Back to Multiple platform build/check report for BioC 3.19: simplified long |
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This page was generated on 2024-10-18 20:41 -0400 (Fri, 18 Oct 2024).
Hostname | OS | Arch (*) | R version | Installed pkgs |
---|---|---|---|---|
nebbiolo1 | Linux (Ubuntu 22.04.3 LTS) | x86_64 | 4.4.1 (2024-06-14) -- "Race for Your Life" | 4763 |
palomino7 | Windows Server 2022 Datacenter | x64 | 4.4.1 (2024-06-14 ucrt) -- "Race for Your Life" | 4500 |
merida1 | macOS 12.7.5 Monterey | x86_64 | 4.4.1 (2024-06-14) -- "Race for Your Life" | 4530 |
kjohnson1 | macOS 13.6.6 Ventura | arm64 | 4.4.1 (2024-06-14) -- "Race for Your Life" | 4480 |
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 |
Package 2016/2300 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
SNPRelate 1.38.1 (landing page) Xiuwen Zheng
| nebbiolo1 | Linux (Ubuntu 22.04.3 LTS) / x86_64 | OK | OK | OK | |||||||||
palomino7 | Windows Server 2022 Datacenter / x64 | OK | OK | OK | OK | |||||||||
merida1 | macOS 12.7.5 Monterey / x86_64 | OK | OK | OK | OK | |||||||||
kjohnson1 | macOS 13.6.6 Ventura / arm64 | OK | OK | OK | NA | |||||||||
To the developers/maintainers of the SNPRelate package: - Allow up to 24 hours (and sometimes 48 hours) for your latest push to git@git.bioconductor.org:packages/SNPRelate.git to reflect on this report. See Troubleshooting Build Report for more information. - Use the following Renviron settings to reproduce errors and warnings. - If 'R CMD check' started to fail recently on the Linux builder(s) over a missing dependency, add the missing dependency to 'Suggests:' in your DESCRIPTION file. See Renviron.bioc for more information. |
Package: SNPRelate |
Version: 1.38.1 |
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_1.38.1.tar.gz |
StartedAt: 2024-10-17 13:28:20 -0400 (Thu, 17 Oct 2024) |
EndedAt: 2024-10-17 13:32:11 -0400 (Thu, 17 Oct 2024) |
EllapsedTime: 231.3 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_1.38.1.tar.gz ### ############################################################################## ############################################################################## * using log directory ‘/Users/biocbuild/bbs-3.19-bioc/meat/SNPRelate.Rcheck’ * using R version 4.4.1 (2024-06-14) * using platform: x86_64-apple-darwin20 * R was compiled by Apple clang version 14.0.0 (clang-1400.0.29.202) GNU Fortran (GCC) 12.2.0 * running under: macOS Monterey 12.7.6 * using session charset: UTF-8 * using option ‘--no-vignettes’ * checking for file ‘SNPRelate/DESCRIPTION’ ... OK * checking extension type ... Package * this is package ‘SNPRelate’ version ‘1.38.1’ * checking package namespace information ... OK * checking package dependencies ... OK * checking if this is a source package ... OK * checking if there is a namespace ... OK * checking for hidden files and directories ... OK * checking for portable file names ... OK * checking for sufficient/correct file permissions ... OK * checking whether package ‘SNPRelate’ can be installed ... OK * used C compiler: ‘Apple clang version 14.0.0 (clang-1400.0.29.202)’ * used C++ compiler: ‘Apple clang version 14.0.0 (clang-1400.0.29.202)’ * used SDK: ‘MacOSX11.3.sdk’ * 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 code 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 whether startup messages can be suppressed ... 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 LazyData ... 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 ... 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-3.19-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/4.4-x86_64/Resources/library’ * installing *source* package ‘SNPRelate’ ... ** using staged installation ** libs using C compiler: ‘Apple clang version 14.0.0 (clang-1400.0.29.202)’ using C++ compiler: ‘Apple clang version 14.0.0 (clang-1400.0.29.202)’ using SDK: ‘MacOSX11.3.sdk’ clang++ -arch x86_64 -std=gnu++17 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -DUSING_R -DUSE_FC_LEN_T -I. -I'/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/gdsfmt/include' -I/opt/R/x86_64/include -fPIC -falign-functions=64 -Wall -g -O2 -c ConvToGDS.cpp -o ConvToGDS.o clang -arch x86_64 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -DUSING_R -DUSE_FC_LEN_T -I. -I'/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/gdsfmt/include' -I/opt/R/x86_64/include -fPIC -falign-functions=64 -Wall -g -O2 -c R_SNPRelate.c -o R_SNPRelate.o clang++ -arch x86_64 -std=gnu++17 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -DUSING_R -DUSE_FC_LEN_T -I. -I'/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/gdsfmt/include' -I/opt/R/x86_64/include -fPIC -falign-functions=64 -Wall -g -O2 -c SNPRelate.cpp -o SNPRelate.o clang++ -arch x86_64 -std=gnu++17 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -DUSING_R -DUSE_FC_LEN_T -I. -I'/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/gdsfmt/include' -I/opt/R/x86_64/include -fPIC -falign-functions=64 -Wall -g -O2 -c ThreadPool.cpp -o ThreadPool.o clang++ -arch x86_64 -std=gnu++17 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -DUSING_R -DUSE_FC_LEN_T -I. -I'/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/gdsfmt/include' -I/opt/R/x86_64/include -fPIC -falign-functions=64 -Wall -g -O2 -c dGenGWAS.cpp -o dGenGWAS.o clang++ -arch x86_64 -std=gnu++17 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -DUSING_R -DUSE_FC_LEN_T -I. -I'/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/gdsfmt/include' -I/opt/R/x86_64/include -fPIC -falign-functions=64 -Wall -g -O2 -c dVect.cpp -o dVect.o clang++ -arch x86_64 -std=gnu++17 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -DUSING_R -DUSE_FC_LEN_T -I. -I'/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/gdsfmt/include' -I/opt/R/x86_64/include -fPIC -falign-functions=64 -Wall -g -O2 -c genBeta.cpp -o genBeta.o clang++ -arch x86_64 -std=gnu++17 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -DUSING_R -DUSE_FC_LEN_T -I. -I'/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/gdsfmt/include' -I/opt/R/x86_64/include -fPIC -falign-functions=64 -Wall -g -O2 -c genEIGMIX.cpp -o genEIGMIX.o clang++ -arch x86_64 -std=gnu++17 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -DUSING_R -DUSE_FC_LEN_T -I. -I'/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/gdsfmt/include' -I/opt/R/x86_64/include -fPIC -falign-functions=64 -Wall -g -O2 -c genFst.cpp -o genFst.o clang++ -arch x86_64 -std=gnu++17 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -DUSING_R -DUSE_FC_LEN_T -I. -I'/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/gdsfmt/include' -I/opt/R/x86_64/include -fPIC -falign-functions=64 -Wall -g -O2 -c genHWE.cpp -o genHWE.o clang++ -arch x86_64 -std=gnu++17 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -DUSING_R -DUSE_FC_LEN_T -I. -I'/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/gdsfmt/include' -I/opt/R/x86_64/include -fPIC -falign-functions=64 -Wall -g -O2 -c genIBD.cpp -o genIBD.o clang++ -arch x86_64 -std=gnu++17 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -DUSING_R -DUSE_FC_LEN_T -I. -I'/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/gdsfmt/include' -I/opt/R/x86_64/include -fPIC -falign-functions=64 -Wall -g -O2 -c genIBS.cpp -o genIBS.o clang++ -arch x86_64 -std=gnu++17 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -DUSING_R -DUSE_FC_LEN_T -I. -I'/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/gdsfmt/include' -I/opt/R/x86_64/include -fPIC -falign-functions=64 -Wall -g -O2 -c genKING.cpp -o genKING.o clang++ -arch x86_64 -std=gnu++17 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -DUSING_R -DUSE_FC_LEN_T -I. -I'/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/gdsfmt/include' -I/opt/R/x86_64/include -fPIC -falign-functions=64 -Wall -g -O2 -c genLD.cpp -o genLD.o clang++ -arch x86_64 -std=gnu++17 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -DUSING_R -DUSE_FC_LEN_T -I. -I'/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/gdsfmt/include' -I/opt/R/x86_64/include -fPIC -falign-functions=64 -Wall -g -O2 -c genPCA.cpp -o genPCA.o clang++ -arch x86_64 -std=gnu++17 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -DUSING_R -DUSE_FC_LEN_T -I. -I'/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/gdsfmt/include' -I/opt/R/x86_64/include -fPIC -falign-functions=64 -Wall -g -O2 -c genSlideWin.cpp -o genSlideWin.o clang++ -arch x86_64 -std=gnu++17 -dynamiclib -Wl,-headerpad_max_install_names -undefined dynamic_lookup -L/Library/Frameworks/R.framework/Resources/lib -L/opt/R/x86_64/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/opt/gfortran/lib/gcc/x86_64-apple-darwin20.0/12.2.0 -L/opt/gfortran/lib -lgfortran -lquadmath -F/Library/Frameworks/R.framework/.. -framework R -Wl,-framework -Wl,CoreFoundation installing to /Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/00LOCK-SNPRelate/00new/SNPRelate/libs ** R ** data *** moving datasets to lazyload DB ** 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 4.4.1 (2024-06-14) -- "Race for Your Life" Copyright (C) 2024 The R Foundation for Statistical Computing Platform: x86_64-apple-darwin20 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 Thu Oct 17 13:30:27 2024 (internal increment: 13960) [..................................................] 0%, ETC: --- [==================================================] 100%, completed, 1s Saving to the GDS file: [..................................................] 0%, ETC: --- [==================================================] 100%, completed, 0s Thu Oct 17 13:30:28 2024 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 Thu Oct 17 13:30:28 2024 (internal increment: 13960) [..................................................] 0%, ETC: --- [==================================================] 100%, completed, 1s Saving to the GDS file: [..................................................] 0%, ETC: --- [==================================================] 100%, completed, 0s Thu Oct 17 13:30:29 2024 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 Thu Oct 17 13:30:29 2024 (internal increment: 13960) [..................................................] 0%, ETC: --- [==================================================] 100%, completed, 1s Saving to the GDS file: [..................................................] 0%, ETC: --- [==================================================] 100%, completed, 1s Thu Oct 17 13:30:31 2024 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 Thu Oct 17 13:30:31 2024 (internal increment: 13960) [..................................................] 0%, ETC: --- [==================================================] 100%, completed, 1s Thu Oct 17 13:30:32 2024 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 Thu Oct 17 13:30:32 2024 (internal increment: 65536) [..................................................] 0%, ETC: --- [==================================================] 100%, completed, 1s Saving to the GDS file: [..................................................] 0%, ETC: --- [==================================================] 100%, completed, 0s Thu Oct 17 13:30:33 2024 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 Thu Oct 17 13:30:33 2024 (internal increment: 65536) [..................................................] 0%, ETC: --- [==================================================] 100%, completed, 0s Saving to the GDS file: [..................................................] 0%, ETC: --- [==================================================] 100%, completed, 1s Thu Oct 17 13:30:34 2024 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 Thu Oct 17 13:30:34 2024 (internal increment: 65536) [..................................................] 0%, ETC: --- [==================================================] 100%, completed, 0s Saving to the GDS file: [..................................................] 0%, ETC: --- [==================================================] 100%, completed, 1s Thu Oct 17 13:30:35 2024 Done. GRM merging: open 'tmp1.gds' (1,000 variants) open 'tmp2.gds' (2,000 variants) open 'tmp3.gds' (3,800 variants) Weight: 0.147059, 0.294118, 0.558824 Output: tmp.gds [..................................................] 0%, ETC: --- [==================================================] 100%, completed, 0s Writing ... [..................................................] 0%, ETC: --- [==================================================] 100%, completed, 0s Genetic Relationship Matrix (GRM, IndivBeta): Excluding 2,288 SNPs (non-autosomes or non-selection) Excluding 0 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN) # 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 Thu Oct 17 13:30:36 2024 (internal increment: 65536) [..................................................] 0%, ETC: --- [==================================================] 100%, completed, 0s Thu Oct 17 13:30:36 2024 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/4.4-x86_64/Resources/library/SNPRelate/extdata/plinkhapmap.bed.gz' SNP-major mode (Sample X SNP), 45.7K FAM file: '/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/SNPRelate/extdata/plinkhapmap.fam.gz' BIM file: '/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/SNPRelate/extdata/plinkhapmap.bim.gz' Thu Oct 17 13:30:43 2024 (store sample id, snp id, position, and chromosome) start writing: 60 samples, 5000 SNPs ... [..................................................] 0%, ETC: --- [==================================================] 100%, completed, 0s Thu Oct 17 13:30:43 2024 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 Thu Oct 17 13:30:43 2024 (internal increment: 64920) [..................................................] 