Xiuwen Zheng
| Snapshot Date: 2022-04-12 01:55:07 -0400 (Tue, 12 Apr 2022) |
| git_url: https://git.bioconductor.org/packages/SNPRelate |
| git_branch: RELEASE_3_14 |
| git_last_commit: 8fcd837 |
| git_last_commit_date: 2021-10-26 12:15:42 -0400 (Tue, 26 Oct 2021) |
| Back to Multiple platform build/check report for BioC 3.14 |
|
This page was generated on 2022-04-13 12:08:49 -0400 (Wed, 13 Apr 2022).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo2 | Linux (Ubuntu 20.04.4 LTS) | x86_64 | 4.1.3 (2022-03-10) -- "One Push-Up" | 4324 |
| tokay2 | Windows Server 2012 R2 Standard | x64 | 4.1.3 (2022-03-10) -- "One Push-Up" | 4077 |
| machv2 | macOS 10.14.6 Mojave | x86_64 | 4.1.3 (2022-03-10) -- "One Push-Up" | 4137 |
| Click on any hostname to see more info about the system (e.g. compilers) (*) as reported by 'uname -p', except on Windows and Mac OS X | ||||
|
To the developers/maintainers of the SNPRelate package: - Please allow up to 24 hours (and sometimes 48 hours) for your latest push to [email protected]:packages/SNPRelate.git to reflect on this report. See How and When does the builder pull? When will my changes propagate? for more information. - Make sure to use the following settings in order to reproduce any error or warning you see on this page. |
| Package 1831/2083 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| SNPRelate 1.28.0 (landing page) Xiuwen Zheng
| nebbiolo2 | Linux (Ubuntu 20.04.4 LTS) / x86_64 | OK | OK | OK | | ||||||||
| tokay2 | Windows Server 2012 R2 Standard / x64 | OK | OK | OK | OK | | ||||||||
| machv2 | macOS 10.14.6 Mojave / x86_64 | OK | OK | OK | OK | | ||||||||
| Package: SNPRelate |
| Version: 1.28.0 |
| Command: /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:SNPRelate.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings SNPRelate_1.28.0.tar.gz |
| StartedAt: 2022-04-12 18:45:43 -0400 (Tue, 12 Apr 2022) |
| EndedAt: 2022-04-12 18:48:20 -0400 (Tue, 12 Apr 2022) |
| EllapsedTime: 156.5 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: SNPRelate.Rcheck |
| Warnings: 0 |
############################################################################## ############################################################################## ### ### Running command: ### ### /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:SNPRelate.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings SNPRelate_1.28.0.tar.gz ### ############################################################################## ############################################################################## * using log directory ‘/Users/biocbuild/bbs-3.14-bioc/meat/SNPRelate.Rcheck’ * using R version 4.1.3 (2022-03-10) * using platform: x86_64-apple-darwin17.0 (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 ‘1.28.0’ * 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 use of PKG_*FLAGS in Makefiles ... 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-3.14-bioc/meat/SNPRelate.Rcheck/00check.log’ for details.
SNPRelate.Rcheck/00install.out
############################################################################## ############################################################################## ### ### Running command: ### ### /Library/Frameworks/R.framework/Resources/bin/R CMD INSTALL SNPRelate ### ############################################################################## ############################################################################## * installing to library ‘/Library/Frameworks/R.framework/Versions/4.1/Resources/library’ * installing *source* package ‘SNPRelate’ ... ** using staged installation ** libs clang++ -mmacosx-version-min=10.13 -std=gnu++14 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -DUSING_R -I. -I'/Library/Frameworks/R.framework/Versions/4.1/Resources/library/gdsfmt/include' -I/usr/local/include -fPIC -Wall -g -O2 -c ConvToGDS.cpp -o ConvToGDS.o clang -mmacosx-version-min=10.13 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -DUSING_R -I. -I'/Library/Frameworks/R.framework/Versions/4.1/Resources/library/gdsfmt/include' -I/usr/local/include -fPIC -Wall -g -O2 -c R_SNPRelate.c -o R_SNPRelate.o clang++ -mmacosx-version-min=10.13 -std=gnu++14 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -DUSING_R -I. -I'/Library/Frameworks/R.framework/Versions/4.1/Resources/library/gdsfmt/include' -I/usr/local/include -fPIC -Wall -g -O2 -c SNPRelate.cpp -o SNPRelate.o clang++ -mmacosx-version-min=10.13 -std=gnu++14 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -DUSING_R -I. -I'/Library/Frameworks/R.framework/Versions/4.1/Resources/library/gdsfmt/include' -I/usr/local/include -fPIC -Wall -g -O2 -c ThreadPool.cpp -o ThreadPool.o clang++ -mmacosx-version-min=10.13 -std=gnu++14 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -DUSING_R -I. -I'/Library/Frameworks/R.framework/Versions/4.1/Resources/library/gdsfmt/include' -I/usr/local/include -fPIC -Wall -g -O2 -c dGenGWAS.cpp -o dGenGWAS.o clang++ -mmacosx-version-min=10.13 -std=gnu++14 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -DUSING_R -I. -I'/Library/Frameworks/R.framework/Versions/4.1/Resources/library/gdsfmt/include' -I/usr/local/include -fPIC -Wall -g -O2 -c dVect.cpp -o dVect.o clang++ -mmacosx-version-min=10.13 -std=gnu++14 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -DUSING_R -I. -I'/Library/Frameworks/R.framework/Versions/4.1/Resources/library/gdsfmt/include' -I/usr/local/include -fPIC -Wall -g -O2 -c genBeta.cpp -o genBeta.o clang++ -mmacosx-version-min=10.13 -std=gnu++14 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -DUSING_R -I. -I'/Library/Frameworks/R.framework/Versions/4.1/Resources/library/gdsfmt/include' -I/usr/local/include -fPIC -Wall -g -O2 -c genEIGMIX.cpp -o genEIGMIX.o clang++ -mmacosx-version-min=10.13 -std=gnu++14 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -DUSING_R -I. -I'/Library/Frameworks/R.framework/Versions/4.1/Resources/library/gdsfmt/include' -I/usr/local/include -fPIC -Wall -g -O2 -c genFst.cpp -o genFst.o clang++ -mmacosx-version-min=10.13 -std=gnu++14 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -DUSING_R -I. -I'/Library/Frameworks/R.framework/Versions/4.1/Resources/library/gdsfmt/include' -I/usr/local/include -fPIC -Wall -g -O2 -c genHWE.cpp -o genHWE.o clang++ -mmacosx-version-min=10.13 -std=gnu++14 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -DUSING_R -I. -I'/Library/Frameworks/R.framework/Versions/4.1/Resources/library/gdsfmt/include' -I/usr/local/include -fPIC -Wall -g -O2 -c genIBD.cpp -o genIBD.o clang++ -mmacosx-version-min=10.13 -std=gnu++14 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -DUSING_R -I. -I'/Library/Frameworks/R.framework/Versions/4.1/Resources/library/gdsfmt/include' -I/usr/local/include -fPIC -Wall -g -O2 -c genIBS.cpp -o genIBS.o clang++ -mmacosx-version-min=10.13 -std=gnu++14 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -DUSING_R -I. -I'/Library/Frameworks/R.framework/Versions/4.1/Resources/library/gdsfmt/include' -I/usr/local/include -fPIC -Wall -g -O2 -c genKING.cpp -o genKING.o clang++ -mmacosx-version-min=10.13 -std=gnu++14 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -DUSING_R -I. -I'/Library/Frameworks/R.framework/Versions/4.1/Resources/library/gdsfmt/include' -I/usr/local/include -fPIC -Wall -g -O2 -c genLD.cpp -o genLD.o clang++ -mmacosx-version-min=10.13 -std=gnu++14 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -DUSING_R -I. -I'/Library/Frameworks/R.framework/Versions/4.1/Resources/library/gdsfmt/include' -I/usr/local/include -fPIC -Wall -g -O2 -c genPCA.cpp -o genPCA.o clang++ -mmacosx-version-min=10.13 -std=gnu++14 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -DUSING_R -I. -I'/Library/Frameworks/R.framework/Versions/4.1/Resources/library/gdsfmt/include' -I/usr/local/include -fPIC -Wall -g -O2 -c genSlideWin.cpp -o genSlideWin.o clang++ -mmacosx-version-min=10.13 -std=gnu++14 -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-darwin18/8.2.0 -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/4.1/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)
SNPRelate.Rcheck/tests/runTests.Rout
R version 4.1.3 (2022-03-10) -- "One Push-Up"
Copyright (C) 2022 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin17.0 (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)
# of samples: 279
# of SNPs: 1,000
using 1 thread
GRM Calculation: the sum of all selected genotypes (0,1,2) = 282597
CPU capabilities: Double-Precision SSE2
Tue Apr 12 18:47:14 2022 (internal increment: 13960)
[..................................................] 0%, ETC: ---
[==================================================] 100%, completed, 0s
Saving to the GDS file:
[..................................................] 0%, ETC: ---
[==================================================] 100%, completed, 0s
Tue Apr 12 18:47:14 2022 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)
# of samples: 279
# of SNPs: 2,000
using 1 thread
GRM Calculation: the sum of all selected genotypes (0,1,2) = 559412
CPU capabilities: Double-Precision SSE2
Tue Apr 12 18:47:14 2022 (internal increment: 13960)
[..................................................] 0%, ETC: ---
[==================================================] 100%, completed, 1s
Saving to the GDS file:
[..................................................] 0%, ETC: ---
[==================================================] 100%, completed, 0s
Tue Apr 12 18:47:15 2022 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)
# of samples: 279
# of SNPs: 3,800
using 1 thread
GRM Calculation: the sum of all selected genotypes (0,1,2) = 1066957
CPU capabilities: Double-Precision SSE2
Tue Apr 12 18:47:15 2022 (internal increment: 13960)
[..................................................] 0%, ETC: ---
[==================================================] 100%, completed, 1s
Saving to the GDS file:
[..................................................] 0%, ETC: ---
[==================================================] 100%, completed, 0s
Tue Apr 12 18:47:16 2022 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
Genetic Relationship Matrix (GRM, GCTA):
Excluding 2,288 SNPs (non-autosomes or non-selection)
Excluding 0 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
# of samples: 279
# of SNPs: 6,800
using 1 thread
GRM Calculation: the sum of all selected genotypes (0,1,2) = 1908966
CPU capabilities: Double-Precision SSE2
Tue Apr 12 18:47:16 2022 (internal increment: 13960)
[..................................................] 0%, ETC: ---
[==================================================] 100%, completed, 1s
Tue Apr 12 18:47:17 2022 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)
# of samples: 279
# of SNPs: 1,000
using 1 thread
GRM Calculation: the sum of all selected genotypes (0,1,2) = 282597
CPU capabilities: Double-Precision SSE2
Tue Apr 12 18:47:17 2022 (internal increment: 65536)
[..................................................] 0%, ETC: ---
[==================================================] 100%, completed, 0s
Saving to the GDS file:
[..................................................] 0%, ETC: ---
[==================================================] 100%, completed, 1s
Tue Apr 12 18:47:18 2022 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)
# of samples: 279
# of SNPs: 2,000
using 1 thread
GRM Calculation: the sum of all selected genotypes (0,1,2) = 559412
CPU capabilities: Double-Precision SSE2
Tue Apr 12 18:47:18 2022 (internal increment: 65536)
[..................................................] 0%, ETC: ---
[==================================================] 100%, completed, 0s
Saving to the GDS file:
[..................................................] 0%, ETC: ---
[==================================================] 100%, completed, 0s
Tue Apr 12 18:47:18 2022 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)
# of samples: 279
# of SNPs: 3,800
using 1 thread
GRM Calculation: the sum of all selected genotypes (0,1,2) = 1066957
CPU capabilities: Double-Precision SSE2
Tue Apr 12 18:47:19 2022 (internal increment: 65536)
[..................................................] 0%, ETC: ---
[==================================================] 100%, completed, 0s
Saving to the GDS file:
[..................................................] 0%, ETC: ---
[==================================================] 100%, completed, 0s
Tue Apr 12 18:47:19 2022 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, 1s
Genetic Relationship Matrix (GRM, IndivBeta):
Excluding 2,288 SNPs (non-autosomes or non-selection)
Excluding 0 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
# of samples: 279
# of SNPs: 6,800
using 1 thread
GRM Calculation: the sum of all selected genotypes (0,1,2) = 1908966
CPU capabilities: Double-Precision SSE2
Tue Apr 12 18:47:20 2022 (internal increment: 65536)
[..................................................] 0%, ETC: ---
[==================================================] 100%, completed, 0s
Tue Apr 12 18:47:20 2022 Done.
Linkage Disequilibrium (LD) estimation on genotypes:
# of samples: 279
# of SNPs: 1,000
using 1 thread
method: covariance
LD matrix: the sum of all selected genotypes (0,1,2) = 283058
Linkage Disequilibrium (LD) estimation on genotypes:
# of samples: 279
# of SNPs: 1,000
using 1 thread
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/4.1/Resources/library/SNPRelate/extdata/plinkhapmap.bed.gz'
SNP-major mode (Sample X SNP), 45.7K
FAM file: '/Library/Frameworks/R.framework/Versions/4.1/Resources/library/SNPRelate/extdata/plinkhapmap.fam.gz'
BIM file: '/Library/Frameworks/R.framework/Versions/4.1/Resources/library/SNPRelate/extdata/plinkhapmap.bim.gz'
Tue Apr 12 18:47:25 2022 (store sample id, snp id, position, and chromosome)
start writing: 60 samples, 5000 SNPs ...
