# lfa Logistic factor analysis ## Installation To install latest version on Bioconductor, open R and type: ```R if (!requireNamespace("BiocManager", quietly = TRUE)) install.packages("BiocManager") BiocManager::install("lfa") ``` You can also install development version from GitHub this way: ```R install.packages("devtools") library("devtools") install_github("Storeylab/lfa") ``` Apple OS X users, see Troubleshooting below. ## Data input We recommend using the `genio` or `BEDMatrix` packages to read genotype data into an R matrix. Be warned that genotype matrices from `genio` and some `lfa` functions require a lot of memory. As a rule of thumb, the in memory sizes of a few relevant genotype matrices: - 431345 SNPs by 940 individuals: 1.5 GB needed for genotype matrix, about 9 GB to run `lfa`. - 339100 SNPs by 1500 individuals: 1.9 GB needed for genotype matrix, about 11.5 GB to run `lfa`. `BEDMatrix` inputs consume much less memory but can be slower otherwise. ## Troubleshooting Apple OS X users may experience a problem due to Fortran code that is included in this package. You must install the X code command line tools (XCode CLI) and `gfortran`. Try the following commands on terminal: ``` xcode-select --install brew install gcc ``` If XCode installation fails, you may have to sign up on Apple Developer: https://www.ics.uci.edu/~pattis/common/handouts/macmingweclipse/allexperimental/macxcodecommandlinetools.html Alternatively, this Installer Package for macOS R toolchain may work https://github.com/rmacoslib/r-macos-rtools/ ## Citations Hao, Wei, Minsun Song, and John D. Storey. "Probabilistic Models of Genetic Variation in Structured Populations Applied to Global Human Studies." Bioinformatics 32, no. 5 (March 1, 2016): 713–21. [doi:10.1093/bioinformatics/btv641](https://doi.org/10.1093/bioinformatics/btv641). [arXiv](https://arxiv.org/abs/1312.2041).