0%, ETC: --- [==================================================] 100%, completed, 0s Thu Oct 17 13:30:43 2024 Begin (eigenvalues and eigenvectors) Thu Oct 17 13:30:43 2024 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 Thu Oct 17 13:30:43 2024 (internal increment: 65536) [..................................................] 0%, ETC: --- [==================================================] 100%, completed, 1s Thu Oct 17 13:30:44 2024 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 Thu Oct 17 13:30:44 2024 (internal increment: 65536) [..................................................] 0%, ETC: --- [==================================================] 100%, completed, 1s Thu Oct 17 13:30:45 2024 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 Thu Oct 17 13:30:45 2024 (internal increment: 13960) [..................................................] 0%, ETC: --- [==================================================] 100%, completed, 1s Thu Oct 17 13:30:46 2024 Begin (eigenvalues and eigenvectors) Thu Oct 17 13:30:46 2024 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 Thu Oct 17 13:30:46 2024 (internal increment: 13960) [..................................................] 0%, ETC: --- [==================================================] 100%, completed, 1s Thu Oct 17 13:30:47 2024 Begin (eigenvalues and eigenvectors) Thu Oct 17 13:30:47 2024 Done. FUNCTION: snpgdsAlleleSwitch Strand-switching at 50 SNP locus/loci. Unable to determine switching at 10 SNP locus/loci. FUNCTION: snpgdsApartSelection Thu Oct 17 13:30:48 2024 Chromosome 1, # of SNPs: 367 Thu Oct 17 13:30:48 2024 Chromosome 2, # of SNPs: 367 Thu Oct 17 13:30:48 2024 Chromosome 3, # of SNPs: 317 Thu Oct 17 13:30:48 2024 Chromosome 4, # of SNPs: 295 Thu Oct 17 13:30:48 2024 Chromosome 5, # of SNPs: 295 Thu Oct 17 13:30:48 2024 Chromosome 6, # of SNPs: 283 Thu Oct 17 13:30:48 2024 Chromosome 7, # of SNPs: 245 Thu Oct 17 13:30:48 2024 Chromosome 8, # of SNPs: 234 Thu Oct 17 13:30:48 2024 Chromosome 9, # of SNPs: 202 Thu Oct 17 13:30:48 2024 Chromosome 10, # of SNPs: 224 Thu Oct 17 13:30:48 2024 Chromosome 11, # of SNPs: 223 Thu Oct 17 13:30:48 2024 Chromosome 12, # of SNPs: 208 Thu Oct 17 13:30:48 2024 Chromosome 13, # of SNPs: 172 Thu Oct 17 13:30:48 2024 Chromosome 14, # of SNPs: 147 Thu Oct 17 13:30:48 2024 Chromosome 15, # of SNPs: 121 Thu Oct 17 13:30:48 2024 Chromosome 16, # of SNPs: 129 Thu Oct 17 13:30:48 2024 Chromosome 17, # of SNPs: 116 Thu Oct 17 13:30:48 2024 Chromosome 18, # of SNPs: 129 Thu Oct 17 13:30:48 2024 Chromosome 19, # of SNPs: 73 Thu Oct 17 13:30:48 2024 Chromosome 20, # of SNPs: 106 Thu Oct 17 13:30:48 2024 Chromosome 21, # of SNPs: 62 Thu Oct 17 13:30:48 2024 Chromosome 22, # of SNPs: 51 Thu Oct 17 13:30:48 2024 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/4.4-x86_64/Resources/library/SNPRelate/extdata/plinkhapmap.bed.gz' SNP-major mode (Sample X SNP), 45.7K FAM file: '/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/SNPRelate/extdata/plinkhapmap.fam.gz' BIM file: '/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/SNPRelate/extdata/plinkhapmap.bim.gz' Thu Oct 17 13:30:48 2024 (store sample id, snp id, position, and chromosome) start writing: 60 samples, 5000 SNPs ... [..................................................] 0%, ETC: --- [==================================================] 100%, completed, 0s Thu Oct 17 13:30:48 2024 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 Thu Oct 17 13:30:49 2024 (internal increment: 13960) [..................................................] 0%, ETC: --- [==================================================] 100%, completed, 0s Thu Oct 17 13:30:49 2024 Begin (eigenvalues and eigenvectors) Thu Oct 17 13:30:49 2024 Done. FUNCTION: snpgdsCreateGenoSet SNP pruning based on LD: Excluding 365 SNPs on non-autosomes Excluding 139 SNPs (monomorphic: TRUE, MAF: 0.005, missing rate: 0.05) # of samples: 279 # of SNPs: 8,584 using 1 thread sliding window: 500,000 basepairs, Inf SNPs |LD| threshold: 0.2 method: composite Chrom 1: |====================|====================| 74.30%, 532 / 716 (Thu Oct 17 13:30:50 2024) Chrom 2: |====================|====================| 72.24%, 536 / 742 (Thu Oct 17 13:30:50 2024) Chrom 3: |====================|====================| 73.40%, 447 / 609 (Thu Oct 17 13:30:50 2024) Chrom 4: |====================|====================| 72.42%, 407 / 562 (Thu Oct 17 13:30:50 2024) Chrom 5: |====================|====================| 75.80%, 429 / 566 (Thu Oct 17 13:30:50 2024) Chrom 6: |====================|====================| 73.81%, 417 / 565 (Thu Oct 17 13:30:50 2024) Chrom 7: |====================|====================| 75.21%, 355 / 472 (Thu Oct 17 13:30:50 2024) Chrom 8: |====================|====================| 69.67%, 340 / 488 (Thu Oct 17 13:30:50 2024) Chrom 9: |====================|====================| 76.92%, 320 / 416 (Thu Oct 17 13:30:50 2024) Chrom 10: |====================|====================| 73.08%, 353 / 483 (Thu Oct 17 13:30:50 2024) Chrom 11: |====================|====================| 76.51%, 342 / 447 (Thu Oct 17 13:30:50 2024) Chrom 12: |====================|====================| 74.71%, 319 / 427 (Thu Oct 17 13:30:50 2024) Chrom 13: |====================|====================| 76.74%, 264 / 344 (Thu Oct 17 13:30:50 2024) Chrom 14: |====================|====================| 76.24%, 215 / 282 (Thu Oct 17 13:30:50 2024) Chrom 15: |====================|====================| 75.95%, 199 / 262 (Thu Oct 17 13:30:50 2024) Chrom 16: |====================|====================| 70.86%, 197 / 278 (Thu Oct 17 13:30:50 2024) Chrom 17: |====================|====================| 76.33%, 158 / 207 (Thu Oct 17 13:30:50 2024) Chrom 18: |====================|====================| 73.31%, 195 / 266 (Thu Oct 17 13:30:50 2024) Chrom 19: |====================|====================| 82.50%, 99 / 120 (Thu Oct 17 13:30:50 2024) Chrom 20: |====================|====================| 70.31%, 161 / 229 (Thu Oct 17 13:30:50 2024) Chrom 21: |====================|====================| 75.40%, 95 / 126 (Thu Oct 17 13:30:50 2024) Chrom 22: |====================|====================| 75.86%, 88 / 116 (Thu Oct 17 13:30:50 2024) 6,468 markers are selected in total. Create a GDS genotype file: The new dataset consists of 279 samples and 6468 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: Thu Oct 17 13:30:50 2024 0% Dissimilarity: Thu Oct 17 13:30:51 2024 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: Thu Oct 17 13:30:54 2024 0% Dissimilarity: Thu Oct 17 13:30:55 2024 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: Thu Oct 17 13:30:57 2024 0% Dissimilarity: Thu Oct 17 13:30:59 2024 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 Thu Oct 17 13:31:00 2024 (internal increment: 13960) [..................................................] 