[..................................................] 0%, ETC: ---
[==================================================] 100%, completed, 0s
Tue Apr 12 18:47:25 2022 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)
# of samples: 60
# of SNPs: 4,769
using 1 thread
# of principal components: 32
PCA: the sum of all selected genotypes (0,1,2) = 124273
CPU capabilities: Double-Precision SSE2
Tue Apr 12 18:47:25 2022 (internal increment: 64920)
[..................................................] 0%, ETC: ---
[==================================================] 100%, completed, 0s
Tue Apr 12 18:47:25 2022 Begin (eigenvalues and eigenvectors)
Tue Apr 12 18:47:25 2022 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)
# of samples: 279
# of SNPs: 8,722
using 1 thread
PLINK IBD: the sum of all selected genotypes (0,1,2) = 2446510
Tue Apr 12 18:47:25 2022 (internal increment: 65536)
[..................................................] 0%, ETC: ---
[==================================================] 100%, completed, 1s
Tue Apr 12 18:47:26 2022 Done.
Identity-By-State (IBS) analysis on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 1 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
# of samples: 279
# of SNPs: 8,722
using 1 thread
IBS: the sum of all selected genotypes (0,1,2) = 2446510
Tue Apr 12 18:47:26 2022 (internal increment: 65536)
[..................................................] 0%, ETC: ---
[==================================================] 100%, completed, 0s
Tue Apr 12 18:47:26 2022 Done.
Linkage Disequilibrium (LD) estimation on genotypes:
# of samples: 279
# of SNPs: 200
using 1 thread
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)
# of samples: 279
# of SNPs: 8,722
using 1 thread
Eigen-analysis: the sum of all selected genotypes (0,1,2) = 2446510
CPU capabilities: Double-Precision SSE2
Tue Apr 12 18:47:27 2022 (internal increment: 13960)
[..................................................] 0%, ETC: ---
[==================================================] 100%, completed, 1s
Tue Apr 12 18:47:28 2022 Begin (eigenvalues and eigenvectors)
Tue Apr 12 18:47:28 2022 Done.
FUNCTION: snpgdsAdmixProp
Eigen-analysis on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 1 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
# of samples: 279
# of SNPs: 8,722
using 1 thread
Eigen-analysis: the sum of all selected genotypes (0,1,2) = 2446510
CPU capabilities: Double-Precision SSE2
Tue Apr 12 18:47:28 2022 (internal increment: 13960)
[..................................................] 0%, ETC: ---
[==================================================] 100%, completed, 0s
Tue Apr 12 18:47:28 2022 Begin (eigenvalues and eigenvectors)
Tue Apr 12 18:47:28 2022 Done.
FUNCTION: snpgdsAlleleSwitch
Strand-switching at 50 SNP locus/loci.
Unable to determine switching at 10 SNP locus/loci.
FUNCTION: snpgdsApartSelection
Tue Apr 12 18:47:29 2022 Chromosome 1, # of SNPs: 367
Tue Apr 12 18:47:29 2022 Chromosome 2, # of SNPs: 367
Tue Apr 12 18:47:29 2022 Chromosome 3, # of SNPs: 317
Tue Apr 12 18:47:29 2022 Chromosome 4, # of SNPs: 295
Tue Apr 12 18:47:29 2022 Chromosome 5, # of SNPs: 295
Tue Apr 12 18:47:29 2022 Chromosome 6, # of SNPs: 283
Tue Apr 12 18:47:29 2022 Chromosome 7, # of SNPs: 245
Tue Apr 12 18:47:29 2022 Chromosome 8, # of SNPs: 234
Tue Apr 12 18:47:29 2022 Chromosome 9, # of SNPs: 202
Tue Apr 12 18:47:29 2022 Chromosome 10, # of SNPs: 224
Tue Apr 12 18:47:29 2022 Chromosome 11, # of SNPs: 223
Tue Apr 12 18:47:29 2022 Chromosome 12, # of SNPs: 208
Tue Apr 12 18:47:29 2022 Chromosome 13, # of SNPs: 172
Tue Apr 12 18:47:29 2022 Chromosome 14, # of SNPs: 147
Tue Apr 12 18:47:29 2022 Chromosome 15, # of SNPs: 121
Tue Apr 12 18:47:29 2022 Chromosome 16, # of SNPs: 129
Tue Apr 12 18:47:29 2022 Chromosome 17, # of SNPs: 116
Tue Apr 12 18:47:29 2022 Chromosome 18, # of SNPs: 129
Tue Apr 12 18:47:29 2022 Chromosome 19, # of SNPs: 73
Tue Apr 12 18:47:29 2022 Chromosome 20, # of SNPs: 106
Tue Apr 12 18:47:29 2022 Chromosome 21, # of SNPs: 62
Tue Apr 12 18:47:29 2022 Chromosome 22, # of SNPs: 51
Tue Apr 12 18:47:29 2022 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/4.1/Resources/library/SNPRelate/extdata/plinkhapmap.bed.gz'
SNP-major mode (Sample X SNP), 45.7K
FAM file: '/Library/Frameworks/R.framework/Versions/4.1/Resources/library/SNPRelate/extdata/plinkhapmap.fam.gz'
BIM file: '/Library/Frameworks/R.framework/Versions/4.1/Resources/library/SNPRelate/extdata/plinkhapmap.bim.gz'
Tue Apr 12 18:47:29 2022 (store sample id, snp id, position, and chromosome)
start writing: 60 samples, 5000 SNPs ...
[..................................................] 0%, ETC: ---
[==================================================] 100%, completed, 0s
Tue Apr 12 18:47:29 2022 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)
# of samples: 279
# of SNPs: 958
using 1 thread
# of principal components: 32
PCA: the sum of all selected genotypes (0,1,2) = 264760
CPU capabilities: Double-Precision SSE2
Tue Apr 12 18:47:29 2022 (internal increment: 13960)
[..................................................] 0%, ETC: ---
[==================================================] 100%, completed, 1s
Tue Apr 12 18:47:30 2022 Begin (eigenvalues and eigenvectors)
Tue Apr 12 18:47:30 2022 Done.
