Closed huangl12138 closed 6 years ago
What is your operating system? Sometimes the web connection can also effect the installation. Please send me more information
I have fix it for reinstall RcppEigen but another issue when run MVP
#--------------------------------------Welcome to MVP--------------------------------------#
# A Memory-efficient, Visualization-enhanced, and Parallel-accelerated Tool For GWAS #
# Version: 0.1 #
# Authors: Lilin Yin, Haohao Zhang, Zhiwu Zhang, Xinyun Li, Shuhong Zhao, and Xiaolei Liu #
# Contact: xiaoleiliu@mail.hzau.edu.cn #
#------------------------------------------------------------------------------------------#
[1] "Input data has 308 individuals, 7349687 markers"
[1] "Principal Component Analysis Start ..."
means for first 10 snps:
[1] 0 0 0 0 0 0 0 0 0 0
[1] "GWAS Start..."
[1] "General Linear Model (GLM) Start ..."
|---------------------------------------------------------------------->100.00%
[1] "****************GLM ACCOMPLISHED****************"
[1] "Mixed Linear Model (MLM) Start ..."
Error in .local(x) :
long vectors not supported yet: ../../src/include/Rinlinedfuns.h:138
my Code is
for(i in 2:ncol(phenotype)){
+ imMVP <- MVP(
+ phe=phenotype[, c(1, i)],
+ geno=genotype,
+ map=map,
+ nPC.GLM=5,
+ nPC.MLM=3,
+ nPC.FarmCPU=3,
+ perc=1,
+ priority="speed",
+ ncpus=16,
+ vc.method="EMMA",
+ maxLoop=10,
+ method.bin="FaST-LMM",
+ threshold=0.05,
+ method=c("GLM", "MLM", "FarmCPU"),
+ file="pdf",
+ )
+ }
What is your operating system? Windows? Mac OS? LINUX? 32 bit? 64 bit? Are you using Microsoft R Open?
64 bit linux centos 6.4
when I use priority="memory",,nothing wrong Thank you!
Thank you for pointing out the issue and good to know that 'memory' version works. I will debug it when I have a data with 7 million markers.
rfunctions install error!
I install rfunctions Spectra/LinAlg/TridiagEigen.h:93:49: error: no matching function for call to 'tridiagonal_qr_step(double&, double&, int&, int&, Eigen::PlainObjectBase<Eigen::Matrix<double, -1, -1> >::Scalar*, int&)' Eigen::internal::tridiagonal_qr_step(maind, subd, start, end, evecs.data(), n);