0%, ETC: --- [==================================================] 100%, completed, 1s Thu Oct 17 13:31:01 2024 Begin (eigenvalues and eigenvectors) Thu Oct 17 13:31:01 2024 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 ... Thu Oct 17 13:31:01 2024 0% Thu Oct 17 13:31:01 2024 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: Thu Oct 17 13:31:01 2024 0% Output: Thu Oct 17 13:31:03 2024 100% Done. FUNCTION: snpgdsGDS2PED Converting from GDS to PLINK PED: Output a MAP file DONE. Output a PED file ... Output: Thu Oct 17 13:31:03 2024 0% Output: Thu Oct 17 13:31:04 2024 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 Thu Oct 17 13:31:05 2024 (internal increment: 13960) [..................................................] 0%, ETC: --- [==================================================] 100%, completed, 0s Thu Oct 17 13:31:05 2024 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 Thu Oct 17 13:31:06 2024 (internal increment: 13960) [..................................................] 0%, ETC: --- [==================================================] 100%, completed, 0s Saving to the GDS file: [..................................................] 0%, ETC: --- [==================================================] 100%, completed, 1s Thu Oct 17 13:31:07 2024 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: Thu Oct 17 13:31:07 2024 0% Dissimilarity: Thu Oct 17 13:31:09 2024 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 Thu Oct 17 13:31:11 2024 (internal increment: 65536) [..................................................] 0%, ETC: --- [==================================================] 100%, completed, 0s Thu Oct 17 13:31:11 2024 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 Thu Oct 17 13:31:11 2024 (internal increment: 65536) [..................................................] 0%, ETC: --- [==================================================] 100%, completed, 0s Thu Oct 17 13:31:11 2024 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 Thu Oct 17 13:31:13 2024 (internal increment: 65536) [..................................................] 0%, ETC: --- [==================================================] 100%, completed, 0s Thu Oct 17 13:31:13 2024 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 Thu Oct 17 13:31:13 2024 (internal increment: 65536) [..................................................] 0%, ETC: --- [==================================================] 100%, completed, 1s Thu Oct 17 13:31:14 2024 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 Thu Oct 17 13:31:14 2024 (internal increment: 65536) [..................................................] 0%, ETC: --- [==================================================] 100%, completed, 0s Thu Oct 17 13:31:14 2024 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 Chrom 1: |====================|====================| 54.75%, 392 / 716 (Thu Oct 17 13:31:15 2024) Chrom 2: |====================|====================| 54.85%, 407 / 742 (Thu Oct 17 13:31:15 2024) Chrom 3: |====================|====================| 55.99%, 341 / 609 (Thu Oct 17 13:31:15 2024) Chrom 4: |====================|====================| 56.58%, 318 / 562 (Thu Oct 17 13:31:15 2024) Chrom 5: |====================|====================| 56.36%, 319 / 566 (Thu Oct 17 13:31:15 2024) Chrom 6: |====================|====================| 53.45%, 302 / 565 (Thu Oct 17 13:31:15 2024) Chrom 7: |====================|====================| 55.72%, 263 / 472 (Thu Oct 17 13:31:15 2024) Chrom 8: |====================|====================| 50.82%, 248 / 488 (Thu Oct 17 13:31:15 2024) Chrom 9: |====================|====================| 54.81%, 228 / 416 (Thu Oct 17 13:31:15 2024) Chrom 10: |====================|====================| 49.90%, 241 / 483 (Thu Oct 17 13:31:15 2024) Chrom 11: |====================|====================| 54.81%, 245 / 447 (Thu Oct 17 13:31:15 2024) Chrom 12: |====================|====================| 54.57%, 233 / 427 (Thu Oct 17 13:31:15 2024) Chrom 13: |====================|====================| 53.49%, 184 / 344 (Thu Oct 17 13:31:15 2024) Chrom 14: |====================|====================| 56.03%, 158 / 282 (Thu Oct 17 13:31:15 2024) Chrom 15: |====================|====================| 54.58%, 143 / 262 (Thu Oct 17 13:31:15 2024) Chrom 16: |====================|====================| 54.68%, 152 / 278 (Thu Oct 17 13:31:15 2024) Chrom 17: |====================|====================| 55.56%, 115 / 207 (Thu Oct 17 13:31:15 2024) Chrom 18: |====================|====================| 55.64%, 148 / 266 (Thu Oct 17 13:31:15 2024) Chrom 19: |====================|====================| 66.67%, 80 / 120 (Thu Oct 17 13:31:15 2024) Chrom 20: |====================|====================| 53.28%, 122 / 229 (Thu Oct 17 13:31:15 2024) Chrom 21: |====================|====================| 50.79%, 64 / 126 (Thu Oct 17 13:31:15 2024) Chrom 22: |====================|====================| 51.72%, 60 / 116 (Thu Oct 17 13:31:15 2024) 4,763 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) = 8025 MLE IBD: Thu Oct 17 13:31:15 2024 0% MLE IBD: Thu Oct 17 13:31:16 2024 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: 0.536, sd: 0.286 MLE IBD: the sum of all selected genotypes (0,1,2) = 6690 MLE IBD: Thu Oct 17 13:31:16 2024 0% MLE IBD: Thu Oct 17 13:31:16 2024 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 Chrom 1: |====================|====================| 54.75%, 392 / 716 (Thu Oct 17 13:31:16 2024) Chrom 2: |====================|====================| 54.85%, 407 / 742 (Thu Oct 17 13:31:16 2024) Chrom 3: |====================|====================| 55.99%, 341 / 609 (Thu Oct 17 13:31:16 2024) Chrom 4: |====================|====================| 56.58%, 318 / 562 (Thu Oct 17 13:31:16 2024) Chrom 5: |====================|====================| 56.36%, 319 / 566 (Thu Oct 17 13:31:16 2024) Chrom 6: |====================|====================| 53.45%, 302 / 565 (Thu Oct 17 13:31:16 2024) Chrom 7: |====================|====================| 55.72%, 263 / 472 (Thu Oct 17 13:31:16 2024) Chrom 8: |====================|====================| 50.82%, 248 / 488 (Thu Oct 17 13:31:16 2024) Chrom 9: |====================|====================| 54.81%, 228 / 416 (Thu Oct 17 13:31:16 2024) Chrom 10: |====================|====================| 49.90%, 241 / 483 (Thu Oct 17 13:31:16 2024) Chrom 11: |====================|====================| 54.81%, 245 / 447 (Thu Oct 17 13:31:16 2024) Chrom 12: |====================|====================| 54.57%, 233 / 427 (Thu Oct 17 13:31:16 2024) Chrom 13: |====================|====================| 53.49%, 184 / 344 (Thu Oct 17 13:31:16 2024) Chrom 14: |====================|====================| 56.03%, 158 / 282 (Thu Oct 17 13:31:16 2024) Chrom 15: |====================|====================| 54.58%, 143 / 262 (Thu Oct 17 13:31:16 2024) Chrom 16: |====================|====================| 54.68%, 152 / 278 (Thu Oct 17 13:31:16 2024) Chrom 17: |====================|====================| 55.56%, 115 / 207 (Thu Oct 17 13:31:16 2024) Chrom 18: |====================|====================| 55.64%, 148 / 266 (Thu Oct 17 13:31:16 2024) Chrom 19: |====================|====================| 66.67%, 80 / 120 (Thu Oct 17 13:31:16 2024) Chrom 20: |====================|====================| 53.28%, 122 / 229 (Thu Oct 17 13:31:16 2024) Chrom 21: |====================|====================| 50.79%, 64 / 126 (Thu Oct 17 13:31:16 2024) Chrom 22: |====================|====================| 51.72%, 60 / 116 (Thu Oct 17 13:31:16 2024) 4,763 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) = 8025 MLE IBD: Thu Oct 17 13:31:16 2024 0% MLE IBD: Thu Oct 17 13:31:17 2024 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: 0.536, sd: 0.286 MLE IBD: the sum of all selected genotypes (0,1,2) = 6690 MLE IBD: Thu Oct 17 13:31:17 2024 0% MLE IBD: Thu Oct 17 13:31:17 2024 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 Thu Oct 17 13:31:17 2024 (internal increment: 65536) [..................................................] 