FUNCTION: snpgdsCreateGenoSet
SNP pruning based on LD:
Excluding 365 SNPs on non-autosomes
Excluding 1 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
# of samples: 279
# of SNPs: 8,722
using 1 thread
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)
# of samples: 279
# of SNPs: 8,722
using 1 thread
Dissimilarity: the sum of all selected genotypes (0,1,2) = 2446510
Dissimilarity: Tue Apr 12 18:47:30 2022 0%
Dissimilarity: Tue Apr 12 18:47:32 2022 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)
# of samples: 279
# of SNPs: 8,722
using 1 thread
Dissimilarity: the sum of all selected genotypes (0,1,2) = 2446510
Dissimilarity: Tue Apr 12 18:47:33 2022 0%
Dissimilarity: Tue Apr 12 18:47:34 2022 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)
# of samples: 279
# of SNPs: 8,722
using 1 thread
Dissimilarity: the sum of all selected genotypes (0,1,2) = 2446510
Dissimilarity: Tue Apr 12 18:47:36 2022 0%
Dissimilarity: Tue Apr 12 18:47:37 2022 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)
# of samples: 279
# of SNPs: 8,722
using 1 thread
Eigen-analysis: the sum of all selected genotypes (0,1,2) = 2446510
CPU capabilities: Double-Precision SSE2
Tue Apr 12 18:47:38 2022 (internal increment: 13960)
[..................................................] 0%, ETC: ---
[==================================================] 100%, completed, 0s
Tue Apr 12 18:47:38 2022 Begin (eigenvalues and eigenvectors)
Tue Apr 12 18:47:38 2022 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)
# of samples: 279
# of SNPs: 8,722
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)
# of samples: 279
# of SNPs: 8,722
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 12 18:47:38 2022 0%
Tue Apr 12 18:47:38 2022 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 12 18:47:38 2022 0%
Output: Tue Apr 12 18:47:39 2022 100%
Done.
FUNCTION: snpgdsGDS2PED
Converting from GDS to PLINK PED:
Output a MAP file DONE.
Output a PED file ...
Output: Tue Apr 12 18:47:39 2022 0%
Output: Tue Apr 12 18:47:40 2022 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)
# of samples: 279
# of SNPs: 8,722
using 1 thread
GRM Calculation: the sum of all selected genotypes (0,1,2) = 2446510
CPU capabilities: Double-Precision SSE2
Tue Apr 12 18:47:40 2022 (internal increment: 13960)
[..................................................] 0%, ETC: ---
[==================================================] 100%, completed, 1s
Tue Apr 12 18:47:41 2022 Done.
Genetic Relationship Matrix (GRM, GCTA):
Excluding 365 SNPs on non-autosomes
Excluding 1 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
# of samples: 279
# of SNPs: 8,722
using 1 thread
GRM Calculation: the sum of all selected genotypes (0,1,2) = 2446510
CPU capabilities: Double-Precision SSE2
Tue Apr 12 18:47:41 2022 (internal increment: 13960)
[..................................................] 0%, ETC: ---
[==================================================] 100%, completed, 0s
Saving to the GDS file:
[..................................................] 0%, ETC: ---
[==================================================] 100%, completed, 1s
Tue Apr 12 18:47:42 2022 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)
# of samples: 279
# of SNPs: 8,722
using 1 thread
Dissimilarity: the sum of all selected genotypes (0,1,2) = 2446510
Dissimilarity: Tue Apr 12 18:47:42 2022 0%
Dissimilarity: Tue Apr 12 18:47:43 2022 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)
# of samples: 92
# of SNPs: 7,506
using 1 thread
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 12 18:47:44 2022 (internal increment: 65536)
[..................................................] 0%, ETC: ---
[==================================================] 100%, completed, 0s
Tue Apr 12 18:47:44 2022 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)
# of samples: 92
# of SNPs: 7,506
using 1 thread
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 12 18:47:44 2022 (internal increment: 65536)
[..................................................] 0%, ETC: ---
[==================================================] 100%, completed, 0s
Tue Apr 12 18:47:44 2022 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)
# of samples: 92
# of SNPs: 7,506
using 1 thread
# 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 12 18:47:46 2022 (internal increment: 65536)
[..................................................] 0%, ETC: ---
[==================================================] 100%, completed, 0s
Tue Apr 12 18:47:46 2022 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)
# of samples: 92
# of SNPs: 7,506
using 1 thread
Relationship inference in a homogeneous population.
KING IBD: the sum of all selected genotypes (0,1,2) = 702139
Tue Apr 12 18:47:46 2022 (internal increment: 65536)
[..................................................] 0%, ETC: ---
[==================================================] 100%, completed, 1s
Tue Apr 12 18:47:47 2022 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)
# of samples: 92
# of SNPs: 7,506
using 1 thread
Relationship inference in a homogeneous population.
KING IBD: the sum of all selected genotypes (0,1,2) = 702139
Tue Apr 12 18:47:47 2022 (internal increment: 65536)
[..................................................] 0%, ETC: ---
[==================================================] 100%, completed, 0s
Tue Apr 12 18:47:47 2022 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)
# of samples: 30
# of SNPs: 7,142
using 1 thread
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)
# of samples: 30
# of SNPs: 250
using 1 thread
MLE IBD: the sum of all selected genotypes (0,1,2) = 7859
MLE IBD: Tue Apr 12 18:47:47 2022 0%
MLE IBD: Tue Apr 12 18:47:48 2022 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)
# of samples: 25
# of SNPs: 250
using 1 thread
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 12 18:47:48 2022 0%
MLE IBD: Tue Apr 12 18:47:48 2022 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)
# of samples: 30
# of SNPs: 7,142
using 1 thread
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)
# of samples: 30
# of SNPs: 250
using 1 thread
MLE IBD: the sum of all selected genotypes (0,1,2) = 7859
MLE IBD: Tue Apr 12 18:47:48 2022 0%
MLE IBD: Tue Apr 12 18:47:49 2022 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)
# of samples: 25
# of SNPs: 250
using 1 thread
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 12 18:47:49 2022 0%
MLE IBD: Tue Apr 12 18:47:49 2022 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)
# of samples: 92
# of SNPs: 7,506
using 1 thread
PLINK IBD: the sum of all selected genotypes (0,1,2) = 702139
Tue Apr 12 18:47:49 2022 (internal increment: 65536)
[..................................................] 0%, ETC: ---
[==================================================] 100%, completed, 0s
Tue Apr 12 18:47:49 2022 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)
# of samples: 93
# of SNPs: 8,160
using 1 thread
PLINK IBD: the sum of all selected genotypes (0,1,2) = 755648
Tue Apr 12 18:47:49 2022 (internal increment: 65536)
[..................................................] 0%, ETC: ---
[==================================================] 100%, completed, 0s
Tue Apr 12 18:47:49 2022 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)
# of samples: 93
# of SNPs: 8,160
using 1 thread
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 12 18:47:49 2022 (internal increment: 65536)
[..................................................] 0%, ETC: ---
[==================================================] 100%, completed, 0s
Tue Apr 12 18:47:49 2022 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)
# of samples: 25
# of SNPs: 8,160
using 1 thread
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 12 18:47:49 2022 (internal increment: 65536)
[..................................................] 0%, ETC: ---
[==================================================] 100%, completed, 0s
Tue Apr 12 18:47:49 2022 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)
# of samples: 93
# of SNPs: 8,160
using 1 thread
PLINK IBD: the sum of all selected genotypes (0,1,2) = 755648
Tue Apr 12 18:47:49 2022 (internal increment: 65536)
[..................................................] 0%, ETC: ---
[==================================================] 100%, completed, 0s
Tue Apr 12 18:47:49 2022 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)
# of samples: 279
# of SNPs: 8,722
using 1 thread
IBS: the sum of all selected genotypes (0,1,2) = 2446510
Tue Apr 12 18:47:49 2022 (internal increment: 65536)
[..................................................] 0%, ETC: ---
[==================================================] 100%, completed, 1s
Tue Apr 12 18:47:50 2022 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)
# of samples: 279
# of SNPs: 8,722
using 1 thread
IBS: the sum of all selected genotypes (0,1,2) = 2446510
Tue Apr 12 18:47:50 2022 (internal increment: 65536)
[..................................................] 0%, ETC: ---
[==================================================] 100%, completed, 0s
Tue Apr 12 18:47:50 2022 Done.
