2GDS0.4710.7871.260
snpgdsVCF2GDS_R0.1600.0470.207