0%, ETC: --- [==================================================] 100%, completed, 0s Thu Oct 17 13:31:17 2024 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 Thu Oct 17 13:31:17 2024 (internal increment: 65536) [..................................................] 0%, ETC: --- [==================================================] 100%, completed, 0s Thu Oct 17 13:31:17 2024 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 Thu Oct 17 13:31:18 2024 (internal increment: 65536) [..................................................] 0%, ETC: --- [==================================================] 100%, completed, 0s Thu Oct 17 13:31:18 2024 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 Thu Oct 17 13:31:18 2024 (internal increment: 65536) [..................................................] 0%, ETC: --- [==================================================] 100%, completed, 0s Thu Oct 17 13:31:18 2024 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 Thu Oct 17 13:31:18 2024 (internal increment: 65536) [..................................................] 0%, ETC: --- [==================================================] 100%, completed, 0s Thu Oct 17 13:31:18 2024 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 Thu Oct 17 13:31:18 2024 (internal increment: 65536) [..................................................] 0%, ETC: --- [==================================================] 100%, completed, 0s Thu Oct 17 13:31:18 2024 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 Thu Oct 17 13:31:19 2024 (internal increment: 65536) [..................................................] 0%, ETC: --- [==================================================] 100%, completed, 0s Thu Oct 17 13:31:19 2024 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 Thu Oct 17 13:31:19 2024 (internal increment: 65536) [..................................................] 0%, ETC: --- [==================================================] 100%, completed, 1s Thu Oct 17 13:31:20 2024 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 139 SNPs (monomorphic: TRUE, MAF: 0.005, missing rate: 0.05) # of samples: 279 # of SNPs: 8,584 using 1 thread sliding window: 500,000 basepairs, Inf SNPs |LD| threshold: 0.2 method: composite Chrom 1: |====================|====================| 74.30%, 532 / 716 (Thu Oct 17 13:31:21 2024) Chrom 2: |====================|====================| 72.24%, 536 / 742 (Thu Oct 17 13:31:21 2024) Chrom 3: |====================|====================| 73.40%, 447 / 609 (Thu Oct 17 13:31:21 2024) Chrom 4: |====================|====================| 72.42%, 407 / 562 (Thu Oct 17 13:31:21 2024) Chrom 5: |====================|====================| 75.80%, 429 / 566 (Thu Oct 17 13:31:21 2024) Chrom 6: |====================|====================| 73.81%, 417 / 565 (Thu Oct 17 13:31:21 2024) Chrom 7: |====================|====================| 75.21%, 355 / 472 (Thu Oct 17 13:31:21 2024) Chrom 8: |====================|====================| 69.67%, 340 / 488 (Thu Oct 17 13:31:21 2024) Chrom 9: |====================|====================| 76.92%, 320 / 416 (Thu Oct 17 13:31:21 2024) Chrom 10: |====================|====================| 73.08%, 353 / 483 (Thu Oct 17 13:31:21 2024) Chrom 11: |====================|====================| 76.51%, 342 / 447 (Thu Oct 17 13:31:21 2024) Chrom 12: |====================|====================| 74.71%, 319 / 427 (Thu Oct 17 13:31:21 2024) Chrom 13: |====================|====================| 76.74%, 264 / 344 (Thu Oct 17 13:31:21 2024) Chrom 14: |====================|====================| 76.24%, 215 / 282 (Thu Oct 17 13:31:21 2024) Chrom 15: |====================|====================| 75.95%, 199 / 262 (Thu Oct 17 13:31:21 2024) Chrom 16: |====================|====================| 70.86%, 197 / 278 (Thu Oct 17 13:31:21 2024) Chrom 17: |====================|====================| 76.33%, 158 / 207 (Thu Oct 17 13:31:21 2024) Chrom 18: |====================|====================| 73.31%, 195 / 266 (Thu Oct 17 13:31:21 2024) Chrom 19: |====================|====================| 82.50%, 99 / 120 (Thu Oct 17 13:31:21 2024) Chrom 20: |====================|====================| 70.31%, 161 / 229 (Thu Oct 17 13:31:21 2024) Chrom 21: |====================|====================| 75.40%, 95 / 126 (Thu Oct 17 13:31:21 2024) Chrom 22: |====================|====================| 75.86%, 88 / 116 (Thu Oct 17 13:31:21 2024) 6,468 markers are selected in total. List of 22 $ chr1 : int [1:532] 1 2 4 5 7 10 12 14 15 16 ... $ chr2 : int [1:536] 717 718 719 720 721 723 724 725 726 727 ... $ chr3 : int [1:447] 1459 1461 1464 1466 1468 1469 1471 1472 1473 1476 ... $ chr4 : int [1:407] 2068 2069 2070 2071 2072 2074 2075 2076 2077 2078 ... $ chr5 : int [1:429] 2630 2631 2635 2636 2637 2638 2640 2642 2643 2645 ... $ chr6 : int [1:417] 3196 3197 3198 3200 3201 3204 3205 3206 3207 3208 ... $ chr7 : int [1:355] 3761 3762 3763 3766 3767 3768 3770 3771 3772 3773 ... $ chr8 : int [1:340] 4233 4234 4235 4236 4237 4238 4239 4240 4241 4242 ... $ chr9 : int [1:320] 4721 4722 4724 4727 4728 4730 4731 4732 4733 4735 ... $ chr10: int [1:353] 5138 5139 5140 5143 5144 5145 5146 5147 5148 5149 ... $ chr11: int [1:342] 5620 5623 5624 5625 5626 5628 5629 5630 5631 5632 ... $ chr12: int [1:319] 6067 6068 6069 6070 6073 6074 6075 6077 6078 6079 ... $ chr13: int [1:264] 6494 6497 6498 6499 6500 6501 6503 6505 6507 6509 ... $ chr14: int [1:215] 6840 6841 6842 6843 6844 6845 6846 6847 6848 6850 ... $ chr15: int [1:199] 7120 7121 7122 7124 7125 7126 7127 7128 7129 7130 ... $ chr16: int [1:197] 7382 7383 7384 7385 7387 7388 7389 7391 7392 7394 ... $ chr17: int [1:158] 7660 7661 7662 7663 7664 7665 7666 7667 7668 7669 ... $ chr18: int [1:195] 7867 7868 7869 7870 7871 7872 7873 7874 7875 7877 ... $ chr19: int [1:99] 8133 8135 8136 8137 8138 8139 8140 8141 8142 8144 ... $ chr20: int [1:161] 8253 8254 8257 8258 8259 8260 8261 8262 8265 8266 ... $ chr21: int [1:95] 8482 8484 8485 8486 8487 8488 8489 8490 8491 8492 ... $ chr22: int [1:88] 8608 8609 8610 8612 8613 8614 8615 8617 8618 8620 ... 