FUNCTION: snpgdsIndInb
Estimating individual inbreeding coefficients:
Excluding 365 SNPs on non-autosomes
Excluding 1 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
# of samples: 279
# of SNPs: 8,722
using 1 thread
[..................................................] 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)
# of samples: 279
# of SNPs: 8,722
using 1 thread
Individual Beta: the sum of all selected genotypes (0,1,2) = 2446510
CPU capabilities: Double-Precision SSE2
Tue Apr 12 18:47:50 2022 (internal increment: 65536)
[..................................................] 0%, ETC: ---
[==================================================] 100%, completed, 1s
Tue Apr 12 18:47:51 2022 Done.
FUNCTION: snpgdsLDMat
Linkage Disequilibrium (LD) estimation on genotypes:
# of samples: 279
# of SNPs: 203
using 1 thread
method: composite
LD matrix: the sum of all selected genotypes (0,1,2) = 56582
Linkage Disequilibrium (LD) estimation on genotypes:
# of samples: 279
# of SNPs: 203
using 1 thread
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)
# of samples: 279
# of SNPs: 8,722
using 1 thread
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.
List of 22
$ chr1 : int [1:545] 1 2 4 5 7 10 12 14 15 16 ...
$ chr2 : int [1:540] 717 718 719 720 721 723 724 725 726 727 ...
$ chr3 : int [1:455] 1459 1460 1461 1464 1466 1468 1469 1471 1472 1473 ...
$ chr4 : int [1:413] 2068 2069 2070 2071 2072 2074 2075 2076 2077 2078 ...
$ chr5 : int [1:435] 2630 2631 2633 2635 2636 2637 2638 2640 2642 2643 ...
$ chr6 : int [1:428] 3196 3197 3198 3200 3201 3204 3205 3206 3207 3208 ...
$ chr7 : int [1:356] 3761 3762 3763 3766 3767 3768 3770 3771 3772 3773 ...
$ chr8 : int [1:347] 4233 4234 4235 4236 4237 4238 4239 4240 4241 4242 ...
$ chr9 : int [1:324] 4721 4722 4724 4727 4728 4730 4731 4732 4733 4735 ...
$ chr10: int [1:358] 5138 5139 5140 5143 5144 5145 5146 5147 5148 5149 ...
$ chr11: int [1:348] 5620 5621 5623 5624 5625 5626 5628 5629 5630 5631 ...
$ chr12: int [1:328] 6067 6068 6069 6070 6073 6074 6075 6077 6078 6079 ...
$ chr13: int [1:262] 6494 6497 6498 6499 6500 6501 6503 6505 6507 6509 ...
$ chr14: int [1:216] 6840 6841 6842 6843 6844 6845 6846 6847 6848 6850 ...
$ chr15: int [1:200] 7120 7121 7122 7124 7125 7126 7127 7128 7129 7130 ...
$ chr16: int [1:202] 7382 7383 7384 7385 7387 7388 7389 7391 7392 7394 ...
$ chr17: int [1:153] 7660 7661 7662 7663 7664 7665 7666 7667 7668 7669 ...
$ chr18: int [1:196] 7867 7868 7869 7870 7871 7872 7873 7874 7875 7877 ...
$ chr19: int [1:102] 8133 8135 8136 8137 8138 8139 8140 8141 8142 8144 ...
$ chr20: int [1:164] 8253 8254 8257 8258 8259 8260 8261 8262 8265 8266 ...
$ chr21: int [1:97] 8482 8484 8485 8486 8487 8488 8489 8490 8491 8492 ...
$ chr22: int [1:88] 8608 8609 8610 8612 8613 8614 8615 8617 8618 8619 ...
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)
# of samples: 279
# of SNPs: 6,800
using 1 thread
GRM Calculation: the sum of all selected genotypes (0,1,2) = 1908966
CPU capabilities: Double-Precision SSE2
Tue Apr 12 18:47:51 2022 (internal increment: 13960)
[..................................................] 0%, ETC: ---
[==================================================] 100%, completed, 1s
Tue Apr 12 18:47:52 2022 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)
# of samples: 279
# of SNPs: 3,400
using 1 thread
GRM Calculation: the sum of all selected genotypes (0,1,2) = 951558
CPU capabilities: Double-Precision SSE2
Tue Apr 12 18:47:52 2022 (internal increment: 13960)
[..................................................] 0%, ETC: ---
[==================================================] 100%, completed, 0s
Saving to the GDS file:
[..................................................] 0%, ETC: ---
[==================================================] 100%, completed, 1s
Tue Apr 12 18:47:53 2022 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)
# of samples: 279
# of SNPs: 3,400
using 1 thread
GRM Calculation: the sum of all selected genotypes (0,1,2) = 957408
CPU capabilities: Double-Precision SSE2
Tue Apr 12 18:47:53 2022 (internal increment: 13960)
[..................................................] 0%, ETC: ---
[==================================================] 100%, completed, 0s
Saving to the GDS file:
[..................................................] 0%, ETC: ---
[==================================================] 100%, completed, 0s
Tue Apr 12 18:47:53 2022 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, 0s
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)
# of samples: 279
# of SNPs: 8,722
using 1 thread
# of principal components: 32
PCA: the sum of all selected genotypes (0,1,2) = 2446510
CPU capabilities: Double-Precision SSE2
Tue Apr 12 18:47:54 2022 (internal increment: 13960)
[..................................................] 0%, ETC: ---
[==================================================] 100%, completed, 1s
Tue Apr 12 18:47:55 2022 Begin (eigenvalues and eigenvectors)
Tue Apr 12 18:47:55 2022 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)
# of samples: 279
# of SNPs: 8,722
using 1 thread
# of principal components: 32
PCA: the sum of all selected genotypes (0,1,2) = 2446510
CPU capabilities: Double-Precision SSE2
Tue Apr 12 18:47:55 2022 (internal increment: 13960)
[..................................................] 0%, ETC: ---
[==================================================] 100%, completed, 1s
Tue Apr 12 18:47:56 2022 Begin (eigenvalues and eigenvectors)
Tue Apr 12 18:47:56 2022 Done.
