We implement a common genotyping workflow with a standardized software interface. 'genotypeR' designs genotyping markers from vcf files, outputs markers for multiplexing suitability on various platforms (Sequenom and Illumina GoldenGate), and provides various QA/QC and analysis functions. We developed this package to analyze data in Stevison LS, SA Sefick, CA Rushton, and RM Graze. 2017. Invited Review: Recombination rate plasticity: revealing mechanisms by design. Philosophical Transactions Royal Society London B Biol Sci 372:1-14. <DOI:10.1098/rstb.2016.0459>, and have published it here Sefick, S.A., M.A. Castronova, and L.S. Stevison. 2017. GENOTYPER: An integrated R packages for single nuleotide polymorphism genotype marker design and data analysis. Methods in Ecology and Evolution 9: 1318-1323. <DOI: 10.1111/2041-210X.12965>.

Generalized PATHMOX Algorithm for PLS-PM, LS and LAD Regression
"Giuseppe Lamberti <giuseppelamb@hotmail.com> [aut, cre]"
genpathmox provides a very interesting solution for handling
segmentation variables in complex statistical methodology. It contains en
extended version of the PATHMOX algorithm in the context of partial least
square path modeling (Sanchez, 2009) including the F-block test (to detect
the responsible latent endogenous equations of the difference), the
F-coefficient (to detect the path coefficients responsible of the
difference) and the invariance test (to realize a comparison between the
sub-models' latent variables). Furthermore, the package contains a
generalized version of the PATHMOX algorithm to approach different
methodologies: linear regression and least absolute regression models.
R (>= 3.1.1),plspm, quantreg,mice,diagram, methods

Generalized Pathmox Approach Segmentation Tree Analysis
person("Giuseppe", "Lamberti", email = "giuseppelamb@hotmail.com",
role = c("aut", "cre"))
Provides a very interesting solution for
handling segmentation variables in complex statistical methodology. It
contains en extended version of the "Pathmox" algorithm (Lamberti, Sanchez
and Aluja,(2016)<doi:10.1002/asmb.2168>) in the context of
Partial Least Squares Path Modeling including the F-block
test (to detect the responsible latent endogenous equations of the
difference), the F-coefficient (to detect the path coefficients responsible
of the difference) and the "invariance" test (to realize a comparison
between the sub-models' latent variables). Furthermore, the package
contains a generalized version of the "Pathmox" algorithm to approach
different methodologies: linear regression and least absolute regression
models.
R (>= 3.1.2), stats, graphics, grDevices, utils, diagram,
methods, mice, plspm, quantreg,