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 Thu Oct 17 13:31:21 2024 (internal increment: 13960) [..................................................] 0%, ETC: --- [==================================================] 100%, completed, 1s Thu Oct 17 13:31:22 2024 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 Thu Oct 17 13:31:22 2024 (internal increment: 13960) [..................................................] 0%, ETC: --- [==================================================] 100%, completed, 0s Saving to the GDS file: [..................................................] 0%, ETC: --- [==================================================] 100%, completed, 1s Thu Oct 17 13:31:23 2024 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 Thu Oct 17 13:31:23 2024 (internal increment: 13960) [..................................................] 0%, ETC: --- [==================================================] 100%, completed, 1s Saving to the GDS file: [..................................................] 0%, ETC: --- [==================================================] 100%, completed, 0s Thu Oct 17 13:31:24 2024 Done. GRM merging: open 'tmp1.gds' (3,400 variants) open 'tmp2.gds' (3,400 variants) Weight: 0.5, 0.5 Output: tmp.gds [..................................................] 0%, ETC: --- [==================================================] 100%, completed, 1s GRM merging: open 'tmp1.gds' (3,400 variants) open 'tmp2.gds' (3,400 variants) Weight: 0.5, 0.5 [..................................................] 0%, ETC: --- [==================================================] 100%, completed, 0s FUNCTION: snpgdsOpen FUNCTION: snpgdsOption FUNCTION: snpgdsPCA Principal Component Analysis (PCA) on genotypes: Excluding 365 SNPs on non-autosomes Excluding 1 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN) # 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 Thu Oct 17 13:31:25 2024 (internal increment: 13960) [..................................................] 0%, ETC: --- [==================================================] 100%, completed, 1s Thu Oct 17 13:31:26 2024 Begin (eigenvalues and eigenvectors) Thu Oct 17 13:31:26 2024 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 Thu Oct 17 13:31:26 2024 (internal increment: 13960) [..................................................] 0%, ETC: --- [==================================================] 100%, completed, 1s Thu Oct 17 13:31:27 2024 Begin (eigenvalues and eigenvectors) Thu Oct 17 13:31:27 2024 Done. SNP Correlation: # of samples: 279 # of SNPs: 9,088 using 1 thread Correlation: the sum of all selected genotypes (0,1,2) = 2553065 Thu Oct 17 13:31:27 2024 (internal increment: 65536) [..................................................] 0%, ETC: --- [==================================================] 100%, completed, 0s Thu Oct 17 13:31:27 2024 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 Thu Oct 17 13:31:27 2024 [..................................................] 0%, ETC: --- [==================================================] 100%, completed, 0s Thu Oct 17 13:31:27 2024 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 Thu Oct 17 13:31:28 2024 (internal increment: 13960) [..................................................] 0%, ETC: --- [==================================================] 100%, completed, 0s Thu Oct 17 13:31:28 2024 Begin (eigenvalues and eigenvectors) Thu Oct 17 13:31:28 2024 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 Thu Oct 17 13:31:28 2024 (internal increment: 65536) [..................................................] 0%, ETC: --- [==================================================] 100%, completed, 0s Thu Oct 17 13:31:28 2024 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 Thu Oct 17 13:31:29 2024 (internal increment: 13960) [..................................................] 0%, ETC: --- [==================================================] 100%, completed, 1s Thu Oct 17 13:31:30 2024 Begin (eigenvalues and eigenvectors) Thu Oct 17 13:31:30 2024 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 Thu Oct 17 13:31:30 2024 (internal increment: 65536) [..................................................] 0%, ETC: --- [==================================================] 100%, completed, 0s Thu Oct 17 13:31:30 2024 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 Thu Oct 17 13:31:30 2024 (internal increment: 65536) [..................................................] 0%, ETC: --- [==================================================] 100%, completed, 0s Thu Oct 17 13:31:30 2024 Done. FUNCTION: snpgdsPED2GDS Converting from GDS to PLINK PED: Output a MAP file DONE. Output a PED file ... Output: Thu Oct 17 13:31:30 2024 0% Output: Thu Oct 17 13:31:31 2024 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 Chrom 1: |====================|====================| 62.29%, 446 / 716 (Thu Oct 17 13:31:32 2024) Chrom 2: |====================|====================| 62.26%, 462 / 742 (Thu Oct 17 13:31:32 2024) Chrom 3: |====================|====================| 60.10%, 366 / 609 (Thu Oct 17 13:31:32 2024) Chrom 4: |====================|====================| 64.41%, 362 / 562 (Thu Oct 17 13:31:32 2024) Chrom 5: |====================|====================| 62.90%, 356 / 566 (Thu Oct 17 13:31:32 2024) Chrom 6: |====================|====================| 60.18%, 340 / 565 (Thu Oct 17 13:31:32 2024) Chrom 7: |====================|====================| 63.14%, 298 / 472 (Thu Oct 17 13:31:32 2024) Chrom 8: |====================|====================| 57.58%, 281 / 488 (Thu Oct 17 13:31:33 2024) Chrom 9: |====================|====================| 62.98%, 262 / 416 (Thu Oct 17 13:31:33 2024) Chrom 10: |====================|====================| 60.46%, 292 / 483 (Thu Oct 17 13:31:33 2024) Chrom 11: |====================|====================| 63.09%, 282 / 447 (Thu Oct 17 13:31:33 2024) Chrom 12: |====================|====================| 62.76%, 268 / 427 (Thu Oct 17 13:31:33 2024) Chrom 13: |====================|====================| 63.08%, 217 / 344 (Thu Oct 17 13:31:33 2024) Chrom 14: |====================|====================| 63.83%, 180 / 282 (Thu Oct 17 13:31:33 2024) Chrom 15: |====================|====================| 63.74%, 167 / 262 (Thu Oct 17 13:31:33 2024) Chrom 16: |====================|====================| 62.23%, 173 / 278 (Thu Oct 17 13:31:33 2024) Chrom 17: |====================|====================| 65.70%, 136 / 207 (Thu Oct 17 13:31:33 2024) Chrom 18: |====================|====================| 59.40%, 158 / 266 (Thu Oct 17 13:31:33 2024) Chrom 19: |====================|====================| 68.33%, 82 / 120 (Thu Oct 17 13:31:33 2024) Chrom 20: |====================|====================| 66.38%, 152 / 229 (Thu Oct 17 13:31:33 2024) Chrom 21: |====================|====================| 61.11%, 77 / 126 (Thu Oct 17 13:31:33 2024) Chrom 22: |====================|====================| 57.76%, 67 / 116 (Thu Oct 17 13:31:33 2024) 5,424 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: 0.508, sd: 0.281 MLE IBD: the sum of all selected genotypes (0,1,2) = 6317 MLE IBD: Thu Oct 17 13:31:33 2024 0% MLE IBD: Thu Oct 17 13:31:33 2024 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: 0.508, sd: 0.281 *** 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) = 6317 Thu Oct 17 13:31:33 2024 (internal increment: 65536) [..................................................] 