SNP Correlation:
# of samples: 279
# of SNPs: 9,088
using 1 thread
Correlation: the sum of all selected genotypes (0,1,2) = 2553065
Tue Apr 12 18:47:56 2022 (internal increment: 65536)
[..................................................] 0%, ETC: ---
[==================================================] 100%, completed, 0s
Tue Apr 12 18:47:56 2022 Done.
SNP Correlation:
# of samples: 279
# of SNPs: 9,088
using 1 thread
Creating 'test.gds' ...
Correlation: the sum of all selected genotypes (0,1,2) = 2553065
Tue Apr 12 18:47:56 2022
[..................................................] 0%, ETC: ---
[==================================================] 100%, completed, 0s
Tue Apr 12 18:47:56 2022 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)
# of samples: 279
# of SNPs: 8,722
using 1 thread
# of principal components: 8
PCA: the sum of all selected genotypes (0,1,2) = 2446510
CPU capabilities: Double-Precision SSE2
Tue Apr 12 18:47:56 2022 (internal increment: 13960)
[..................................................] 0%, ETC: ---
[==================================================] 100%, completed, 1s
Tue Apr 12 18:47:57 2022 Begin (eigenvalues and eigenvectors)
Tue Apr 12 18:47:57 2022 Done.
SNP Loading:
# of samples: 279
# of SNPs: 8,722
using 1 thread
using the top 8 eigenvectors
SNP Loading: the sum of all selected genotypes (0,1,2) = 2446510
Tue Apr 12 18:47:57 2022 (internal increment: 65536)
[..................................................] 0%, ETC: ---
[==================================================] 100%, completed, 0s
Tue Apr 12 18:47:57 2022 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)
# of samples: 279
# of SNPs: 8,722
using 1 thread
# of principal components: 8
PCA: the sum of all selected genotypes (0,1,2) = 2446510
CPU capabilities: Double-Precision SSE2
Tue Apr 12 18:47:57 2022 (internal increment: 13960)
[..................................................] 0%, ETC: ---
[==================================================] 100%, completed, 1s
Tue Apr 12 18:47:58 2022 Begin (eigenvalues and eigenvectors)
Tue Apr 12 18:47:58 2022 Done.
SNP Loading:
# of samples: 279
# of SNPs: 8,722
using 1 thread
using the top 8 eigenvectors
SNP Loading: the sum of all selected genotypes (0,1,2) = 2446510
Tue Apr 12 18:47:58 2022 (internal increment: 65536)
[..................................................] 0%, ETC: ---
[==================================================] 100%, completed, 0s
Tue Apr 12 18:47:58 2022 Done.
Sample Loading:
# of samples: 100
# of SNPs: 8,722
using 1 thread
using the top 8 eigenvectors
Sample Loading: the sum of all selected genotypes (0,1,2) = 878146
Tue Apr 12 18:47:58 2022 (internal increment: 65536)
[..................................................] 0%, ETC: ---
[==================================================] 100%, completed, 0s
Tue Apr 12 18:47:58 2022 Done.
FUNCTION: snpgdsPED2GDS
Converting from GDS to PLINK PED:
Output a MAP file DONE.
Output a PED file ...
Output: Tue Apr 12 18:47:58 2022 0%
Output: Tue Apr 12 18:47:58 2022 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)
# of samples: 93
# of SNPs: 7,077
using 1 thread
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)
# of samples: 25
# of SNPs: 250
using 1 thread
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 12 18:48:00 2022 0%
MLE IBD: Tue Apr 12 18:48:00 2022 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)
# of samples: 25
# of SNPs: 250
using 1 thread
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 12 18:48:00 2022 (internal increment: 65536)
[..................................................] 0%, ETC: ---
[==================================================] 100%, completed, 0s
Tue Apr 12 18:48:00 2022 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)
# of samples: 25
# of SNPs: 250
using 1 thread
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 12 18:48:00 2022 0%
MLE IBD: Tue Apr 12 18:48:01 2022 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)
# of samples: 93
# of SNPs: 7,077
using 1 thread
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)
# of samples: 25
# of SNPs: 250
using 1 thread
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 12 18:48:01 2022 0%
MLE IBD: Tue Apr 12 18:48:01 2022 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)
# of samples: 25
# of SNPs: 250
using 1 thread
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 12 18:48:01 2022 (internal increment: 65536)
[..................................................] 0%, ETC: ---
[==================================================] 100%, completed, 0s
Tue Apr 12 18:48:01 2022 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
Pair Score Calculation:
# of samples: 120
# of SNPs: 8,723
Method: IBS
Genotype Score: the sum of all selected genotypes (0,1,2) = 1050236
List of 3
$ sample.id: chr [1:120] "NA19139" "NA19160" "NA07034" "NA12814" ...
$ snp.id : int [1:8723] 1 2 3 4 5 6 7 8 9 10 ...
$ score :'data.frame': 60 obs. of 5 variables:
..$ Avg : num [1:60] 1.72 1.73 1.71 1.72 1.73 ...
..$ SD : num [1:60] 0.452 0.443 0.457 0.45 0.443 ...
..$ Num : int [1:60] 8684 8627 8669 8637 8682 8634 8654 8678 8680 8679 ...
..$ Sample1: chr [1:60] "NA19139" "NA10847" "NA18515" "NA19129" ...
..$ Sample2: chr [1:60] "NA19138" "NA12146" "NA18516" "NA19128" ...
Pair Score Calculation:
# of samples: 120
# of SNPs: 8,723
Method: IBS
Genotype Score: the sum of all selected genotypes (0,1,2) = 1050236
List of 3
$ sample.id: chr [1:120] "NA19139" "NA19160" "NA07034" "NA12814" ...
$ snp.id : int [1:8723] 1 2 3 4 5 6 7 8 9 10 ...
$ score :'data.frame': 60 obs. of 5 variables:
..$ Avg : num [1:60] 0.999 1 1 1 1 ...
..$ SD : num [1:60] 0.024 0 0.0186 0.0215 0.0215 ...
..$ Num : int [1:60] 8684 8627 8669 8637 8682 8634 8654 8678 8680 8679 ...
..$ Sample1: chr [1:60] "NA19139" "NA10847" "NA18515" "NA19129" ...
..$ Sample2: chr [1:60] "NA19138" "NA12146" "NA18516" "NA19128" ...
Pair Score Calculation:
# of samples: 120
# of SNPs: 8,723
Method: IBS
Genotype Score: the sum of all selected genotypes (0,1,2) = 1050236
List of 3
$ sample.id: chr [1:120] "NA19139" "NA19160" "NA07034" "NA12814" ...
$ snp.id : int [1:8723] 1 2 3 4 5 6 7 8 9 10 ...
$ score : num [1:3, 1:8723] 1.75 0.437 60 1.583 0.497 ...
..- attr(*, "dimnames")=List of 2
.. ..$ : chr [1:3] "Avg" "SD" "Num"
.. ..$ : NULL
Pair Score Calculation:
# of samples: 120
# of SNPs: 8,723
Method: IBS
Genotype Score: the sum of all selected genotypes (0,1,2) = 1050236
List of 3
$ sample.id: chr [1:120] "NA19139" "NA19160" "NA07034" "NA12814" ...
