markcharder
commented
4 years ago Just a quick update to this issue. I've found that when I run the example multivariate model found here), I stumble upon the same issue. For example:
using JWAS,JWAS.Datasets,DataFrames,CSV
phenofile = Datasets.dataset("example","phenotypes.txt")
pedfile = Datasets.dataset("example","pedigree.txt")
genofile = Datasets.dataset("example","genotypes.txt")
phenotypes = CSV.read(phenofile,delim = ',',header=true,missingstrings=["NA"])
pedigree = get_pedigree(pedfile,separator=",",header=true);
model_equation2 ="y1 = intercept + x1 + x3 + ID + dam
y2 = intercept + x1 + x2 + x3 + ID
y3 = intercept + x1 + x1*x3 + x2 + ID";
model2 = build_model(model_equation2);
set_covariate(model2,"x1");
set_random(model2,"x2");
set_random(model2,"ID dam",pedigree);
add_genotypes(model2,genofile,separator=',');
out2=runMCMC(model2,phenotypes,methods="BayesC",estimatePi=true);
This produces the same error:
ERROR: MethodError: no method matching zero(::Type{Any})
Closest candidates are:
zero(::Type{Union{Missing, T}}) where T at missing.jl:105
zero(::Type{Missing}) at missing.jl:103
zero(::Type{LibGit2.GitHash}) at /buildworker/worker/package_linux64/build/usr/share/julia/stdlib/v1.4/LibGit2/src/oid.jl:220
...
Stacktrace:
[1] zero(::Type{Any}) at ./missing.jl:105
[2] _zeros_eltypes at /buildworker/worker/package_linux64/build/usr/share/julia/stdlib/v1.4/SparseArrays/src/higherorderfns.jl:204 [inlined]
[3] _noshapecheck_map(::typeof(+), ::SparseArrays.SparseMatrixCSC{Any,Int64}, ::SparseArrays.SparseMatrixCSC{Float64,Int64}) at /buildworker/worker/package_linux64/build/usr/share/julia/stdlib/v1.4/SparseArrays/src/higherorderfns.jl:159
[4] map(::typeof(+), ::SparseArrays.SparseMatrixCSC{Any,Int64}, ::SparseArrays.SparseMatrixCSC{Float64,Int64}) at /buildworker/worker/package_linux64/build/usr/share/julia/stdlib/v1.4/SparseArrays/src/higherorderfns.jl:1153
[5] +(::SparseArrays.SparseMatrixCSC{Any,Int64}, ::SparseArrays.SparseMatrixCSC{Float64,Int64}) at /buildworker/worker/package_linux64/build/usr/share/julia/stdlib/v1.4/SparseArrays/src/sparsematrix.jl:1648
[6] addVinv(::JWAS.MME) at /home/mark/.julia/packages/JWAS/4xynz/src/1.JWAS/src/buildMME/random_effects.jl:209
[7] getMME(::JWAS.MME, ::DataFrame) at /home/mark/.julia/packages/JWAS/4xynz/src/1.JWAS/src/buildMME/build_MME.jl:261
[8] init_mixed_model_equations(::JWAS.MME, ::DataFrame, ::Bool) at /home/mark/.julia/packages/JWAS/4xynz/src/1.JWAS/src/JWAS.jl:581
[9] runMCMC(::JWAS.MME, ::DataFrame; heterogeneous_residuals::Bool, chain_length::Int64, starting_value::Bool, burnin::Int64, output_samples_frequency::Int64, update_priors_frequency::Int64, methods::String, estimate_variance::Bool, Pi::Float64, estimatePi::Bool, estimateScale::Bool, single_step_analysis::Bool, pedigree::Bool, categorical_trait::Bool, missing_phenotypes::Bool, constraint::Bool, causal_structure::Bool, outputEBV::Bool, output_heritability::Bool, seed::Bool, printout_model_info::Bool, printout_frequency::Int64, big_memory::Bool, double_precision::Bool, output_samples_file::String, output_samples_for_all_parameters::Bool) at /home/mark/.julia/packages/JWAS/4xynz/src/1.JWAS/src/JWAS.jl:252
[10] top-level scope at REPL[19]:1
fmorgante
rohanLuigi
reworkhow
I am hoping to fit a multiple trait Bayesian genomic prediction model using the JWAS package. I've managed to run the tutorials without any issues. However, when I apply the model to my own data, I get an error message. I've checked and re-checked the format of the data, which, as far as I can tell, is fine. In fact, the analysis will run for a single trait model but only throws the error for a multi-trait model.
Here is a snippet of some preliminary code that I ran recently:
This is what the phenotypes file looks like:
This is what the genotypes file looks like:
The error message that I get from running this model is as follows:
I would really appreciate if anybody can figure out what the issue might be. Sorry for such a long message.
Mark