0%, ETC: --- [==================================================] 100%, completed, 0s Thu Oct 17 13:31:33 2024 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: 0.508, sd: 0.281 MLE IBD: the sum of all selected genotypes (0,1,2) = 6317 MLE IBD: Thu Oct 17 13:31:33 2024 0% MLE IBD: Thu Oct 17 13:31:34 2024 100% Genotype matrix: 250 SNPs X 25 samples [1] -384.5064 [1] -379.8635 [1] -389.2882 [1] -390.0637 [1] -405.3267 [1] -386.6771 [1] -382.3052 [1] -375.7884 [1] -400.5859 [1] -379.9675 [1] -372.4947 [1] -372.3346 [1] -393.543 [1] -387.7755 [1] -373.858 [1] -380.4349 [1] -389.0108 [1] -402.2013 [1] -393.1451 [1] -388.5999 [1] -383.8134 [1] -376.6837 [1] -385.4354 [1] -378.9947 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 Chrom 1: |====================|====================| 62.29%, 446 / 716 (Thu Oct 17 13:31:34 2024) Chrom 2: |====================|====================| 62.26%, 462 / 742 (Thu Oct 17 13:31:34 2024) Chrom 3: |====================|====================| 60.10%, 366 / 609 (Thu Oct 17 13:31:34 2024) Chrom 4: |====================|====================| 64.41%, 362 / 562 (Thu Oct 17 13:31:34 2024) Chrom 5: |====================|====================| 62.90%, 356 / 566 (Thu Oct 17 13:31:34 2024) Chrom 6: |====================|====================| 60.18%, 340 / 565 (Thu Oct 17 13:31:34 2024) Chrom 7: |====================|====================| 63.14%, 298 / 472 (Thu Oct 17 13:31:34 2024) Chrom 8: |====================|====================| 57.58%, 281 / 488 (Thu Oct 17 13:31:34 2024) Chrom 9: |====================|====================| 62.98%, 262 / 416 (Thu Oct 17 13:31:34 2024) Chrom 10: |====================|====================| 60.46%, 292 / 483 (Thu Oct 17 13:31:34 2024) Chrom 11: |====================|====================| 63.09%, 282 / 447 (Thu Oct 17 13:31:34 2024) Chrom 12: |====================|====================| 62.76%, 268 / 427 (Thu Oct 17 13:31:34 2024) Chrom 13: |====================|====================| 63.08%, 217 / 344 (Thu Oct 17 13:31:34 2024) Chrom 14: |====================|====================| 63.83%, 180 / 282 (Thu Oct 17 13:31:34 2024) Chrom 15: |====================|====================| 63.74%, 167 / 262 (Thu Oct 17 13:31:34 2024) Chrom 16: |====================|====================| 62.23%, 173 / 278 (Thu Oct 17 13:31:34 2024) Chrom 17: |====================|====================| 65.70%, 136 / 207 (Thu Oct 17 13:31:34 2024) Chrom 18: |====================|====================| 59.40%, 158 / 266 (Thu Oct 17 13:31:34 2024) Chrom 19: |====================|====================| 68.33%, 82 / 120 (Thu Oct 17 13:31:34 2024) Chrom 20: |====================|====================| 66.38%, 152 / 229 (Thu Oct 17 13:31:34 2024) Chrom 21: |====================|====================| 61.11%, 77 / 126 (Thu Oct 17 13:31:34 2024) Chrom 22: |====================|====================| 57.76%, 67 / 116 (Thu Oct 17 13:31:34 2024) 5,424 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: 0.508, sd: 0.281 MLE IBD: the sum of all selected genotypes (0,1,2) = 6317 MLE IBD: Thu Oct 17 13:31:34 2024 0% MLE IBD: Thu Oct 17 13:31:35 2024 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: 0.508, sd: 0.281 *** 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) = 6317 Thu Oct 17 13:31:35 2024 (internal increment: 65536) [..................................................] 0%, ETC: --- [==================================================] 100%, completed, 0s Thu Oct 17 13:31:35 2024 Done. Genotype matrix: 250 SNPs X 25 samples [1] -384.5064 [1] -379.8635 [1] -389.2882 [1] -390.0637 [1] -405.3267 [1] -386.6771 [1] -382.3052 [1] -375.7884 [1] -400.5859 [1] -379.9675 [1] -372.4947 [1] -372.3346 [1] -393.543 [1] -387.7755 [1] -373.858 [1] -380.4349 [1] -389.0108 [1] -402.2013 [1] -393.1451 [1] -388.5999 [1] -383.8134 [1] -376.6837 [1] -385.4354 [1] -378.9947 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-3.19-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 Thu Oct 17 13:31:37 2024, Chromosome 1 (716 SNPs), 2448 windows Thu Oct 17 13:31:37 2024, Chromosome 2 (742 SNPs), 2416 windows Thu Oct 17 13:31:37 2024, Chromosome 3 (609 SNPs), 1985 windows Thu Oct 17 13:31:37 2024, Chromosome 4 (562 SNPs), 1894 windows Thu Oct 17 13:31:38 2024, Chromosome 5 (566 SNPs), 1797 windows Thu Oct 17 13:31:38 2024, Chromosome 6 (565 SNPs), 1694 windows Thu Oct 17 13:31:38 2024, Chromosome 7 (472 SNPs), 1573 windows Thu Oct 17 13:31:38 2024, Chromosome 8 (488 SNPs), 1445 windows Thu Oct 17 13:31:38 2024, Chromosome 9 (416 SNPs), 1393 windows Thu Oct 17 13:31:38 2024, Chromosome 10 (483 SNPs), 1343 windows Thu Oct 17 13:31:38 2024, Chromosome 11 (447 SNPs), 1338 windows Thu Oct 17 13:31:38 2024, Chromosome 12 (427 SNPs), 1316 windows Thu Oct 17 13:31:38 2024, Chromosome 13 (344 SNPs), 948 windows Thu Oct 17 13:31:38 2024, Chromosome 14 (281 SNPs), 847 windows Thu Oct 17 13:31:39 2024, Chromosome 15 (262 SNPs), 774 windows Thu Oct 17 13:31:39 2024, Chromosome 16 (278 SNPs), 873 windows Thu Oct 17 13:31:39 2024, Chromosome 17 (207 SNPs), 773 windows Thu Oct 17 13:31:39 2024, Chromosome 18 (266 SNPs), 753 windows Thu Oct 17 13:31:39 2024, Chromosome 19 (120 SNPs), 627 windows Thu Oct 17 13:31:39 2024, Chromosome 20 (229 SNPs), 602 windows Thu Oct 17 13:31:39 2024, Chromosome 21 (126 SNPs), 311 windows Thu Oct 17 13:31:39 2024, Chromosome 22 (116 SNPs), 312 windows Thu Oct 17 13:31:39 2024, Chromosome 23 (358 SNPs), 1507 windows Thu Oct 17 13:31:39 2024 Done. FUNCTION: snpgdsSummary The file name: /Library/Frameworks/R.framework/Versions/4.4-x86_64/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-3.19-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-3.19-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/4.4-x86_64/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-3.19-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/4.4-x86_64/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-3.19-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/4.4-x86_64/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-3.19-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/4.4-x86_64/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-3.19-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/4.4-x86_64/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-3.19-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/4.4-x86_64/Resources/library/SNPRelate/extdata/sequence.vcf