$ snp.id : int [1:8723] 1 2 3 4 5 6 7 8 9 10 ...
$ score : int [1:60, 1:8723] 1 1 2 2 2 2 2 1 2 2 ...
Pair Score Calculation:
# of samples: 120
# of SNPs: 8,723
Method: IBS
Output: /Users/biocbuild/bbs-3.14-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)
# of samples: 279
# of SNPs: 9,080
using 1 thread
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 12 18:48:02 2022, Chromosome 1 (716 SNPs), 2448 windows
Tue Apr 12 18:48:03 2022, Chromosome 2 (742 SNPs), 2416 windows
Tue Apr 12 18:48:03 2022, Chromosome 3 (609 SNPs), 1985 windows
Tue Apr 12 18:48:03 2022, Chromosome 4 (562 SNPs), 1894 windows
Tue Apr 12 18:48:03 2022, Chromosome 5 (566 SNPs), 1797 windows
Tue Apr 12 18:48:03 2022, Chromosome 6 (565 SNPs), 1694 windows
Tue Apr 12 18:48:03 2022, Chromosome 7 (472 SNPs), 1573 windows
Tue Apr 12 18:48:03 2022, Chromosome 8 (488 SNPs), 1445 windows
Tue Apr 12 18:48:03 2022, Chromosome 9 (416 SNPs), 1393 windows
Tue Apr 12 18:48:03 2022, Chromosome 10 (483 SNPs), 1343 windows
Tue Apr 12 18:48:04 2022, Chromosome 11 (447 SNPs), 1338 windows
Tue Apr 12 18:48:04 2022, Chromosome 12 (427 SNPs), 1316 windows
Tue Apr 12 18:48:04 2022, Chromosome 13 (344 SNPs), 948 windows
Tue Apr 12 18:48:04 2022, Chromosome 14 (281 SNPs), 847 windows
Tue Apr 12 18:48:04 2022, Chromosome 15 (262 SNPs), 774 windows
Tue Apr 12 18:48:04 2022, Chromosome 16 (278 SNPs), 873 windows
Tue Apr 12 18:48:04 2022, Chromosome 17 (207 SNPs), 773 windows
Tue Apr 12 18:48:04 2022, Chromosome 18 (266 SNPs), 753 windows
Tue Apr 12 18:48:04 2022, Chromosome 19 (120 SNPs), 627 windows
Tue Apr 12 18:48:04 2022, Chromosome 20 (229 SNPs), 602 windows
Tue Apr 12 18:48:04 2022, Chromosome 21 (126 SNPs), 311 windows
Tue Apr 12 18:48:04 2022, Chromosome 22 (116 SNPs), 312 windows
Tue Apr 12 18:48:04 2022, Chromosome 23 (358 SNPs), 1507 windows
Tue Apr 12 18:48:04 2022 Done.
FUNCTION: snpgdsSummary
The file name: /Library/Frameworks/R.framework/Versions/4.1/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-3.14-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-3.14-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
Start file conversion from VCF to SNP GDS ...
Method: extracting biallelic SNPs
Number of samples: 3
Parsing "/Library/Frameworks/R.framework/Versions/4.1/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-3.14-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: extracting biallelic SNPs
Number of samples: 3
Parsing "/Library/Frameworks/R.framework/Versions/4.1/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-3.14-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/4.1/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-3.14-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/4.1/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-3.14-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/4.1/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-3.14-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/4.1/Resources/library/SNPRelate/extdata/sequence.vcf
content: 5 rows x 12 columns
Tue Apr 12 18:48:05 2022 store sample id, snp id, position, and chromosome.
start writing: 3 samples, 2 SNPs ...
file: /Library/Frameworks/R.framework/Versions/4.1/Resources/library/SNPRelate/extdata/sequence.vcf
[1] 1
Tue Apr 12 18:48:05 2022 Done.
The file name: /Users/biocbuild/bbs-3.14-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/4.1/Resources/library/SNPRelate/extdata/sequence.vcf
content: 5 rows x 12 columns
Tue Apr 12 18:48:05 2022 store sample id, snp id, position, and chromosome.
start writing: 3 samples, 2 SNPs ...
file: /Library/Frameworks/R.framework/Versions/4.1/Resources/library/SNPRelate/extdata/sequence.vcf
[1] 1
Tue Apr 12 18:48:05 2022 Done.
The file name: /Users/biocbuild/bbs-3.14-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/4.1/Resources/library/SNPRelate/extdata/sequence.vcf
content: 5 rows x 12 columns
Tue Apr 12 18:48:05 2022 store sample id, snp id, position, and chromosome.
start writing: 3 samples, 5 SNPs ...
file: /Library/Frameworks/R.framework/Versions/4.1/Resources/library/SNPRelate/extdata/sequence.vcf
Tue Apr 12 18:48:05 2022 Done.
Some of 'snp.allele' are not standard (e.g., A/G,T).
The file name: /Users/biocbuild/bbs-3.14-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/4.1/Resources/library/SNPRelate/extdata/sequence.vcf
content: 5 rows x 12 columns
Tue Apr 12 18:48:05 2022 store sample id, snp id, position, and chromosome.
start writing: 3 samples, 5 SNPs ...
file: /Library/Frameworks/R.framework/Versions/4.1/Resources/library/SNPRelate/extdata/sequence.vcf
Tue Apr 12 18:48:05 2022 Done.
Some of 'snp.allele' are not standard (e.g., A/G,T).
The file name: /Users/biocbuild/bbs-3.14-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:
# of samples: 90
# of SNPs: 9,088
using 1 thread
Correlation: the sum of all selected genotypes (0,1,2) = 824424
Tue Apr 12 18:48:07 2022 (internal increment: 65536)
[..................................................] 0%, ETC: ---
[==================================================] 100%, completed, 0s
Tue Apr 12 18:48:07 2022 Done.
SNP Correlation:
# of samples: 90
# of SNPs: 9,088
using 1 thread
Creating 'test.gds' ...
Correlation: the sum of all selected genotypes (0,1,2) = 824424
Tue Apr 12 18:48:07 2022
[..................................................] 0%, ETC: ---
[==================================================] 100%, completed, 0s
Tue Apr 12 18:48:07 2022 Done.
SNP Loading:
# of samples: 90
# of SNPs: 8,695
using 1 thread
using the top 8 eigenvectors
SNP Loading: the sum of all selected genotypes (0,1,2) = 787449
Tue Apr 12 18:48:07 2022 (internal increment: 65536)
[..................................................] 0%, ETC: ---
[==================================================] 100%, completed, 0s
Tue Apr 12 18:48:07 2022 Done.
