Copyright © 2007-2024 The OpenMx Project
We are pleased to announce the official release of OpenMx version 2.19.1. Click here [1] for instructions on how to install the package from our repository. As usual, our repository has package binaries for Windows and macOS, and source tarballs for Linux/GNU and other non-Mac Unix-likes, all of which come with the proprietary NPSOL optimizer. Alternately, users may install the fully open-source build of the new version from CRAN.
We are excited to report that, a few weeks prior to this new version release, our manuscript documenting OpenMx's GREML [2] (Genomic-relatedness-matrix REstricted Maximum Likelihood) feature was published online (click here [3] to read it)! Consequently, we wish to highlight several new "mxGREML"-related developments included in OpenMx 2.19:
mxAutoStart()
[9] is now compatible with the GREML expectation [2] type.
A repository of example scripts that demonstrate the mxGREML feature is available here [10].
Although the package gwsem [11] has been available on CRAN for some time already, the article documenting how to use it [12] is finally out. If you didn't know already, most genome-wide association study (GWAS) analyses test the association between single-nucleotide polymorphisms (SNPs) and a single trait or outcome. While multivariate GWAS opens up a broad new landscape of feasible and informative analyses, its adoption has been slow. An OpenMx add-on, gwsem [11], overcomes the inherent computational challenges associated with multivariate GWAS. In the associated article [12], we conducted (1) a series of GWAS using three substance use frequency items from data in the UK Biobank, (2) a timing study for several predefined GWAS functions, and (3) a Type I Error rate study. Our multivariate GWAS analyses emphasize the utility of GW-SEM for identifying novel patterns of associations that vary considerably between genomic loci for specific substances, highlighting the importance of differentiating between substance-specific use behaviors and polysubstance use.
rowwiseParallel
to mxFitFunctionML()
[14] is NA
(which is now its default).
mxSE()
[15] is now faster, since the elements of its Jacobian matrix are now calculated in parallel.
mxPath()
[16] now accepts argument arrows=0
, which forms a "co-path" representing Pearson-Aitken selection (see example here [17]).
mxGenerateData()
[21] no longer fails with an unhelpful error if it is passed a model with definition variables but no data.
mxAutoStart()
[9] no longer fails with an error when given a model that has a custom compute plan containing an MxComputeConfidenceInterval [22] step.
runstate
slot unnecessarily stores the pre-run states of MxMatrices and MxAlgebras that are modified during runtime. Thus, the runstate
slot expands the memory footprint of many mxGREML [2] models by around 50%. We plan to eliminate the runstate
slot in the next OpenMx release.
mxCompare()
[25] works correctly with WLS [18] models only some of the time.
mxModelAverage()
[26] fails with an unhelpful error if any of reference
quantities have variances of NaN
in any of the MxModels in argument models
.
Links
[1] http://openmx.ssri.psu.edu/installing-openmx
[2] https://openmx.ssri.psu.edu/docs/OpenMx/latest/_static/Rdoc/mxExpectationGREML.html
[3] https://link.springer.com/epdf/10.1007/s10519-020-10037-5?sharing_token=INP3yfEWSSnRrYbud5tdYfe4RwlQNchNByi7wbcMAY4aTpj44ctBtFDRh5Lkg8swWAczdWQ-Kf_47MDcL0tMCPA_WmVJpBMbDNIC6KKC2pak0KM1RcUyx99HUIeT89ie5k_-_ngpM5mtAqCah1mvu_lSEj6v99a6Vyf5l_DRynM%3D
[4] https://openmx.ssri.psu.edu/docs/OpenMx/latest/_static/Rdoc/mxFitFunctionGREML.html
[5] https://openmx.ssri.psu.edu/docs/OpenMx/latest/_static/Rdoc/mxMatrix.html
[6] https://openmx.ssri.psu.edu/docs/OpenMx/latest/_static/Rdoc/mxAlgebra.html
[7] https://openmx.ssri.psu.edu/docs/OpenMx/latest/_static/Rdoc/mxComputeNewtonRaphson.html
[8] https://openmx.ssri.psu.edu/docs/OpenMx/latest/_static/Rdoc/mxComputeStandardError.html
[9] https://openmx.ssri.psu.edu/docs/OpenMx/latest/_static/Rdoc/mxAutoStart.html
[10] https://github.com/RMKirkpatrick/mxGREMLdemos
[11] https://cran.r-project.org/package=gwsem
[12] https://link.springer.com/epdf/10.1007/s10519-021-10043-1
[13] https://openmx.ssri.psu.edu/docs/OpenMx/latest/_static/Rdoc/mxConstraint.html
[14] https://openmx.ssri.psu.edu/docs/OpenMx/latest/_static/Rdoc/mxFitFunctionML.html
[15] https://openmx.ssri.psu.edu/docs/OpenMx/latest/_static/Rdoc/mxSE.html
[16] https://openmx.ssri.psu.edu/docs/OpenMx/latest/_static/Rdoc/mxPath.html
[17] https://raw.githubusercontent.com/OpenMx/OpenMx/master/tests/testthat/test-pearsonSel.R
[18] https://openmx.ssri.psu.edu/docs/OpenMx/latest/_static/Rdoc/mxFitFunctionWLS.html
[19] https://openmx.ssri.psu.edu/docs/OpenMx/latest/_static/Rdoc/mxCI.html
[20] https://openmx.ssri.psu.edu/docs/OpenMx/latest/_static/Rdoc/mxOption.html
[21] https://openmx.ssri.psu.edu/docs/OpenMx/latest/_static/Rdoc/mxGenerateData.html
[22] https://openmx.ssri.psu.edu/docs/OpenMx/latest/_static/Rdoc/mxComputeConfidenceInterval.html
[23] https://openmx.ssri.psu.edu/docs/OpenMx/latest/_static/Rdoc/mxExpectationRAM.html
[24] https://openmx.ssri.psu.edu/docs/OpenMx/latest/_static/Rdoc/MxModel-class.html
[25] https://openmx.ssri.psu.edu/docs/OpenMx/latest/_static/Rdoc/mxCompare.html
[26] https://openmx.ssri.psu.edu/docs/OpenMx/latest/_static/Rdoc/MxMMI.html
[27] https://github.com/OpenMx/OpenMx/issues