content: 5 rows x 12 columns Thu Oct 17 13:31:41 2024 store sample id, snp id, position, and chromosome. start writing: 3 samples, 2 SNPs ... file: /Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/SNPRelate/extdata/sequence.vcf [1] 1 Thu Oct 17 13:31:41 2024 Done. The file name: /Users/biocbuild/bbs-3.19-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/4.4-x86_64/Resources/library/SNPRelate/extdata/sequence.vcf content: 5 rows x 12 columns Thu Oct 17 13:31:41 2024 store sample id, snp id, position, and chromosome. start writing: 3 samples, 2 SNPs ... file: /Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/SNPRelate/extdata/sequence.vcf [1] 1 Thu Oct 17 13:31:41 2024 Done. The file name: /Users/biocbuild/bbs-3.19-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/4.4-x86_64/Resources/library/SNPRelate/extdata/sequence.vcf content: 5 rows x 12 columns Thu Oct 17 13:31:41 2024 store sample id, snp id, position, and chromosome. start writing: 3 samples, 5 SNPs ... file: /Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/SNPRelate/extdata/sequence.vcf Thu Oct 17 13:31:41 2024 Done. Some of 'snp.allele' are not standard (e.g., A/G,T). The file name: /Users/biocbuild/bbs-3.19-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/4.4-x86_64/Resources/library/SNPRelate/extdata/sequence.vcf content: 5 rows x 12 columns Thu Oct 17 13:31:41 2024 store sample id, snp id, position, and chromosome. start writing: 3 samples, 5 SNPs ... file: /Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/SNPRelate/extdata/sequence.vcf Thu Oct 17 13:31:41 2024 Done. Some of 'snp.allele' are not standard (e.g., A/G,T). The file name: /Users/biocbuild/bbs-3.19-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 Thu Oct 17 13:31:43 2024 (internal increment: 65536) [..................................................] 0%, ETC: --- [==================================================] 100%, completed, 0s Thu Oct 17 13:31:43 2024 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 Thu Oct 17 13:31:43 2024 [..................................................] 0%, ETC: --- [==================================================] 100%, completed, 0s Thu Oct 17 13:31:43 2024 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 Thu Oct 17 13:31:43 2024 (internal increment: 65536) [..................................................] 0%, ETC: --- [==================================================] 100%, completed, 0s Thu Oct 17 13:31:43 2024 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 Thu Oct 17 13:31:43 2024 (internal increment: 65536) [..................................................] 0%, ETC: --- [==================================================] 100%, completed, 0s Thu Oct 17 13:31:43 2024 Done. SNP Correlation: # of samples: 90 # of SNPs: 9,088 using 2 threads Correlation: the sum of all selected genotypes (0,1,2) = 824424 Thu Oct 17 13:31:44 2024 (internal increment: 65536) [..................................................] 0%, ETC: --- [==================================================] 100%, completed, 0s Thu Oct 17 13:31:44 2024 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 Thu Oct 17 13:31:44 2024 [..................................................] 0%, ETC: --- [==================================================] 100%, completed, 0s Thu Oct 17 13:31:44 2024 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 Thu Oct 17 13:31:44 2024 (internal increment: 65536) [..................................................] 0%, ETC: --- [==================================================] 100%, completed, 0s Thu Oct 17 13:31:44 2024 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 Thu Oct 17 13:31:44 2024 (internal increment: 65536) [..................................................] 0%, ETC: --- [==================================================] 100%, completed, 0s Thu Oct 17 13:31:44 2024 Done. RUNIT TEST PROTOCOL -- Thu Oct 17 13:31:44 2024 *********************************************** 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 60.483 5.090 78.582
SNPRelate.Rcheck/SNPRelate-Ex.timings
name | user | system | elapsed | |
SNPGDSFileClass-class | 0.089 | 0.012 | 0.121 | |
SNPRelate-package | 2.123 | 0.271 | 2.797 | |
snpgdsAdmixPlot | 0.860 | 0.027 | 1.021 | |
snpgdsAdmixProp | 0.816 | 0.026 | 0.970 | |
snpgdsAlleleSwitch | 0.164 | 0.017 | 0.204 | |
snpgdsApartSelection | 0.249 | 0.023 | 0.311 | |
snpgdsBED2GDS | 0.212 | 0.046 | 0.302 | |
snpgdsClose | 0.058 | 0.003 | 0.067 | |
snpgdsCombineGeno | 0.185 | 0.094 | 0.368 | |
snpgdsCreateGeno | 0.737 | 0.030 | 0.879 | |
snpgdsCreateGenoSet | 0.329 | 0.052 | 0.483 | |
snpgdsCutTree | 3.424 | 0.171 | 4.050 | |
snpgdsDiss | 2.714 | 0.028 | 3.070 | |
snpgdsDrawTree | 2.329 | 0.034 | 2.649 | |
snpgdsEIGMIX | 0.752 | 0.029 | 0.886 | |
snpgdsErrMsg | 0.000 | 0.000 | 0.001 | |
snpgdsExampleFileName | 0.001 | 0.001 | 0.002 | |
snpgdsFst | 0.059 | 0.012 | 0.077 | |
snpgdsGDS2BED | 0.112 | 0.029 | 0.166 | |
snpgdsGDS2Eigen | 1.122 | 0.236 | 1.532 | |
snpgdsGDS2PED | 0.712 | 0.141 | 1.016 | |
snpgdsGEN2GDS | 0.000 | 0.000 | 0.001 | |
snpgdsGRM | 1.847 | 0.062 | 2.316 | |
snpgdsGetGeno | 0.097 | 0.024 | 0.144 | |
snpgdsHCluster | 2.745 | 0.062 | 3.170 | |
snpgdsHWE | 0.030 | 0.007 | 0.045 | |
snpgdsIBDKING | 3.179 | 0.133 | 3.717 | |
snpgdsIBDMLE | 0.946 | 0.040 | 1.137 | |
snpgdsIBDMLELogLik | 0.988 | 0.040 | 1.199 | |
snpgdsIBDMoM | 0.491 | 0.069 | 0.684 | |
snpgdsIBDSelection | 0.174 | 0.024 | 0.235 | |
snpgdsIBS | 0.434 | 0.017 | 0.546 | |
snpgdsIBSNum | 0.562 | 0.051 | 0.713 | |
snpgdsIndInb | 0.052 | 0.005 | 0.066 | |
snpgdsIndInbCoef | 0.011 | 0.003 | 0.020 | |
snpgdsIndivBeta | 0.312 | 0.010 | 0.375 | |
snpgdsLDMat | 0.443 | 0.050 | 0.632 | |
snpgdsLDpair | 0.006 | 0.004 | 0.015 | |
snpgdsLDpruning | 0.272 | 0.041 | 0.376 | |
snpgdsMergeGRM | 3.093 | 0.167 | 3.976 | |
snpgdsOpen | 0.052 | 0.004 | 0.075 | |
snpgdsOption | 0.004 | 0.003 | 0.009 | |
snpgdsPCA | 0.986 | 0.050 | 1.240 | |
snpgdsPCACorr | 1.030 | 0.060 | 1.278 | |
snpgdsPCASNPLoading | 1.062 | 0.028 | 1.261 | |
snpgdsPCASampLoading | 0.774 | 0.021 | 0.925 | |
snpgdsPED2GDS | 2.009 | 0.204 | 2.643 | |
snpgdsPairIBD | 1.470 | 0.060 | 1.708 | |
snpgdsPairIBDMLELogLik | 0.799 | 0.045 | 0.953 | |
snpgdsPairScore | 0.430 | 0.179 | 0.693 | |
snpgdsSNPList | 0.014 | 0.004 | 0.020 | |
snpgdsSNPListIntersect | 0.093 | 0.006 | 0.108 | |
snpgdsSNPRateFreq | 0.243 | 0.012 | 0.269 | |
snpgdsSampMissRate | 0.010 | 0.002 | 0.014 | |
snpgdsSelectSNP | 0.011 | 0.003 | 0.015 | |
snpgdsSlidingWindow | 1.961 | 0.110 | 2.251 | |
snpgdsSummary | 0.127 | 0.006 | 0.153 | |
snpgdsTranspose | 0.255 | 0.024 | 0.325 | |
snpgdsVCF2GDS | 0.485 | 0.440 | 1.143 | |
snpgdsVCF2GDS_R | 0.198 | 0.221 | 0.520 | |