Sample Loading:
# of samples: 100
# of SNPs: 8,695
using 1 thread
using the top 8 eigenvectors
Sample Loading: the sum of all selected genotypes (0,1,2) = 875255
Tue Apr 12 18:48:07 2022 (internal increment: 65536)
[..................................................] 0%, ETC: ---
[==================================================] 100%, completed, 0s
Tue Apr 12 18:48:07 2022 Done.
SNP Correlation:
# of samples: 90
# of SNPs: 9,088
using 2 threads
Correlation: the sum of all selected genotypes (0,1,2) = 824424
Tue Apr 12 18:48:07 2022 (internal increment: 65536)
[..................................................] 0%, ETC: ---
[==================================================] 100%, completed, 0s
Tue Apr 12 18:48:07 2022 Done.
SNP Correlation:
# of samples: 90
# of SNPs: 9,088
using 2 threads
Creating 'test.gds' ...
Correlation: the sum of all selected genotypes (0,1,2) = 824424
Tue Apr 12 18:48:07 2022
[..................................................] 0%, ETC: ---
[==================================================] 100%, completed, 0s
Tue Apr 12 18:48:07 2022 Done.
SNP Loading:
# of samples: 90
# of SNPs: 8,695
using 1 thread
using the top 8 eigenvectors
SNP Loading: the sum of all selected genotypes (0,1,2) = 787449
Tue Apr 12 18:48:07 2022 (internal increment: 65536)
[..................................................] 0%, ETC: ---
[==================================================] 100%, completed, 0s
Tue Apr 12 18:48:07 2022 Done.
Sample Loading:
# of samples: 100
# of SNPs: 8,695
using 1 thread
using the top 8 eigenvectors
Sample Loading: the sum of all selected genotypes (0,1,2) = 875255
Tue Apr 12 18:48:07 2022 (internal increment: 65536)
[..................................................] 0%, ETC: ---
[==================================================] 100%, completed, 0s
Tue Apr 12 18:48:07 2022 Done.
RUNIT TEST PROTOCOL -- Tue Apr 12 18:48:08 2022
***********************************************
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
52.171 3.169 55.255
SNPRelate.Rcheck/SNPRelate-Ex.timings
| name | user | system | elapsed | |
| SNPGDSFileClass-class | 0.038 | 0.002 | 0.040 | |
| SNPRelate-package | 1.887 | 0.179 | 2.075 | |
| snpgdsAdmixPlot | 0.714 | 0.015 | 0.733 | |
| snpgdsAdmixProp | 0.709 | 0.014 | 0.723 | |
| snpgdsAlleleSwitch | 0.137 | 0.013 | 0.150 | |
| snpgdsApartSelection | 0.154 | 0.018 | 0.173 | |
| snpgdsBED2GDS | 0.166 | 0.036 | 0.202 | |
| snpgdsClose | 0.044 | 0.001 | 0.045 | |
| snpgdsCombineGeno | 0.156 | 0.042 | 0.198 | |
| snpgdsCreateGeno | 0.649 | 0.018 | 0.669 | |
| snpgdsCreateGenoSet | 0.224 | 0.018 | 0.243 | |
| snpgdsCutTree | 2.944 | 0.133 | 3.086 | |
| snpgdsDiss | 2.295 | 0.013 | 2.310 | |
| snpgdsDrawTree | 1.940 | 0.014 | 1.957 | |
| snpgdsEIGMIX | 0.602 | 0.009 | 0.612 | |
| snpgdsErrMsg | 0 | 0 | 0 | |
| snpgdsExampleFileName | 0.001 | 0.001 | 0.001 | |
| snpgdsFst | 0.031 | 0.004 | 0.036 | |
| snpgdsGDS2BED | 0.098 | 0.015 | 0.113 | |
| snpgdsGDS2Eigen | 0.764 | 0.102 | 0.867 | |
| snpgdsGDS2PED | 0.560 | 0.074 | 0.642 | |
| snpgdsGEN2GDS | 0 | 0 | 0 | |
| snpgdsGRM | 1.563 | 0.036 | 1.600 | |
| snpgdsGetGeno | 0.101 | 0.028 | 0.129 | |
| snpgdsHCluster | 2.427 | 0.057 | 2.489 | |
| snpgdsHWE | 0.028 | 0.004 | 0.032 | |
| snpgdsIBDKING | 2.576 | 0.078 | 2.703 | |
| snpgdsIBDMLE | 0.857 | 0.018 | 0.877 | |
| snpgdsIBDMLELogLik | 0.856 | 0.018 | 0.874 | |
| snpgdsIBDMoM | 0.442 | 0.045 | 0.490 | |
| snpgdsIBDSelection | 0.169 | 0.017 | 0.188 | |
| snpgdsIBS | 0.375 | 0.011 | 0.388 | |
| snpgdsIBSNum | 0.357 | 0.021 | 0.380 | |
| snpgdsIndInb | 0.037 | 0.003 | 0.040 | |
| snpgdsIndInbCoef | 0.010 | 0.002 | 0.012 | |
| snpgdsIndivBeta | 0.307 | 0.008 | 0.315 | |
| snpgdsLDMat | 0.385 | 0.034 | 0.422 | |
| snpgdsLDpair | 0.005 | 0.003 | 0.008 | |
| snpgdsLDpruning | 0.066 | 0.011 | 0.077 | |
| snpgdsMergeGRM | 2.779 | 0.090 | 2.870 | |
| snpgdsOpen | 0.043 | 0.003 | 0.046 | |
| snpgdsOption | 0.003 | 0.003 | 0.006 | |
| snpgdsPCA | 0.870 | 0.033 | 0.906 | |
| snpgdsPCACorr | 0.830 | 0.039 | 0.871 | |
| snpgdsPCASNPLoading | 0.927 | 0.012 | 0.942 | |
| snpgdsPCASampLoading | 0.675 | 0.012 | 0.687 | |
| snpgdsPED2GDS | 1.781 | 0.105 | 1.899 | |
| snpgdsPairIBD | 1.387 | 0.026 | 1.416 | |
| snpgdsPairIBDMLELogLik | 0.658 | 0.017 | 0.675 | |
| snpgdsPairScore | 0.513 | 0.102 | 0.617 | |
| snpgdsSNPList | 0.011 | 0.002 | 0.012 | |
| snpgdsSNPListIntersect | 0.074 | 0.005 | 0.079 | |
| snpgdsSNPRateFreq | 0.215 | 0.009 | 0.225 | |
| snpgdsSampMissRate | 0.008 | 0.002 | 0.010 | |
| snpgdsSelectSNP | 0.009 | 0.002 | 0.010 | |
| snpgdsSlidingWindow | 1.165 | 0.135 | 1.302 | |
| snpgdsSummary | 0.077 | 0.002 | 0.079 | |
| snpgdsTranspose | 0.203 | 0.020 | 0.224 | |
| snpgdsVCF2GDS | 0.397 | 0.318 | 0.720 | |
| snpgdsVCF2GDS_R | 0.181 | 0.158 | 0.341 | |