Title: Automatic Phenotyping of Electronic Health Record at Visit
Description: Using Electronic Health Record (EHR) is difficult because most of the time the true characteristic of the patient is not available. Instead we can retrieve the International Classification of Disease code related to the disease of interest or we can count the occurrence of the Unified Medical Language System. None of them is the true phenotype which needs chart review to identify. However chart review is time consuming and costly. 'PheVis' is an algorithm which is phenotyping (i.e identify a characteristic) at the visit level in an unsupervised fashion. It can be used for chronic or acute diseases. An example of how to use 'PheVis' is available in the vignette. Basically there are two functions that are to be used: `train_phevis()` which trains the algorithm and `test_phevis()` which get the predicted probabilities. The detailed method is described in preprint by Ferté et al. (2020) <doi:10.1101/2020.06.15.20131458>.
Imports: dplyr, ggplot2, glmnet, knitr, lme4, purrr, randomForest, Rcpp

Title: A Tool for Phenotypic Data Processing
Authors@R: person(given = "Peng", family = "Zhao", email = "pengzhao@nwafu.edu.cn", role  = c("aut", "cre"))
Description: Large-scale phenotypic data processing is essential in research. Researchers need to eliminate outliers from the data in order to obtain true and reliable results. Best linear unbiased prediction (BLUP) is a standard method for estimating random effects of a mixed model. This method can be used to process phenotypic data under different conditions and is widely used in animal and plant breeding. The 'Phenotype' can remove outliers from phenotypic data and performs the best linear unbiased prediction (BLUP), help researchers quickly complete phenotypic data analysis. H.P.Piepho. (2008) <doi:10.1007/s10681-007-9449-8>.
Packaged: 2020-07-31 08:03:53 UTC; Misosugar

Title: Flexible Phenotype Simulation from Different Genetic and Noise
person("Hannah", "Meyer", email = "hannah@ebi.ac.uk", role = c("aut", "cre")),
person("Konrad", "Rudolph", email = "konrad.rudolph@gmail.com", role = "ctb")
Description: Phenotype simulator allows for the flexible simulation of
phenotypes under different models, including fixed and background genetic
effects as well as correlated, fixed and background noise effects. Different
phenotypic effects can be combined into a final phenotype while controling
for the proportion of variance explained by each of the components. For each
component, the number of variables, their distribution and the design of
their effect across traits can be customised. The final simulated phenotypes
and its components can be automatically saved into .rds or .csv files. In
addition, for simulated genotypes, export into plink format is possible.
Imports: methods, optparse, R.utils, plyr, mvtnorm, snpStats, Rcpp (>=